From 2478eec9ccc8bcadb51904820a523e9e93265983 Mon Sep 17 00:00:00 2001 From: LukasMasuch Date: Thu, 10 Feb 2022 15:08:08 +0000 Subject: [PATCH] Update best-of list for version 2022.02.10 --- README.md | 6381 +++++++++++++++++-------------- history/2022-02-10_changes.md | 72 + history/2022-02-10_projects.csv | 923 +++++ latest-changes.md | 82 +- 4 files changed, 4631 insertions(+), 2827 deletions(-) create mode 100644 history/2022-02-10_changes.md create mode 100644 history/2022-02-10_projects.csv diff --git a/README.md b/README.md index a9998c7d..aac3ac9d 100644 --- a/README.md +++ b/README.md @@ -10,14 +10,14 @@

- +

-This curated list contains 890 awesome open-source projects with a total of 3.2M stars grouped into 33 categories. All projects are ranked by a project-quality score, which is calculated based on various metrics automatically collected from GitHub and different package managers. If you like to add or update projects, feel free to open an [issue](https://github.com/ml-tooling/best-of-ml-python/issues/new/choose), submit a [pull request](https://github.com/ml-tooling/best-of-ml-python/pulls), or directly edit the [projects.yaml](https://github.com/ml-tooling/best-of-ml-python/edit/main/projects.yaml). Contributions are very welcome! +This curated list contains 920 awesome open-source projects with a total of 3.3M stars grouped into 34 categories. All projects are ranked by a project-quality score, which is calculated based on various metrics automatically collected from GitHub and different package managers. If you like to add or update projects, feel free to open an [issue](https://github.com/ml-tooling/best-of-ml-python/issues/new/choose), submit a [pull request](https://github.com/ml-tooling/best-of-ml-python/pulls), or directly edit the [projects.yaml](https://github.com/ml-tooling/best-of-ml-python/edit/main/projects.yaml). Contributions are very welcome! --- @@ -33,37 +33,38 @@ This curated list contains 890 awesome open-source projects with a total of 3.2M - [Machine Learning Frameworks](#machine-learning-frameworks) _55 projects_ - [Data Visualization](#data-visualization) _50 projects_ -- [Text Data & NLP](#text-data--nlp) _90 projects_ -- [Image Data](#image-data) _56 projects_ -- [Graph Data](#graph-data) _32 projects_ -- [Audio Data](#audio-data) _27 projects_ -- [Geospatial Data](#geospatial-data) _21 projects_ -- [Financial Data](#financial-data) _23 projects_ +- [Text Data & NLP](#text-data--nlp) _96 projects_ +- [Image Data](#image-data) _60 projects_ +- [Graph Data](#graph-data) _36 projects_ +- [Audio Data](#audio-data) _28 projects_ +- [Geospatial Data](#geospatial-data) _22 projects_ +- [Financial Data](#financial-data) _25 projects_ - [Time Series Data](#time-series-data) _23 projects_ - [Medical Data](#medical-data) _19 projects_ -- [Tabular Data](#tabular-data) _3 projects_ +- [Tabular Data](#tabular-data) _4 projects_ - [Optical Character Recognition](#optical-character-recognition) _11 projects_ -- [Data Containers & Structures](#data-containers--structures) _29 projects_ +- [Data Containers & Structures](#data-containers--structures) _31 projects_ - [Data Loading & Extraction](#data-loading--extraction) _1 projects_ - [Web Scraping & Crawling](#web-scraping--crawling) _1 projects_ -- [Data Pipelines & Streaming](#data-pipelines--streaming) _42 projects_ -- [Distributed Machine Learning](#distributed-machine-learning) _29 projects_ +- [Data Pipelines & Streaming](#data-pipelines--streaming) _43 projects_ +- [Distributed Machine Learning](#distributed-machine-learning) _32 projects_ - [Hyperparameter Optimization & AutoML](#hyperparameter-optimization--automl) _47 projects_ -- [Reinforcement Learning](#reinforcement-learning) _21 projects_ +- [Reinforcement Learning](#reinforcement-learning) _23 projects_ - [Recommender Systems](#recommender-systems) _15 projects_ - [Privacy Machine Learning](#privacy-machine-learning) _6 projects_ -- [Workflow & Experiment Tracking](#workflow--experiment-tracking) _36 projects_ -- [Model Serialization & Deployment](#model-serialization--deployment) _14 projects_ +- [Workflow & Experiment Tracking](#workflow--experiment-tracking) _38 projects_ +- [Model Serialization & Deployment](#model-serialization--deployment) _15 projects_ - [Model Interpretability](#model-interpretability) _50 projects_ - [Vector Similarity Search (ANN)](#vector-similarity-search-ann) _12 projects_ -- [Probabilistics & Statistics](#probabilistics--statistics) _23 projects_ +- [Probabilistics & Statistics](#probabilistics--statistics) _22 projects_ - [Adversarial Robustness](#adversarial-robustness) _9 projects_ -- [GPU Utilities](#gpu-utilities) _18 projects_ +- [GPU Utilities](#gpu-utilities) _19 projects_ - [Tensorflow Utilities](#tensorflow-utilities) _15 projects_ +- [Jax Utilities](#jax-utilities) _2 projects_ - [Sklearn Utilities](#sklearn-utilities) _17 projects_ -- [Pytorch Utilities](#pytorch-utilities) _31 projects_ +- [Pytorch Utilities](#pytorch-utilities) _32 projects_ - [Database Clients](#database-clients) _1 projects_ -- [Others](#others) _57 projects_ +- [Others](#others) _60 projects_ ## Explanation - πŸ₯‡πŸ₯ˆπŸ₯‰  Combined project-quality score @@ -88,6 +89,7 @@ This curated list contains 890 awesome open-source projects with a total of 3.2M -   Jupyter related project -   PaddlePaddle related project -   Pandas related project +-   Jax related project
@@ -99,238 +101,242 @@ _General-purpose machine learning and deep learning frameworks._
Tensorflow (πŸ₯‡55 Β· ⭐ 160K) - An Open Source Machine Learning Framework for Everyone. Apache-2 -- [GitHub](https://github.com/tensorflow/tensorflow) (πŸ‘¨β€πŸ’» 3.9K Β· πŸ”€ 86K Β· πŸ“¦ 180K Β· πŸ“‹ 34K - 7% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/tensorflow/tensorflow) (πŸ‘¨β€πŸ’» 3.9K Β· πŸ”€ 86K Β· πŸ“¦ 180K Β· πŸ“‹ 34K - 7% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/tensorflow/tensorflow ``` -- [PyPi](https://pypi.org/project/tensorflow) (πŸ“₯ 13M / month Β· πŸ“¦ 14K Β· ⏱️ 22.12.2021): +- [PyPi](https://pypi.org/project/tensorflow) (πŸ“₯ 17M / month Β· πŸ“¦ 14K Β· ⏱️ 02.02.2022): ``` pip install tensorflow ``` -- [Conda](https://anaconda.org/conda-forge/tensorflow) (πŸ“₯ 3M Β· ⏱️ 08.12.2021): +- [Conda](https://anaconda.org/conda-forge/tensorflow) (πŸ“₯ 3M Β· ⏱️ 06.02.2022): ``` conda install -c conda-forge tensorflow ``` -- [Docker Hub](https://hub.docker.com/r/tensorflow/tensorflow) (πŸ“₯ 64M Β· ⭐ 2K Β· ⏱️ 13.01.2022): +- [Docker Hub](https://hub.docker.com/r/tensorflow/tensorflow) (πŸ“₯ 64M Β· ⭐ 2K Β· ⏱️ 10.02.2022): ``` docker pull tensorflow/tensorflow ```
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PyTorch (πŸ₯‡49 Β· ⭐ 53K) - Tensors and Dynamic neural networks in Python with strong GPU.. BSD-3 +
scikit-learn (πŸ₯‡50 Β· ⭐ 49K) - scikit-learn: machine learning in Python. BSD-3 -- [GitHub](https://github.com/pytorch/pytorch) (πŸ‘¨β€πŸ’» 3.1K Β· πŸ”€ 15K Β· πŸ“₯ 1.3K Β· πŸ“‹ 28K - 40% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/scikit-learn/scikit-learn) (πŸ‘¨β€πŸ’» 2.5K Β· πŸ”€ 22K Β· πŸ“₯ 770 Β· πŸ“¦ 310K Β· πŸ“‹ 10K - 24% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/pytorch/pytorch + git clone https://github.com/scikit-learn/scikit-learn ``` -- [PyPi](https://pypi.org/project/torch) (πŸ“₯ 5.7M / month Β· πŸ“¦ 6.6K Β· ⏱️ 15.12.2021): +- [PyPi](https://pypi.org/project/scikit-learn) (πŸ“₯ 27M / month Β· πŸ“¦ 24K Β· ⏱️ 25.12.2021): ``` - pip install torch + pip install scikit-learn ``` -- [Conda](https://anaconda.org/pytorch/pytorch) (πŸ“₯ 15M Β· ⏱️ 15.12.2021): +- [Conda](https://anaconda.org/conda-forge/scikit-learn) (πŸ“₯ 11M Β· ⏱️ 26.12.2021): ``` - conda install -c pytorch pytorch + conda install -c conda-forge scikit-learn ```
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scikit-learn (πŸ₯‡49 Β· ⭐ 49K) - scikit-learn: machine learning in Python. BSD-3 +
PyTorch (πŸ₯‡49 Β· ⭐ 54K) - Tensors and Dynamic neural networks in Python with strong GPU.. BSD-3 -- [GitHub](https://github.com/scikit-learn/scikit-learn) (πŸ‘¨β€πŸ’» 2.4K Β· πŸ”€ 22K Β· πŸ“₯ 760 Β· πŸ“¦ 300K Β· πŸ“‹ 9.9K - 25% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/pytorch/pytorch) (πŸ‘¨β€πŸ’» 3.1K Β· πŸ”€ 15K Β· πŸ“₯ 1.7K Β· πŸ“‹ 28K - 40% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/scikit-learn/scikit-learn + git clone https://github.com/pytorch/pytorch ``` -- [PyPi](https://pypi.org/project/scikit-learn) (πŸ“₯ 23M / month Β· πŸ“¦ 24K Β· ⏱️ 25.12.2021): +- [PyPi](https://pypi.org/project/torch) (πŸ“₯ 6M / month Β· πŸ“¦ 6.8K Β· ⏱️ 27.01.2022): ``` - pip install scikit-learn + pip install torch ``` -- [Conda](https://anaconda.org/conda-forge/scikit-learn) (πŸ“₯ 11M Β· ⏱️ 26.12.2021): +- [Conda](https://anaconda.org/pytorch/pytorch) (πŸ“₯ 15M Β· ⏱️ 27.01.2022): ``` - conda install -c conda-forge scikit-learn + conda install -c pytorch pytorch ```
Keras (πŸ₯‡44 Β· ⭐ 54K) - Deep Learning for humans. Apache-2 -- [GitHub](https://github.com/keras-team/keras) (πŸ‘¨β€πŸ’» 1K Β· πŸ”€ 19K Β· πŸ“‹ 11K - 2% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/keras-team/keras) (πŸ‘¨β€πŸ’» 1K Β· πŸ”€ 19K Β· πŸ“‹ 11K - 2% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/keras-team/keras ``` -- [PyPi](https://pypi.org/project/keras) (πŸ“₯ 6.9M / month Β· πŸ“¦ 210 Β· ⏱️ 21.12.2021): +- [PyPi](https://pypi.org/project/keras) (πŸ“₯ 8.1M / month Β· πŸ“¦ 220 Β· ⏱️ 31.01.2022): ``` pip install keras ``` -- [Conda](https://anaconda.org/conda-forge/keras) (πŸ“₯ 2M Β· ⏱️ 25.11.2021): +- [Conda](https://anaconda.org/conda-forge/keras) (πŸ“₯ 2M Β· ⏱️ 04.02.2022): ``` conda install -c conda-forge keras ```
XGBoost (πŸ₯‡44 Β· ⭐ 22K) - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or.. Apache-2 -- [GitHub](https://github.com/dmlc/xgboost) (πŸ‘¨β€πŸ’» 540 Β· πŸ”€ 8.2K Β· πŸ“₯ 3.6K Β· πŸ“¦ 26K Β· πŸ“‹ 4.3K - 7% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/dmlc/xgboost) (πŸ‘¨β€πŸ’» 550 Β· πŸ”€ 8.3K Β· πŸ“₯ 3.7K Β· πŸ“¦ 27K Β· πŸ“‹ 4.3K - 6% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/dmlc/xgboost ``` -- [PyPi](https://pypi.org/project/xgboost) (πŸ“₯ 8M / month Β· πŸ“¦ 1.3K Β· ⏱️ 24.11.2021): +- [PyPi](https://pypi.org/project/xgboost) (πŸ“₯ 8.5M / month Β· πŸ“¦ 1.3K Β· ⏱️ 17.01.2022): ``` pip install xgboost ``` -- [Conda](https://anaconda.org/conda-forge/xgboost) (πŸ“₯ 2.2M Β· ⏱️ 20.11.2021): +- [Conda](https://anaconda.org/conda-forge/xgboost) (πŸ“₯ 2.3M Β· ⏱️ 26.01.2022): ``` conda install -c conda-forge xgboost ```
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StatsModels (πŸ₯‡44 Β· ⭐ 7K) - Statsmodels: statistical modeling and econometrics in Python. BSD-3 +
StatsModels (πŸ₯‡44 Β· ⭐ 7.1K) - Statsmodels: statistical modeling and econometrics in Python. BSD-3 -- [GitHub](https://github.com/statsmodels/statsmodels) (πŸ‘¨β€πŸ’» 350 Β· πŸ”€ 2.4K Β· πŸ“₯ 26 Β· πŸ“¦ 56K Β· πŸ“‹ 4.7K - 47% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/statsmodels/statsmodels) (πŸ‘¨β€πŸ’» 360 Β· πŸ”€ 2.4K Β· πŸ“₯ 26 Β· πŸ“¦ 57K Β· πŸ“‹ 4.8K - 47% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/statsmodels/statsmodels ``` -- [PyPi](https://pypi.org/project/statsmodels) (πŸ“₯ 6.8M / month Β· πŸ“¦ 4.4K Β· ⏱️ 15.12.2021): +- [PyPi](https://pypi.org/project/statsmodels) (πŸ“₯ 7.5M / month Β· πŸ“¦ 4.5K Β· ⏱️ 08.02.2022): ``` pip install statsmodels ``` -- [Conda](https://anaconda.org/conda-forge/statsmodels) (πŸ“₯ 5.5M Β· ⏱️ 13.11.2021): +- [Conda](https://anaconda.org/conda-forge/statsmodels) (πŸ“₯ 5.6M Β· ⏱️ 13.11.2021): ``` conda install -c conda-forge statsmodels ```
PySpark (πŸ₯ˆ42 Β· ⭐ 32K) - Apache Spark Python API. Apache-2 -- [GitHub](https://github.com/apache/spark) (πŸ‘¨β€πŸ’» 2.6K Β· πŸ”€ 25K Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/apache/spark) (πŸ‘¨β€πŸ’» 2.6K Β· πŸ”€ 25K Β· ⏱️ 10.02.2022): ``` git clone https://github.com/apache/spark ``` -- [PyPi](https://pypi.org/project/pyspark) (πŸ“₯ 15M / month Β· πŸ“¦ 750 Β· ⏱️ 18.10.2021): +- [PyPi](https://pypi.org/project/pyspark) (πŸ“₯ 17M / month Β· πŸ“¦ 760 Β· ⏱️ 26.01.2022): ``` pip install pyspark ``` -- [Conda](https://anaconda.org/conda-forge/pyspark) (πŸ“₯ 1.4M Β· ⏱️ 18.10.2021): +- [Conda](https://anaconda.org/conda-forge/pyspark) (πŸ“₯ 1.5M Β· ⏱️ 26.01.2022): ``` conda install -c conda-forge pyspark ```
pytorch-lightning (πŸ₯ˆ42 Β· ⭐ 17K) - The lightweight PyTorch wrapper for high-performance.. Apache-2 -- [GitHub](https://github.com/PyTorchLightning/pytorch-lightning) (πŸ‘¨β€πŸ’» 600 Β· πŸ”€ 2.1K Β· πŸ“₯ 5K Β· πŸ“¦ 6.4K Β· πŸ“‹ 4.5K - 10% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/PyTorchLightning/pytorch-lightning) (πŸ‘¨β€πŸ’» 620 Β· πŸ”€ 2.2K Β· πŸ“₯ 5.4K Β· πŸ“¦ 6.8K Β· πŸ“‹ 4.6K - 10% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/PyTorchLightning/pytorch-lightning ``` -- [PyPi](https://pypi.org/project/pytorch-lightning) (πŸ“₯ 850K / month Β· πŸ“¦ 290 Β· ⏱️ 05.01.2022): +- [PyPi](https://pypi.org/project/pytorch-lightning) (πŸ“₯ 1.1M / month Β· πŸ“¦ 310 Β· ⏱️ 09.02.2022): ``` pip install pytorch-lightning ``` -- [Conda](https://anaconda.org/conda-forge/pytorch-lightning) (πŸ“₯ 390K Β· ⏱️ 05.01.2022): +- [Conda](https://anaconda.org/conda-forge/pytorch-lightning) (πŸ“₯ 390K Β· ⏱️ 21.01.2022): ``` conda install -c conda-forge pytorch-lightning ```
LightGBM (πŸ₯ˆ42 Β· ⭐ 13K) - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT,.. MIT -- [GitHub](https://github.com/microsoft/LightGBM) (πŸ‘¨β€πŸ’» 250 Β· πŸ”€ 3.5K Β· πŸ“₯ 130K Β· πŸ“¦ 11K Β· πŸ“‹ 2.5K - 6% open Β· ⏱️ 09.01.2022): +- [GitHub](https://github.com/microsoft/LightGBM) (πŸ‘¨β€πŸ’» 250 Β· πŸ”€ 3.5K Β· πŸ“₯ 140K Β· πŸ“¦ 11K Β· πŸ“‹ 2.5K - 6% open Β· ⏱️ 01.02.2022): ``` git clone https://github.com/microsoft/LightGBM ``` -- [PyPi](https://pypi.org/project/lightgbm) (πŸ“₯ 10M / month Β· πŸ“¦ 570 Β· ⏱️ 07.01.2022): +- [PyPi](https://pypi.org/project/lightgbm) (πŸ“₯ 9.7M / month Β· πŸ“¦ 580 Β· ⏱️ 07.01.2022): ``` pip install lightgbm ``` -- [Conda](https://anaconda.org/conda-forge/lightgbm) (πŸ“₯ 850K Β· ⏱️ 08.01.2022): +- [Conda](https://anaconda.org/conda-forge/lightgbm) (πŸ“₯ 890K Β· ⏱️ 08.01.2022): ``` conda install -c conda-forge lightgbm ```
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PaddlePaddle (πŸ₯ˆ41 Β· ⭐ 17K) - PArallel Distributed Deep LEarning: Machine Learning.. Apache-2 +
PaddlePaddle (πŸ₯ˆ41 Β· ⭐ 18K) - PArallel Distributed Deep LEarning: Machine Learning.. Apache-2 -- [GitHub](https://github.com/PaddlePaddle/Paddle) (πŸ‘¨β€πŸ’» 690 Β· πŸ”€ 4.2K Β· πŸ“₯ 15K Β· πŸ“¦ 88 Β· πŸ“‹ 15K - 18% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/PaddlePaddle/Paddle) (πŸ‘¨β€πŸ’» 700 Β· πŸ”€ 4.3K Β· πŸ“₯ 15K Β· πŸ“¦ 91 Β· πŸ“‹ 15K - 18% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/PaddlePaddle/Paddle ``` -- [PyPi](https://pypi.org/project/paddlepaddle) (πŸ“₯ 97K / month Β· πŸ“¦ 41 Β· ⏱️ 02.12.2021): +- [PyPi](https://pypi.org/project/paddlepaddle) (πŸ“₯ 100K / month Β· πŸ“¦ 44 Β· ⏱️ 20.01.2022): ``` pip install paddlepaddle ```
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jax (πŸ₯ˆ41 Β· ⭐ 16K) - Composable transformations of Python+NumPy programs: differentiate,.. Apache-2 +
Catboost (πŸ₯ˆ41 Β· ⭐ 6.3K) - A fast, scalable, high performance Gradient Boosting on Decision.. Apache-2 -- [GitHub](https://github.com/google/jax) (πŸ‘¨β€πŸ’» 350 Β· πŸ”€ 1.4K Β· πŸ“¦ 3.2K Β· πŸ“‹ 2.9K - 31% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/catboost/catboost) (πŸ‘¨β€πŸ’» 950 Β· πŸ”€ 950 Β· πŸ“₯ 74K Β· πŸ“‹ 1.7K - 20% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/google/jax + git clone https://github.com/catboost/catboost ``` -- [PyPi](https://pypi.org/project/jax) (πŸ“₯ 300K / month Β· πŸ“¦ 240 Β· ⏱️ 08.12.2021): +- [PyPi](https://pypi.org/project/catboost) (πŸ“₯ 3.3M / month Β· πŸ“¦ 210 Β· ⏱️ 14.01.2022): ``` - pip install jax + pip install catboost ``` -- [Conda](https://anaconda.org/conda-forge/jaxlib) (πŸ“₯ 260K Β· ⏱️ 10.12.2021): +- [Conda](https://anaconda.org/conda-forge/catboost) (πŸ“₯ 920K Β· ⏱️ 04.02.2022): ``` - conda install -c conda-forge jaxlib + conda install -c conda-forge catboost ```
MXNet (πŸ₯ˆ40 Β· ⭐ 20K) - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning.. Apache-2 -- [GitHub](https://github.com/apache/incubator-mxnet) (πŸ‘¨β€πŸ’» 970 Β· πŸ”€ 6.9K Β· πŸ“₯ 24K Β· πŸ“‹ 9.6K - 20% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/apache/incubator-mxnet) (πŸ‘¨β€πŸ’» 970 Β· πŸ”€ 6.9K Β· πŸ“₯ 25K Β· πŸ“‹ 9.7K - 20% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/apache/incubator-mxnet ``` -- [PyPi](https://pypi.org/project/mxnet) (πŸ“₯ 250K / month Β· πŸ“¦ 280 Β· ⏱️ 18.12.2021): +- [PyPi](https://pypi.org/project/mxnet) (πŸ“₯ 290K / month Β· πŸ“¦ 280 Β· ⏱️ 18.12.2021): ``` pip install mxnet ``` -- [Conda](https://anaconda.org/anaconda/mxnet) (πŸ“₯ 6.9K Β· πŸ“¦ 5 Β· ⏱️ 29.02.2020): +- [Conda](https://anaconda.org/anaconda/mxnet) (πŸ“₯ 7K Β· πŸ“¦ 5 Β· ⏱️ 29.02.2020): ``` conda install -c anaconda mxnet ```
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Catboost (πŸ₯ˆ40 Β· ⭐ 6.3K) - A fast, scalable, high performance Gradient Boosting on Decision.. Apache-2 +
jax (πŸ₯ˆ40 Β· ⭐ 16K) - Composable transformations of Python+NumPy programs: differentiate,.. Apache-2 -- [GitHub](https://github.com/catboost/catboost) (πŸ‘¨β€πŸ’» 940 Β· πŸ”€ 950 Β· πŸ“₯ 71K Β· πŸ“‹ 1.7K - 20% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/google/jax) (πŸ‘¨β€πŸ’» 360 Β· πŸ”€ 1.5K Β· πŸ“¦ 3.4K Β· πŸ“‹ 3.1K - 31% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/catboost/catboost + git clone https://github.com/google/jax ``` -- [PyPi](https://pypi.org/project/catboost) (πŸ“₯ 3.1M / month Β· πŸ“¦ 190 Β· ⏱️ 04.11.2021): +- [PyPi](https://pypi.org/project/jax) (πŸ“₯ 290K / month Β· πŸ“¦ 260 Β· ⏱️ 18.01.2022): ``` - pip install catboost + pip install jax ``` -- [Conda](https://anaconda.org/conda-forge/catboost) (πŸ“₯ 900K Β· ⏱️ 09.11.2021): +- [Conda](https://anaconda.org/conda-forge/jaxlib) (πŸ“₯ 270K Β· ⏱️ 10.12.2021): ``` - conda install -c conda-forge catboost + conda install -c conda-forge jaxlib ```
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Fastai (πŸ₯ˆ37 Β· ⭐ 22K) - The fastai deep learning library. Apache-2 +
Jina (πŸ₯ˆ38 Β· ⭐ 13K) - Cloud-native neural search framework for kind of data. Apache-2 -- [GitHub](https://github.com/fastai/fastai) (πŸ‘¨β€πŸ’» 600 Β· πŸ”€ 7.1K Β· πŸ“‹ 1.5K - 6% open Β· ⏱️ 29.11.2021): +- [GitHub](https://github.com/jina-ai/jina) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 1.8K Β· πŸ“¦ 220 Β· πŸ“‹ 1.3K - 5% open Β· ⏱️ 09.02.2022): ``` - git clone https://github.com/fastai/fastai + git clone https://github.com/jina-ai/jina ``` -- [PyPi](https://pypi.org/project/fastai) (πŸ“₯ 190K / month Β· πŸ“¦ 290 Β· ⏱️ 23.10.2021): +- [PyPi](https://pypi.org/project/jina) (πŸ“₯ 36K / month Β· ⏱️ 07.02.2022): ``` - pip install fastai + pip install jina + ``` +- [Conda](https://anaconda.org/conda-forge/jina-core) (πŸ“₯ 2.2K Β· ⏱️ 01.11.2021): + ``` + conda install -c conda-forge jina-core + ``` +- [Docker Hub](https://hub.docker.com/r/jinaai/jina) (πŸ“₯ 1M Β· ⭐ 6 Β· ⏱️ 07.02.2022): + ``` + docker pull jinaai/jina ```
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Jina (πŸ₯ˆ37 Β· ⭐ 13K) - Cloud-native neural search framework for kind of data. Apache-2 +
Fastai (πŸ₯ˆ37 Β· ⭐ 22K) - The fastai deep learning library. Apache-2 -- [GitHub](https://github.com/jina-ai/jina) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 1.8K Β· πŸ“¦ 210 Β· πŸ“‹ 1.3K - 6% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/fastai/fastai) (πŸ‘¨β€πŸ’» 600 Β· πŸ”€ 7.1K Β· πŸ“‹ 1.5K - 6% open Β· ⏱️ 09.02.2022): ``` - git clone https://github.com/jina-ai/jina - ``` -- [PyPi](https://pypi.org/project/jina) (πŸ“₯ 13K / month Β· ⏱️ 11.01.2022): - ``` - pip install jina + git clone https://github.com/fastai/fastai ``` -- [Docker Hub](https://hub.docker.com/r/jinaai/jina) (πŸ“₯ 1M Β· ⭐ 6 Β· ⏱️ 11.01.2022): +- [PyPi](https://pypi.org/project/fastai) (πŸ“₯ 230K / month Β· πŸ“¦ 290 Β· ⏱️ 23.10.2021): ``` - docker pull jinaai/jina + pip install fastai ```
Theano (πŸ₯ˆ37 Β· ⭐ 9.5K) - Theano was a Python library that allows you to define, optimize, and.. BSD-3 @@ -340,7 +346,7 @@ _General-purpose machine learning and deep learning frameworks._ ``` git clone https://github.com/Theano/Theano ``` -- [PyPi](https://pypi.org/project/theano) (πŸ“₯ 220K / month Β· πŸ“¦ 2.8K Β· ⏱️ 27.07.2020): +- [PyPi](https://pypi.org/project/theano) (πŸ“₯ 270K / month Β· πŸ“¦ 2.8K Β· ⏱️ 27.07.2020): ``` pip install theano ``` @@ -349,6 +355,18 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge theano ```
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PyFlink (πŸ₯ˆ36 Β· ⭐ 18K) - Apache Flink Python API. Apache-2 + +- [GitHub](https://github.com/apache/flink) (πŸ‘¨β€πŸ’» 1.5K Β· πŸ”€ 10K Β· ⏱️ 10.02.2022): + + ``` + git clone https://github.com/apache/flink + ``` +- [PyPi](https://pypi.org/project/apache-flink) (πŸ“₯ 9K / month Β· πŸ“¦ 9 Β· ⏱️ 17.01.2022): + ``` + pip install apache-flink + ``` +
Chainer (πŸ₯ˆ36 Β· ⭐ 5.7K) - A flexible framework of neural networks for deep learning. MIT - [GitHub](https://github.com/chainer/chainer) (πŸ‘¨β€πŸ’» 320 Β· πŸ”€ 1.4K Β· πŸ“¦ 2.5K Β· πŸ“‹ 2K - 0% open Β· ⏱️ 05.01.2022): @@ -356,19 +374,23 @@ _General-purpose machine learning and deep learning frameworks._ ``` git clone https://github.com/chainer/chainer ``` -- [PyPi](https://pypi.org/project/chainer) (πŸ“₯ 18K / month Β· πŸ“¦ 400 Β· ⏱️ 05.01.2022): +- [PyPi](https://pypi.org/project/chainer) (πŸ“₯ 22K / month Β· πŸ“¦ 400 Β· ⏱️ 05.01.2022): ``` pip install chainer ``` +- [Conda](https://anaconda.org/conda-forge/chainer) (πŸ“₯ 6.7K Β· ⏱️ 21.01.2022): + ``` + conda install -c conda-forge chainer + ```
Thinc (πŸ₯ˆ36 Β· ⭐ 2.4K) - A refreshing functional take on deep learning, compatible with your favorite.. MIT -- [GitHub](https://github.com/explosion/thinc) (πŸ‘¨β€πŸ’» 43 Β· πŸ”€ 230 Β· πŸ“¦ 18K Β· πŸ“‹ 120 - 17% open Β· ⏱️ 21.12.2021): +- [GitHub](https://github.com/explosion/thinc) (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 230 Β· πŸ“¦ 19K Β· πŸ“‹ 120 - 17% open Β· ⏱️ 04.02.2022): ``` git clone https://github.com/explosion/thinc ``` -- [PyPi](https://pypi.org/project/thinc) (πŸ“₯ 3.7M / month Β· πŸ“¦ 610 Β· ⏱️ 17.12.2021): +- [PyPi](https://pypi.org/project/thinc) (πŸ“₯ 3.6M / month Β· πŸ“¦ 610 Β· ⏱️ 17.12.2021): ``` pip install thinc ``` @@ -377,204 +399,208 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge thinc ```
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PyFlink (πŸ₯ˆ34 Β· ⭐ 18K) - Apache Flink Python API. Apache-2 - -- [GitHub](https://github.com/apache/flink) (πŸ‘¨β€πŸ’» 1.4K Β· πŸ”€ 9.9K Β· ⏱️ 13.01.2022): - - ``` - git clone https://github.com/apache/flink - ``` -- [PyPi](https://pypi.org/project/apache-flink) (πŸ“₯ 7.4K / month Β· πŸ“¦ 9 Β· ⏱️ 16.12.2021): - ``` - pip install apache-flink - ``` -
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Vowpal Wabbit (πŸ₯ˆ33 Β· ⭐ 7.8K) - Vowpal Wabbit is a machine learning system which pushes the.. BSD-3 +
Vowpal Wabbit (πŸ₯ˆ34 Β· ⭐ 7.9K) - Vowpal Wabbit is a machine learning system which pushes the.. BSD-3 -- [GitHub](https://github.com/VowpalWabbit/vowpal_wabbit) (πŸ‘¨β€πŸ’» 310 Β· πŸ”€ 1.8K Β· πŸ“‹ 1.2K - 15% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/VowpalWabbit/vowpal_wabbit) (πŸ‘¨β€πŸ’» 310 Β· πŸ”€ 1.8K Β· πŸ“‹ 1.2K - 11% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/VowpalWabbit/vowpal_wabbit ``` -- [PyPi](https://pypi.org/project/vowpalwabbit) (πŸ“₯ 48K / month Β· πŸ“¦ 25 Β· ⏱️ 14.07.2021): +- [PyPi](https://pypi.org/project/vowpalwabbit) (πŸ“₯ 53K / month Β· πŸ“¦ 29 Β· ⏱️ 01.02.2022): ``` pip install vowpalwabbit ``` +- [Conda](https://anaconda.org/conda-forge/vowpalwabbit) (πŸ“₯ 55K Β· ⏱️ 02.02.2022): + ``` + conda install -c conda-forge vowpalwabbit + ```
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Ignite (πŸ₯ˆ33 Β· ⭐ 3.8K) - High-level library to help with training and evaluating neural.. BSD-3 +
Ignite (πŸ₯ˆ33 Β· ⭐ 3.9K) - High-level library to help with training and evaluating neural.. BSD-3 -- [GitHub](https://github.com/pytorch/ignite) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 510 Β· πŸ“‹ 1K - 13% open Β· ⏱️ 10.01.2022): +- [GitHub](https://github.com/pytorch/ignite) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 520 Β· πŸ“‹ 1K - 13% open Β· ⏱️ 08.02.2022): ``` git clone https://github.com/pytorch/ignite ``` -- [PyPi](https://pypi.org/project/pytorch-ignite) (πŸ“₯ 69K / month Β· πŸ“¦ 76 Β· ⏱️ 13.01.2022): +- [PyPi](https://pypi.org/project/pytorch-ignite) (πŸ“₯ 120K / month Β· πŸ“¦ 76 Β· ⏱️ 10.02.2022): ``` pip install pytorch-ignite ``` -- [Conda](https://anaconda.org/pytorch/ignite) (πŸ“₯ 77K Β· ⏱️ 19.10.2021): +- [Conda](https://anaconda.org/pytorch/ignite) (πŸ“₯ 79K Β· ⏱️ 17.01.2022): ``` conda install -c pytorch ignite ```
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Flax (πŸ₯ˆ33 Β· ⭐ 2.5K) - Flax is a neural network library for JAX that is designed for.. Apache-2 jax +
Flax (πŸ₯ˆ33 Β· ⭐ 2.6K) - Flax is a neural network library for JAX that is designed for.. Apache-2 -- [GitHub](https://github.com/google/flax) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 270 Β· πŸ“₯ 31 Β· πŸ“¦ 610 Β· πŸ“‹ 450 - 36% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/google/flax) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 290 Β· πŸ“₯ 31 Β· πŸ“¦ 660 Β· πŸ“‹ 490 - 36% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/google/flax ``` -- [PyPi](https://pypi.org/project/flax) (πŸ“₯ 160K / month Β· πŸ“¦ 50 Β· ⏱️ 27.10.2021): +- [PyPi](https://pypi.org/project/flax) (πŸ“₯ 88K / month Β· πŸ“¦ 57 Β· ⏱️ 27.01.2022): ``` pip install flax ``` +- [Conda](https://anaconda.org/conda-forge/flax) (πŸ“₯ 2.2K Β· ⏱️ 27.01.2022): + ``` + conda install -c conda-forge flax + ```
tensorflow-upstream (πŸ₯ˆ33 Β· ⭐ 580) - TensorFlow ROCm port. Apache-2 -- [GitHub](https://github.com/ROCmSoftwarePlatform/tensorflow-upstream) (πŸ‘¨β€πŸ’» 3.9K Β· πŸ”€ 66 Β· πŸ“₯ 17 Β· πŸ“‹ 320 - 17% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/ROCmSoftwarePlatform/tensorflow-upstream) (πŸ‘¨β€πŸ’» 3.9K Β· πŸ”€ 67 Β· πŸ“₯ 17 Β· πŸ“‹ 320 - 17% open Β· ⏱️ 08.02.2022): ``` git clone https://github.com/ROCmSoftwarePlatform/tensorflow-upstream ``` -- [PyPi](https://pypi.org/project/tensorflow-rocm) (πŸ“₯ 1.6K / month Β· πŸ“¦ 5 Β· ⏱️ 17.12.2021): +- [PyPi](https://pypi.org/project/tensorflow-rocm) (πŸ“₯ 41K / month Β· πŸ“¦ 5 Β· ⏱️ 17.12.2021): ``` pip install tensorflow-rocm ```
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Turi Create (πŸ₯‰32 Β· ⭐ 11K) - Turi Create simplifies the development of custom machine learning.. BSD-3 +
Ludwig (πŸ₯‰32 Β· ⭐ 8.1K Β· πŸ“ˆ) - Data-centric declarative deep learning framework. Apache-2 -- [GitHub](https://github.com/apple/turicreate) (πŸ‘¨β€πŸ’» 83 Β· πŸ”€ 1.1K Β· πŸ“₯ 5K Β· πŸ“¦ 280 Β· πŸ“‹ 1.8K - 27% open Β· ⏱️ 29.11.2021): +- [GitHub](https://github.com/ludwig-ai/ludwig) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 960 Β· πŸ“¦ 99 Β· πŸ“‹ 680 - 26% open Β· ⏱️ 08.02.2022): ``` - git clone https://github.com/apple/turicreate + git clone https://github.com/ludwig-ai/ludwig ``` -- [PyPi](https://pypi.org/project/turicreate) (πŸ“₯ 22K / month Β· πŸ“¦ 19 Β· ⏱️ 30.09.2020): +- [PyPi](https://pypi.org/project/ludwig) (πŸ“₯ 2.9K / month Β· πŸ“¦ 8 Β· ⏱️ 01.02.2022): ``` - pip install turicreate + pip install ludwig ```
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tensorpack (πŸ₯‰32 Β· ⭐ 6.1K) - A Neural Net Training Interface on TensorFlow, with focus.. Apache-2 +
tensorpack (πŸ₯‰32 Β· ⭐ 6.2K) - A Neural Net Training Interface on TensorFlow, with focus.. Apache-2 -- [GitHub](https://github.com/tensorpack/tensorpack) (πŸ‘¨β€πŸ’» 58 Β· πŸ”€ 1.8K Β· πŸ“₯ 130 Β· πŸ“¦ 920 Β· πŸ“‹ 1.3K - 0% open Β· ⏱️ 27.11.2021): +- [GitHub](https://github.com/tensorpack/tensorpack) (πŸ‘¨β€πŸ’» 58 Β· πŸ”€ 1.8K Β· πŸ“₯ 130 Β· πŸ“¦ 930 Β· πŸ“‹ 1.3K - 0% open Β· ⏱️ 27.11.2021): ``` git clone https://github.com/tensorpack/tensorpack ``` -- [PyPi](https://pypi.org/project/tensorpack) (πŸ“₯ 21K / month Β· πŸ“¦ 46 Β· ⏱️ 22.01.2021): +- [PyPi](https://pypi.org/project/tensorpack) (πŸ“₯ 22K / month Β· πŸ“¦ 46 Β· ⏱️ 22.01.2021): ``` pip install tensorpack ``` +- [Conda](https://anaconda.org/conda-forge/tensorpack) (πŸ“₯ 200 Β· ⏱️ 06.02.2022): + ``` + conda install -c conda-forge tensorpack + ```
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mlpack (πŸ₯‰32 Β· ⭐ 3.9K) - mlpack: a scalable C++ machine learning library --. BSD-3 +
Turi Create (πŸ₯‰31 Β· ⭐ 11K) - Turi Create simplifies the development of custom machine learning.. BSD-3 -- [GitHub](https://github.com/mlpack/mlpack) (πŸ‘¨β€πŸ’» 280 Β· πŸ”€ 1.4K Β· πŸ“‹ 1.4K - 7% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/apple/turicreate) (πŸ‘¨β€πŸ’» 85 Β· πŸ”€ 1.1K Β· πŸ“₯ 5K Β· πŸ“¦ 290 Β· πŸ“‹ 1.8K - 27% open Β· ⏱️ 29.11.2021): ``` - git clone https://github.com/mlpack/mlpack - ``` -- [PyPi](https://pypi.org/project/mlpack) (πŸ“₯ 210 / month Β· πŸ“¦ 1 Β· ⏱️ 28.10.2020): - ``` - pip install mlpack + git clone https://github.com/apple/turicreate ``` -- [Conda](https://anaconda.org/conda-forge/mlpack) (πŸ“₯ 97K Β· ⏱️ 09.11.2021): +- [PyPi](https://pypi.org/project/turicreate) (πŸ“₯ 28K / month Β· πŸ“¦ 19 Β· ⏱️ 30.09.2020): ``` - conda install -c conda-forge mlpack + pip install turicreate ```
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Sonnet (πŸ₯‰31 Β· ⭐ 9.2K) - TensorFlow-based neural network library. Apache-2 +
einops (πŸ₯‰31 Β· ⭐ 4.4K) - Deep learning operations reinvented (for pytorch, tensorflow, jax and.. MIT -- [GitHub](https://github.com/deepmind/sonnet) (πŸ‘¨β€πŸ’» 53 Β· πŸ”€ 1.3K Β· πŸ“¦ 750 Β· πŸ“‹ 170 - 13% open Β· ⏱️ 15.12.2021): +- [GitHub](https://github.com/arogozhnikov/einops) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 180 Β· πŸ“¦ 1.9K Β· πŸ“‹ 100 - 33% open Β· ⏱️ 03.02.2022): ``` - git clone https://github.com/deepmind/sonnet + git clone https://github.com/arogozhnikov/einops ``` -- [PyPi](https://pypi.org/project/dm-sonnet) (πŸ“₯ 120K / month Β· πŸ“¦ 52 Β· ⏱️ 27.03.2020): +- [PyPi](https://pypi.org/project/einops) (πŸ“₯ 700K / month Β· πŸ“¦ 190 Β· ⏱️ 18.01.2022): ``` - pip install dm-sonnet + pip install einops ``` -- [Conda](https://anaconda.org/conda-forge/sonnet) (πŸ“₯ 13K Β· ⏱️ 14.11.2020): +- [Conda](https://anaconda.org/conda-forge/einops) (πŸ“₯ 10K Β· ⏱️ 18.01.2022): ``` - conda install -c conda-forge sonnet + conda install -c conda-forge einops ```
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dyNET (πŸ₯‰31 Β· ⭐ 3.3K Β· πŸ’€) - DyNet: The Dynamic Neural Network Toolkit. Apache-2 +
mlpack (πŸ₯‰31 Β· ⭐ 3.9K) - mlpack: a scalable C++ machine learning library --. BSD-3 -- [GitHub](https://github.com/clab/dynet) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 700 Β· πŸ“₯ 4.4K Β· πŸ“¦ 200 Β· πŸ“‹ 920 - 28% open Β· ⏱️ 27.01.2021): +- [GitHub](https://github.com/mlpack/mlpack) (πŸ‘¨β€πŸ’» 280 Β· πŸ”€ 1.4K Β· πŸ“‹ 1.5K - 7% open Β· ⏱️ 30.01.2022): ``` - git clone https://github.com/clab/dynet + git clone https://github.com/mlpack/mlpack + ``` +- [PyPi](https://pypi.org/project/mlpack) (πŸ“₯ 250 / month Β· πŸ“¦ 1 Β· ⏱️ 28.10.2020): + ``` + pip install mlpack ``` -- [PyPi](https://pypi.org/project/dyNET) (πŸ“₯ 15K / month Β· πŸ“¦ 28 Β· ⏱️ 21.10.2020): +- [Conda](https://anaconda.org/conda-forge/mlpack) (πŸ“₯ 97K Β· ⏱️ 09.11.2021): ``` - pip install dyNET + conda install -c conda-forge mlpack ```
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einops (πŸ₯‰30 Β· ⭐ 4.1K) - Deep learning operations reinvented (for pytorch, tensorflow, jax and.. MIT +
Sonnet (πŸ₯‰30 Β· ⭐ 9.2K) - TensorFlow-based neural network library. Apache-2 -- [GitHub](https://github.com/arogozhnikov/einops) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 160 Β· πŸ“¦ 1.8K Β· πŸ“‹ 91 - 32% open Β· ⏱️ 10.01.2022): +- [GitHub](https://github.com/deepmind/sonnet) (πŸ‘¨β€πŸ’» 53 Β· πŸ”€ 1.3K Β· πŸ“¦ 760 Β· πŸ“‹ 170 - 13% open Β· ⏱️ 01.02.2022): ``` - git clone https://github.com/arogozhnikov/einops + git clone https://github.com/deepmind/sonnet ``` -- [PyPi](https://pypi.org/project/einops) (πŸ“₯ 580K / month Β· πŸ“¦ 160 Β· ⏱️ 31.08.2021): +- [PyPi](https://pypi.org/project/dm-sonnet) (πŸ“₯ 23K / month Β· πŸ“¦ 52 Β· ⏱️ 27.03.2020): ``` - pip install einops + pip install dm-sonnet ``` -- [Conda](https://anaconda.org/conda-forge/einops) (πŸ“₯ 9.7K Β· ⏱️ 31.08.2021): +- [Conda](https://anaconda.org/conda-forge/sonnet) (πŸ“₯ 13K Β· ⏱️ 14.11.2020): ``` - conda install -c conda-forge einops + conda install -c conda-forge sonnet ```
Neural Network Libraries (πŸ₯‰30 Β· ⭐ 2.5K) - Neural Network Libraries. Apache-2 -- [GitHub](https://github.com/sony/nnabla) (πŸ‘¨β€πŸ’» 64 Β· πŸ”€ 310 Β· πŸ“₯ 530 Β· πŸ“‹ 76 - 42% open Β· ⏱️ 11.01.2022): +- [GitHub](https://github.com/sony/nnabla) (πŸ‘¨β€πŸ’» 64 Β· πŸ”€ 310 Β· πŸ“₯ 530 Β· πŸ“‹ 77 - 41% open Β· ⏱️ 26.01.2022): ``` git clone https://github.com/sony/nnabla ``` -- [PyPi](https://pypi.org/project/nnabla) (πŸ“₯ 3.9K / month Β· πŸ“¦ 51 Β· ⏱️ 23.12.2021): +- [PyPi](https://pypi.org/project/nnabla) (πŸ“₯ 4.6K / month Β· πŸ“¦ 51 Β· ⏱️ 26.01.2022): ``` pip install nnabla ```
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ktrain (πŸ₯‰30 Β· ⭐ 940) - ktrain is a Python library that makes deep learning and AI more.. Apache-2 +
skorch (πŸ₯‰29 Β· ⭐ 4.4K) - A scikit-learn compatible neural network library that wraps.. BSD-3 -- [GitHub](https://github.com/amaiya/ktrain) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 220 Β· πŸ“¦ 250 Β· πŸ“‹ 380 - 1% open Β· ⏱️ 23.11.2021): +- [GitHub](https://github.com/skorch-dev/skorch) (πŸ‘¨β€πŸ’» 48 Β· πŸ”€ 300 Β· πŸ“¦ 430 Β· πŸ“‹ 420 - 12% open Β· ⏱️ 18.01.2022): ``` - git clone https://github.com/amaiya/ktrain + git clone https://github.com/skorch-dev/skorch ``` -- [PyPi](https://pypi.org/project/ktrain) (πŸ“₯ 31K / month Β· πŸ“¦ 2 Β· ⏱️ 05.11.2021): +- [PyPi](https://pypi.org/project/skorch) (πŸ“₯ 20K / month Β· πŸ“¦ 33 Β· ⏱️ 31.10.2021): ``` - pip install ktrain + pip install skorch + ``` +- [Conda](https://anaconda.org/conda-forge/skorch) (πŸ“₯ 500K Β· ⏱️ 30.11.2021): + ``` + conda install -c conda-forge skorch ```
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Ludwig (πŸ₯‰29 Β· ⭐ 8K) - Data-centric declarative deep learning framework. Apache-2 +
Haiku (πŸ₯‰29 Β· ⭐ 1.7K Β· πŸ“ˆ) - JAX-based neural network library. Apache-2 -- [GitHub](https://github.com/ludwig-ai/ludwig) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 950 Β· πŸ“¦ 99 Β· πŸ“‹ 640 - 24% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/deepmind/dm-haiku) (πŸ‘¨β€πŸ’» 57 Β· πŸ”€ 130 Β· πŸ“¦ 320 Β· πŸ“‹ 130 - 25% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/ludwig-ai/ludwig + git clone https://github.com/deepmind/dm-haiku ``` -- [PyPi](https://pypi.org/project/ludwig) (πŸ“₯ 2.9K / month Β· πŸ“¦ 8 Β· ⏱️ 15.06.2021): +- [PyPi](https://pypi.org/project/dm-haiku) (πŸ“₯ 80K / month Β· πŸ“¦ 24 Β· ⏱️ 01.11.2021): ``` - pip install ludwig + pip install dm-haiku + ``` +- [Conda](https://anaconda.org/conda-forge/dm-haiku) (πŸ“₯ 1.9K Β· ⏱️ 03.11.2021): + ``` + conda install -c conda-forge dm-haiku ```
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skorch (πŸ₯‰29 Β· ⭐ 4.3K) - A scikit-learn compatible neural network library that wraps.. BSD-3 +
ktrain (πŸ₯‰29 Β· ⭐ 950) - ktrain is a Python library that makes deep learning and AI more.. Apache-2 -- [GitHub](https://github.com/skorch-dev/skorch) (πŸ‘¨β€πŸ’» 47 Β· πŸ”€ 300 Β· πŸ“¦ 420 Β· πŸ“‹ 420 - 12% open Β· ⏱️ 30.12.2021): +- [GitHub](https://github.com/amaiya/ktrain) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 230 Β· πŸ“¦ 260 Β· πŸ“‹ 390 - 0% open Β· ⏱️ 09.02.2022): ``` - git clone https://github.com/skorch-dev/skorch - ``` -- [PyPi](https://pypi.org/project/skorch) (πŸ“₯ 23K / month Β· πŸ“¦ 33 Β· ⏱️ 31.10.2021): - ``` - pip install skorch + git clone https://github.com/amaiya/ktrain ``` -- [Conda](https://anaconda.org/conda-forge/skorch) (πŸ“₯ 500K Β· ⏱️ 30.11.2021): +- [PyPi](https://pypi.org/project/ktrain) (πŸ“₯ 33K / month Β· πŸ“¦ 2 Β· ⏱️ 09.02.2022): ``` - conda install -c conda-forge skorch + pip install ktrain ```
mace (πŸ₯‰25 Β· ⭐ 4.6K) - MACE is a deep learning inference framework optimized for mobile.. Apache-2 @@ -587,44 +613,36 @@ _General-purpose machine learning and deep learning frameworks._
Neural Tangents (πŸ₯‰25 Β· ⭐ 1.7K) - Fast and Easy Infinite Neural Networks in Python. Apache-2 -- [GitHub](https://github.com/google/neural-tangents) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 190 Β· πŸ“₯ 190 Β· πŸ“¦ 27 Β· πŸ“‹ 100 - 30% open Β· ⏱️ 14.12.2021): +- [GitHub](https://github.com/google/neural-tangents) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 190 Β· πŸ“₯ 190 Β· πŸ“¦ 29 Β· πŸ“‹ 110 - 32% open Β· ⏱️ 08.02.2022): ``` git clone https://github.com/google/neural-tangents ``` -- [PyPi](https://pypi.org/project/neural-tangents) (πŸ“₯ 430 / month Β· πŸ“¦ 1 Β· ⏱️ 17.11.2021): +- [PyPi](https://pypi.org/project/neural-tangents) (πŸ“₯ 490 / month Β· πŸ“¦ 1 Β· ⏱️ 17.11.2021): ``` pip install neural-tangents ```
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Haiku (πŸ₯‰25 Β· ⭐ 1.7K) - JAX-based neural network library. Apache-2 - -- [GitHub](https://github.com/deepmind/dm-haiku) (πŸ‘¨β€πŸ’» 56 Β· πŸ”€ 120 Β· πŸ“¦ 290 Β· πŸ“‹ 130 - 25% open Β· ⏱️ 12.01.2022): - - ``` - git clone https://github.com/deepmind/dm-haiku - ``` -
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fklearn (πŸ₯‰25 Β· ⭐ 1.4K) - fklearn: Functional Machine Learning. Apache-2 +
fklearn (πŸ₯‰24 Β· ⭐ 1.4K) - fklearn: Functional Machine Learning. Apache-2 -- [GitHub](https://github.com/nubank/fklearn) (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 150 Β· πŸ“¦ 11 Β· πŸ“‹ 41 - 48% open Β· ⏱️ 30.12.2021): +- [GitHub](https://github.com/nubank/fklearn) (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 160 Β· πŸ“¦ 11 Β· πŸ“‹ 42 - 50% open Β· ⏱️ 04.02.2022): ``` git clone https://github.com/nubank/fklearn ``` -- [PyPi](https://pypi.org/project/fklearn) (πŸ“₯ 3K / month Β· ⏱️ 30.12.2021): +- [PyPi](https://pypi.org/project/fklearn) (πŸ“₯ 4K / month Β· ⏱️ 30.12.2021): ``` pip install fklearn ```
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Objax (πŸ₯‰22 Β· ⭐ 670 Β· πŸ“ˆ) - Objax is a machine learning framework that provides an Object.. Apache-2 jax +
Objax (πŸ₯‰23 Β· ⭐ 680) - Objax is a machine learning framework that provides an Object.. Apache-2 -- [GitHub](https://github.com/google/objax) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 59 Β· πŸ“¦ 17 Β· πŸ“‹ 100 - 44% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/google/objax) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 59 Β· πŸ“¦ 18 Β· πŸ“‹ 100 - 44% open Β· ⏱️ 01.02.2022): ``` git clone https://github.com/google/objax ``` -- [PyPi](https://pypi.org/project/objax) (πŸ“₯ 260 / month Β· πŸ“¦ 2 Β· ⏱️ 10.01.2022): +- [PyPi](https://pypi.org/project/objax) (πŸ“₯ 490 / month Β· πŸ“¦ 2 Β· ⏱️ 31.01.2022): ``` pip install objax ``` @@ -636,69 +654,63 @@ _General-purpose machine learning and deep learning frameworks._ ``` git clone https://github.com/Xtra-Computing/thundersvm ``` -- [PyPi](https://pypi.org/project/thundersvm) (πŸ“₯ 540 / month Β· ⏱️ 13.03.2020): +- [PyPi](https://pypi.org/project/thundersvm) (πŸ“₯ 830 / month Β· ⏱️ 13.03.2020): ``` pip install thundersvm ```
Torchbearer (πŸ₯‰21 Β· ⭐ 620 Β· πŸ’€) - torchbearer: A model fitting library for PyTorch. MIT -- [GitHub](https://github.com/pytorchbearer/torchbearer) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 68 Β· πŸ“¦ 56 Β· πŸ“‹ 240 - 3% open Β· ⏱️ 26.03.2021): +- [GitHub](https://github.com/pytorchbearer/torchbearer) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 68 Β· πŸ“¦ 59 Β· πŸ“‹ 240 - 3% open Β· ⏱️ 26.03.2021): ``` git clone https://github.com/pytorchbearer/torchbearer ``` -- [PyPi](https://pypi.org/project/torchbearer) (πŸ“₯ 660 / month Β· πŸ“¦ 4 Β· ⏱️ 31.01.2020): +- [PyPi](https://pypi.org/project/torchbearer) (πŸ“₯ 670 / month Β· πŸ“¦ 4 Β· ⏱️ 31.01.2020): ``` pip install torchbearer ```
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elegy (πŸ₯‰19 Β· ⭐ 310) - A High Level API for Deep Learning in JAX. MIT jax +
NeoML (πŸ₯‰19 Β· ⭐ 660) - Machine learning framework for both deep learning and traditional.. Apache-2 -- [GitHub](https://github.com/poets-ai/elegy) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 21 Β· πŸ“‹ 85 - 25% open Β· ⏱️ 14.12.2021): +- [GitHub](https://github.com/neoml-lib/neoml) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 100 Β· πŸ“‹ 70 - 40% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/poets-ai/elegy - ``` -- [PyPi](https://pypi.org/project/elegy) (πŸ“₯ 380 / month Β· ⏱️ 14.12.2021): - ``` - pip install elegy + git clone https://github.com/neoml-lib/neoml ``` -
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NeoML (πŸ₯‰18 Β· ⭐ 660) - Machine learning framework for both deep learning and traditional.. Apache-2 - -- [GitHub](https://github.com/neoml-lib/neoml) (πŸ‘¨β€πŸ’» 28 Β· πŸ”€ 100 Β· πŸ“‹ 70 - 40% open Β· ⏱️ 12.01.2022): - +- [PyPi](https://pypi.org/project/neoml) (πŸ“₯ 87 / month Β· ⏱️ 21.06.2021): ``` - git clone https://github.com/neoml-lib/neoml + pip install neoml ```
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ThunderGBM (πŸ₯‰17 Β· ⭐ 620 Β· πŸ’€) - ThunderGBM: Fast GBDTs and Random Forests on GPUs. Apache-2 +
elegy (πŸ₯‰18 Β· ⭐ 320) - A High Level API for Deep Learning in JAX. MIT -- [GitHub](https://github.com/Xtra-Computing/thundergbm) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 81 Β· πŸ“‹ 68 - 47% open Β· ⏱️ 05.01.2021): +- [GitHub](https://github.com/poets-ai/elegy) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 21 Β· πŸ“‹ 85 - 25% open Β· ⏱️ 14.12.2021): ``` - git clone https://github.com/Xtra-Computing/thundergbm + git clone https://github.com/poets-ai/elegy ``` -- [PyPi](https://pypi.org/project/thundergbm) (πŸ“₯ 110 / month Β· ⏱️ 01.05.2020): +- [PyPi](https://pypi.org/project/elegy) (πŸ“₯ 170 / month Β· ⏱️ 14.12.2021): ``` - pip install thundergbm + pip install elegy ```
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Show 12 hidden projects... +
Show 14 hidden projects... -- dlib (πŸ₯ˆ38 Β· ⭐ 11K) - A toolkit for making real world machine learning and data analysis.. ❗️BSL-1.0 +- dlib (πŸ₯ˆ39 Β· ⭐ 11K) - A toolkit for making real world machine learning and data analysis.. ❗️BSL-1.0 - TFlearn (πŸ₯‰32 Β· ⭐ 9.6K Β· πŸ’€) - Deep learning library featuring a higher-level API for TensorFlow. MIT - CNTK (πŸ₯‰31 Β· ⭐ 17K Β· πŸ’€) - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit. MIT -- MindsDB (πŸ₯‰29 Β· ⭐ 4.3K) - Predictive AI layer for existing databases. ❗️GPL-3.0 +- dyNET (πŸ₯‰31 Β· ⭐ 3.3K Β· πŸ’€) - DyNet: The Dynamic Neural Network Toolkit. Apache-2 - Lasagne (πŸ₯‰29 Β· ⭐ 3.8K Β· πŸ’€) - Lightweight library to build and train neural networks in Theano. MIT - NuPIC (πŸ₯‰28 Β· ⭐ 6.3K Β· πŸ’€) - Numenta Platform for Intelligent Computing is an implementation.. ❗️AGPL-3.0 -- SHOGUN (πŸ₯‰26 Β· ⭐ 2.9K Β· πŸ’€) - Unified and efficient Machine Learning. BSD-3 +- MindsDB (πŸ₯‰28 Β· ⭐ 5.4K) - In-Database Machine Learning. ❗️GPL-3.0 +- SHOGUN (πŸ₯‰27 Β· ⭐ 2.9K Β· πŸ’€) - Unified and efficient Machine Learning. BSD-3 - xLearn (πŸ₯‰25 Β· ⭐ 3K Β· πŸ’€) - High performance, easy-to-use, and scalable machine learning (ML).. Apache-2 - NeuPy (πŸ₯‰25 Β· ⭐ 700 Β· πŸ’€) - NeuPy is a Tensorflow based python library for prototyping and building.. MIT -- neon (πŸ₯‰22 Β· ⭐ 3.9K Β· πŸ’€) - Intel Nervana reference deep learning framework committed to best.. Apache-2 +- neon (πŸ₯‰23 Β· ⭐ 3.9K Β· πŸ’€) - Intel Nervana reference deep learning framework committed to best.. Apache-2 - chefboost (πŸ₯‰20 Β· ⭐ 300) - A Lightweight Decision Tree Framework supporting regular algorithms:.. MIT -- StarSpace (πŸ₯‰16 Β· ⭐ 3.7K Β· πŸ’€) - Learning embeddings for classification, retrieval and ranking. MIT +- ThunderGBM (πŸ₯‰16 Β· ⭐ 620 Β· πŸ’€) - ThunderGBM: Fast GBDTs and Random Forests on GPUs. Apache-2 +- StarSpace (πŸ₯‰15 Β· ⭐ 3.7K Β· πŸ’€) - Learning embeddings for classification, retrieval and ranking. MIT

@@ -710,12 +722,12 @@ _General-purpose and task-specific data visualization libraries._
Matplotlib (πŸ₯‡49 Β· ⭐ 15K) - matplotlib: plotting with Python. Python-2.0 -- [GitHub](https://github.com/matplotlib/matplotlib) (πŸ‘¨β€πŸ’» 1.3K Β· πŸ”€ 6.2K Β· πŸ“¦ 490K Β· πŸ“‹ 8.5K - 20% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/matplotlib/matplotlib) (πŸ‘¨β€πŸ’» 1.3K Β· πŸ”€ 6.2K Β· πŸ“¦ 500K Β· πŸ“‹ 8.6K - 20% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/matplotlib/matplotlib ``` -- [PyPi](https://pypi.org/project/matplotlib) (πŸ“₯ 24M / month Β· πŸ“¦ 52K Β· ⏱️ 11.12.2021): +- [PyPi](https://pypi.org/project/matplotlib) (πŸ“₯ 27M / month Β· πŸ“¦ 52K Β· ⏱️ 11.12.2021): ``` pip install matplotlib ``` @@ -726,64 +738,64 @@ _General-purpose and task-specific data visualization libraries._
Bokeh (πŸ₯‡43 Β· ⭐ 16K) - Interactive Data Visualization in the browser, from Python. BSD-3 -- [GitHub](https://github.com/bokeh/bokeh) (πŸ‘¨β€πŸ’» 590 Β· πŸ”€ 3.9K Β· πŸ“¦ 43K Β· πŸ“‹ 6.8K - 10% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/bokeh/bokeh) (πŸ‘¨β€πŸ’» 600 Β· πŸ”€ 3.9K Β· πŸ“¦ 45K Β· πŸ“‹ 6.8K - 10% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/bokeh/bokeh ``` -- [PyPi](https://pypi.org/project/bokeh) (πŸ“₯ 1.9M / month Β· πŸ“¦ 3.5K Β· ⏱️ 06.01.2022): +- [PyPi](https://pypi.org/project/bokeh) (πŸ“₯ 2.8M / month Β· πŸ“¦ 3.5K Β· ⏱️ 27.01.2022): ``` pip install bokeh ``` -- [Conda](https://anaconda.org/conda-forge/bokeh) (πŸ“₯ 6.3M Β· ⏱️ 22.11.2021): +- [Conda](https://anaconda.org/conda-forge/bokeh) (πŸ“₯ 6.5M Β· ⏱️ 22.11.2021): ``` conda install -c conda-forge bokeh ```
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Seaborn (πŸ₯‡42 Β· ⭐ 9.1K) - Statistical data visualization in Python. BSD-3 +
Plotly (πŸ₯‡42 Β· ⭐ 11K) - The interactive graphing library for Python (includes Plotly Express). MIT -- [GitHub](https://github.com/mwaskom/seaborn) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 1.5K Β· πŸ“₯ 210 Β· πŸ“¦ 130K Β· πŸ“‹ 2K - 4% open Β· ⏱️ 02.01.2022): +- [GitHub](https://github.com/plotly/plotly.py) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 2.1K Β· πŸ“¦ 9 Β· πŸ“‹ 2.3K - 48% open Β· ⏱️ 09.02.2022): ``` - git clone https://github.com/mwaskom/seaborn + git clone https://github.com/plotly/plotly.py ``` -- [PyPi](https://pypi.org/project/seaborn) (πŸ“₯ 5.2M / month Β· πŸ“¦ 8.8K Β· ⏱️ 16.08.2021): +- [PyPi](https://pypi.org/project/plotly) (πŸ“₯ 7.2M / month Β· πŸ“¦ 3.8K Β· ⏱️ 09.02.2022): ``` - pip install seaborn + pip install plotly + ``` +- [Conda](https://anaconda.org/conda-forge/plotly) (πŸ“₯ 2.2M Β· ⏱️ 21.12.2021): + ``` + conda install -c conda-forge plotly ``` -- [Conda](https://anaconda.org/conda-forge/seaborn) (πŸ“₯ 3.2M Β· ⏱️ 16.08.2021): +- [npm](https://www.npmjs.com/package/plotlywidget) (πŸ“₯ 52K / month Β· πŸ“¦ 4 Β· ⏱️ 12.01.2021): ``` - conda install -c conda-forge seaborn + npm install plotlywidget ```
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Plotly (πŸ₯‡41 Β· ⭐ 11K) - The interactive graphing library for Python (includes Plotly Express). MIT +
Seaborn (πŸ₯‡41 Β· ⭐ 9.1K) - Statistical data visualization in Python. BSD-3 -- [GitHub](https://github.com/plotly/plotly.py) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 2.1K Β· πŸ“¦ 9 Β· πŸ“‹ 2.2K - 47% open Β· ⏱️ 21.12.2021): +- [GitHub](https://github.com/mwaskom/seaborn) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 1.5K Β· πŸ“₯ 210 Β· πŸ“¦ 140K Β· πŸ“‹ 2K - 5% open Β· ⏱️ 18.01.2022): ``` - git clone https://github.com/plotly/plotly.py - ``` -- [PyPi](https://pypi.org/project/plotly) (πŸ“₯ 6.3M / month Β· πŸ“¦ 3.8K Β· ⏱️ 21.12.2021): - ``` - pip install plotly + git clone https://github.com/mwaskom/seaborn ``` -- [Conda](https://anaconda.org/conda-forge/plotly) (πŸ“₯ 2.2M Β· ⏱️ 21.12.2021): +- [PyPi](https://pypi.org/project/seaborn) (πŸ“₯ 6.9M / month Β· πŸ“¦ 8.8K Β· ⏱️ 16.08.2021): ``` - conda install -c conda-forge plotly + pip install seaborn ``` -- [npm](https://www.npmjs.com/package/plotlywidget) (πŸ“₯ 44K / month Β· πŸ“¦ 4 Β· ⏱️ 12.01.2021): +- [Conda](https://anaconda.org/conda-forge/seaborn) (πŸ“₯ 3.3M Β· ⏱️ 16.08.2021): ``` - npm install plotlywidget + conda install -c conda-forge seaborn ```
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Altair (πŸ₯‡39 Β· ⭐ 7.2K) - Declarative statistical visualization library for Python. BSD-3 +
Altair (πŸ₯‡39 Β· ⭐ 7.3K) - Declarative statistical visualization library for Python. BSD-3 -- [GitHub](https://github.com/altair-viz/altair) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 630 Β· πŸ“¦ 21K Β· πŸ“‹ 1.6K - 15% open Β· ⏱️ 29.12.2021): +- [GitHub](https://github.com/altair-viz/altair) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 630 Β· πŸ“¦ 22K Β· πŸ“‹ 1.6K - 15% open Β· ⏱️ 07.02.2022): ``` git clone https://github.com/altair-viz/altair ``` -- [PyPi](https://pypi.org/project/altair) (πŸ“₯ 3.7M / month Β· πŸ“¦ 340 Β· ⏱️ 29.12.2021): +- [PyPi](https://pypi.org/project/altair) (πŸ“₯ 4.7M / month Β· πŸ“¦ 340 Β· ⏱️ 29.12.2021): ``` pip install altair ``` @@ -794,96 +806,104 @@ _General-purpose and task-specific data visualization libraries._
dash (πŸ₯ˆ38 Β· ⭐ 16K) - Analytical Web Apps for Python, R, Julia, and Jupyter. No JavaScript Required. MIT -- [GitHub](https://github.com/plotly/dash) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 1.6K Β· πŸ“¦ 170 Β· πŸ“‹ 1.2K - 47% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/plotly/dash) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 1.6K Β· πŸ“¦ 180 Β· πŸ“‹ 1.2K - 47% open Β· ⏱️ 31.01.2022): ``` git clone https://github.com/plotly/dash ``` -- [PyPi](https://pypi.org/project/dash) (πŸ“₯ 1.1M / month Β· πŸ“¦ 1.1K Β· ⏱️ 04.09.2021): +- [PyPi](https://pypi.org/project/dash) (πŸ“₯ 930K / month Β· πŸ“¦ 1.1K Β· ⏱️ 28.01.2022): ``` pip install dash ``` -- [Conda](https://anaconda.org/conda-forge/dash) (πŸ“₯ 340K Β· ⏱️ 21.09.2021): +- [Conda](https://anaconda.org/conda-forge/dash) (πŸ“₯ 350K Β· ⏱️ 29.01.2022): ``` conda install -c conda-forge dash ```
Graphviz (πŸ₯ˆ37 Β· ⭐ 1.1K) - Simple Python interface for Graphviz. MIT -- [GitHub](https://github.com/xflr6/graphviz) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 170 Β· πŸ“¦ 27K Β· πŸ“‹ 120 - 3% open Β· ⏱️ 01.01.2022): +- [GitHub](https://github.com/xflr6/graphviz) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 170 Β· πŸ“¦ 28K Β· πŸ“‹ 130 - 5% open Β· ⏱️ 20.01.2022): ``` git clone https://github.com/xflr6/graphviz ``` -- [PyPi](https://pypi.org/project/graphviz) (πŸ“₯ 7.8M / month Β· πŸ“¦ 2.9K Β· ⏱️ 12.12.2021): +- [PyPi](https://pypi.org/project/graphviz) (πŸ“₯ 9M / month Β· πŸ“¦ 2.9K Β· ⏱️ 12.12.2021): ``` pip install graphviz ``` -
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pyecharts (πŸ₯ˆ36 Β· ⭐ 12K) - Python Echarts Plotting Library. MIT - -- [GitHub](https://github.com/pyecharts/pyecharts) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 2.6K Β· πŸ“¦ 2K Β· πŸ“‹ 1.5K - 1% open Β· ⏱️ 16.11.2021): - - ``` - git clone https://github.com/pyecharts/pyecharts - ``` -- [PyPi](https://pypi.org/project/pyecharts) (πŸ“₯ 66K / month Β· πŸ“¦ 210 Β· ⏱️ 16.11.2021): +- [Conda](https://anaconda.org/anaconda/python-graphviz) (πŸ“₯ 17K Β· ⏱️ 04.02.2021): ``` - pip install pyecharts + conda install -c anaconda python-graphviz ```
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pandas-profiling (πŸ₯ˆ36 Β· ⭐ 8.4K) - Create HTML profiling reports from pandas DataFrame.. MIT +
pandas-profiling (πŸ₯ˆ36 Β· ⭐ 8.5K) - Create HTML profiling reports from pandas DataFrame.. MIT -- [GitHub](https://github.com/pandas-profiling/pandas-profiling) (πŸ‘¨β€πŸ’» 83 Β· πŸ”€ 1.2K Β· πŸ“¦ 6.4K Β· πŸ“‹ 530 - 18% open Β· ⏱️ 08.01.2022): +- [GitHub](https://github.com/pandas-profiling/pandas-profiling) (πŸ‘¨β€πŸ’» 85 Β· πŸ”€ 1.2K Β· πŸ“¦ 6.6K Β· πŸ“‹ 540 - 19% open Β· ⏱️ 26.01.2022): ``` git clone https://github.com/pandas-profiling/pandas-profiling ``` -- [PyPi](https://pypi.org/project/pandas-profiling) (πŸ“₯ 960K / month Β· πŸ“¦ 140 Β· ⏱️ 27.09.2021): +- [PyPi](https://pypi.org/project/pandas-profiling) (πŸ“₯ 930K / month Β· πŸ“¦ 140 Β· ⏱️ 27.09.2021): ``` pip install pandas-profiling ``` -- [Conda](https://anaconda.org/conda-forge/pandas-profiling) (πŸ“₯ 180K Β· ⏱️ 28.09.2021): +- [Conda](https://anaconda.org/conda-forge/pandas-profiling) (πŸ“₯ 190K Β· ⏱️ 28.09.2021): ``` conda install -c conda-forge pandas-profiling ```
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UMAP (πŸ₯ˆ36 Β· ⭐ 5.3K) - Uniform Manifold Approximation and Projection. BSD-3 +
UMAP (πŸ₯ˆ36 Β· ⭐ 5.4K) - Uniform Manifold Approximation and Projection. BSD-3 -- [GitHub](https://github.com/lmcinnes/umap) (πŸ‘¨β€πŸ’» 97 Β· πŸ”€ 600 Β· πŸ“¦ 4.4K Β· πŸ“‹ 590 - 51% open Β· ⏱️ 04.01.2022): +- [GitHub](https://github.com/lmcinnes/umap) (πŸ‘¨β€πŸ’» 98 Β· πŸ”€ 610 Β· πŸ“¦ 4.5K Β· πŸ“‹ 600 - 52% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/lmcinnes/umap ``` -- [PyPi](https://pypi.org/project/umap-learn) (πŸ“₯ 1.4M / month Β· πŸ“¦ 290 Β· ⏱️ 29.10.2021): +- [PyPi](https://pypi.org/project/umap-learn) (πŸ“₯ 1M / month Β· πŸ“¦ 290 Β· ⏱️ 29.10.2021): ``` pip install umap-learn ``` +- [Conda](https://anaconda.org/conda-forge/umap-learn) (πŸ“₯ 890K Β· ⏱️ 15.01.2022): + ``` + conda install -c conda-forge umap-learn + ``` +
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pyecharts (πŸ₯ˆ35 Β· ⭐ 12K) - Python Echarts Plotting Library. MIT + +- [GitHub](https://github.com/pyecharts/pyecharts) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 2.6K Β· πŸ“¦ 2K Β· πŸ“‹ 1.5K - 1% open Β· ⏱️ 16.11.2021): + + ``` + git clone https://github.com/pyecharts/pyecharts + ``` +- [PyPi](https://pypi.org/project/pyecharts) (πŸ“₯ 41K / month Β· πŸ“¦ 210 Β· ⏱️ 16.11.2021): + ``` + pip install pyecharts + ```
PyQtGraph (πŸ₯ˆ34 Β· ⭐ 2.7K) - Fast data visualization and GUI tools for scientific / engineering.. MIT -- [GitHub](https://github.com/pyqtgraph/pyqtgraph) (πŸ‘¨β€πŸ’» 220 Β· πŸ”€ 900 Β· πŸ“‹ 990 - 31% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/pyqtgraph/pyqtgraph) (πŸ‘¨β€πŸ’» 220 Β· πŸ”€ 900 Β· πŸ“‹ 990 - 31% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/pyqtgraph/pyqtgraph ``` -- [PyPi](https://pypi.org/project/pyqtgraph) (πŸ“₯ 56K / month Β· πŸ“¦ 760 Β· ⏱️ 11.10.2021): +- [PyPi](https://pypi.org/project/pyqtgraph) (πŸ“₯ 77K / month Β· πŸ“¦ 760 Β· ⏱️ 11.10.2021): ``` pip install pyqtgraph ``` -- [Conda](https://anaconda.org/conda-forge/pyqtgraph) (πŸ“₯ 210K Β· ⏱️ 11.10.2021): +- [Conda](https://anaconda.org/conda-forge/pyqtgraph) (πŸ“₯ 220K Β· ⏱️ 11.10.2021): ``` conda install -c conda-forge pyqtgraph ```
HoloViews (πŸ₯ˆ34 Β· ⭐ 2.1K) - With Holoviews, your data visualizes itself. BSD-3 -- [GitHub](https://github.com/holoviz/holoviews) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 340 Β· πŸ“‹ 2.7K - 29% open Β· ⏱️ 18.12.2021): +- [GitHub](https://github.com/holoviz/holoviews) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 350 Β· πŸ“‹ 2.7K - 30% open Β· ⏱️ 08.02.2022): ``` git clone https://github.com/holoviz/holoviews ``` -- [PyPi](https://pypi.org/project/holoviews) (πŸ“₯ 220K / month Β· πŸ“¦ 190 Β· ⏱️ 16.12.2021): +- [PyPi](https://pypi.org/project/holoviews) (πŸ“₯ 230K / month Β· πŸ“¦ 200 Β· ⏱️ 21.01.2022): ``` pip install holoviews ``` @@ -891,7 +911,7 @@ _General-purpose and task-specific data visualization libraries._ ``` conda install -c conda-forge holoviews ``` -- [npm](https://www.npmjs.com/package/@pyviz/jupyterlab_pyviz) (πŸ“₯ 1.7K / month Β· ⏱️ 24.05.2020): +- [npm](https://www.npmjs.com/package/@pyviz/jupyterlab_pyviz) (πŸ“₯ 1.8K / month Β· ⏱️ 24.05.2020): ``` npm install @pyviz/jupyterlab_pyviz ``` @@ -903,79 +923,83 @@ _General-purpose and task-specific data visualization libraries._ ``` git clone https://github.com/amueller/word_cloud ``` -- [PyPi](https://pypi.org/project/wordcloud) (πŸ“₯ 500K / month Β· πŸ“¦ 710 Β· ⏱️ 11.11.2020): +- [PyPi](https://pypi.org/project/wordcloud) (πŸ“₯ 600K / month Β· πŸ“¦ 710 Β· ⏱️ 11.11.2020): ``` pip install wordcloud ``` -- [Conda](https://anaconda.org/conda-forge/wordcloud) (πŸ“₯ 250K Β· ⏱️ 15.11.2021): +- [Conda](https://anaconda.org/conda-forge/wordcloud) (πŸ“₯ 260K Β· ⏱️ 15.11.2021): ``` conda install -c conda-forge wordcloud ```
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Perspective (πŸ₯ˆ32 Β· ⭐ 4.1K) - A data visualization and analytics component, especially.. Apache-2 +
Perspective (πŸ₯ˆ33 Β· ⭐ 4.2K) - A data visualization and analytics component, especially.. Apache-2 -- [GitHub](https://github.com/finos/perspective) (πŸ‘¨β€πŸ’» 65 Β· πŸ”€ 430 Β· πŸ“¦ 220 Β· πŸ“‹ 490 - 14% open Β· ⏱️ 06.01.2022): +- [GitHub](https://github.com/finos/perspective) (πŸ‘¨β€πŸ’» 65 Β· πŸ”€ 440 Β· πŸ“¦ 220 Β· πŸ“‹ 500 - 14% open Β· ⏱️ 06.02.2022): ``` git clone https://github.com/finos/perspective ``` -- [PyPi](https://pypi.org/project/perspective-python) (πŸ“₯ 3K / month Β· πŸ“¦ 9 Β· ⏱️ 06.01.2022): +- [PyPi](https://pypi.org/project/perspective-python) (πŸ“₯ 4.2K / month Β· πŸ“¦ 9 Β· ⏱️ 02.02.2022): ``` pip install perspective-python ``` -- [npm](https://www.npmjs.com/package/@finos/perspective-jupyterlab) (πŸ“₯ 1.7K / month Β· ⏱️ 05.01.2022): +- [Conda](https://anaconda.org/conda-forge/perspective) (πŸ“₯ 40K Β· ⏱️ 02.02.2022): + ``` + conda install -c conda-forge perspective + ``` +- [npm](https://www.npmjs.com/package/@finos/perspective-jupyterlab) (πŸ“₯ 2.2K / month Β· ⏱️ 01.02.2022): ``` npm install @finos/perspective-jupyterlab ```
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VisPy (πŸ₯ˆ32 Β· ⭐ 2.8K) - High-performance interactive 2D/3D data visualization library. BSD-3 +
bqplot (πŸ₯ˆ32 Β· ⭐ 3.2K) - Plotting library for IPython/Jupyter notebooks. Apache-2 -- [GitHub](https://github.com/vispy/vispy) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 580 Β· πŸ“¦ 660 Β· πŸ“‹ 1.3K - 22% open Β· ⏱️ 10.12.2021): +- [GitHub](https://github.com/bqplot/bqplot) (πŸ‘¨β€πŸ’» 56 Β· πŸ”€ 460 Β· πŸ“¦ 30 Β· πŸ“‹ 580 - 38% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/vispy/vispy + git clone https://github.com/bqplot/bqplot ``` -- [PyPi](https://pypi.org/project/vispy) (πŸ“₯ 35K / month Β· πŸ“¦ 93 Β· ⏱️ 24.11.2021): +- [PyPi](https://pypi.org/project/bqplot) (πŸ“₯ 65K / month Β· πŸ“¦ 90 Β· ⏱️ 07.01.2022): ``` - pip install vispy + pip install bqplot ``` -- [Conda](https://anaconda.org/conda-forge/vispy) (πŸ“₯ 200K Β· ⏱️ 24.11.2021): +- [Conda](https://anaconda.org/conda-forge/bqplot) (πŸ“₯ 920K Β· ⏱️ 07.01.2022): ``` - conda install -c conda-forge vispy + conda install -c conda-forge bqplot ``` -- [npm](https://www.npmjs.com/package/vispy) (πŸ“₯ 13 / month Β· ⏱️ 15.03.2020): +- [npm](https://www.npmjs.com/package/bqplot) (πŸ“₯ 24K / month Β· πŸ“¦ 10 Β· ⏱️ 07.01.2022): ``` - npm install vispy + npm install bqplot ```
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bqplot (πŸ₯ˆ31 Β· ⭐ 3.2K) - Plotting library for IPython/Jupyter notebooks. Apache-2 +
VisPy (πŸ₯ˆ32 Β· ⭐ 2.8K) - High-performance interactive 2D/3D data visualization library. BSD-3 -- [GitHub](https://github.com/bqplot/bqplot) (πŸ‘¨β€πŸ’» 55 Β· πŸ”€ 460 Β· πŸ“¦ 29 Β· πŸ“‹ 580 - 38% open Β· ⏱️ 07.01.2022): +- [GitHub](https://github.com/vispy/vispy) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 580 Β· πŸ“¦ 680 Β· πŸ“‹ 1.3K - 21% open Β· ⏱️ 08.02.2022): ``` - git clone https://github.com/bqplot/bqplot + git clone https://github.com/vispy/vispy ``` -- [PyPi](https://pypi.org/project/bqplot) (πŸ“₯ 47K / month Β· πŸ“¦ 90 Β· ⏱️ 07.01.2022): +- [PyPi](https://pypi.org/project/vispy) (πŸ“₯ 41K / month Β· πŸ“¦ 94 Β· ⏱️ 04.02.2022): ``` - pip install bqplot + pip install vispy ``` -- [Conda](https://anaconda.org/conda-forge/bqplot) (πŸ“₯ 910K Β· ⏱️ 07.01.2022): +- [Conda](https://anaconda.org/conda-forge/vispy) (πŸ“₯ 200K Β· ⏱️ 05.02.2022): ``` - conda install -c conda-forge bqplot + conda install -c conda-forge vispy ``` -- [npm](https://www.npmjs.com/package/bqplot) (πŸ“₯ 17K / month Β· πŸ“¦ 10 Β· ⏱️ 07.01.2022): +- [npm](https://www.npmjs.com/package/vispy) (πŸ“₯ 10 / month Β· ⏱️ 15.03.2020): ``` - npm install bqplot + npm install vispy ```
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PyVista (πŸ₯ˆ31 Β· ⭐ 1.1K) - 3D plotting and mesh analysis through a streamlined interface for.. MIT +
PyVista (πŸ₯ˆ32 Β· ⭐ 1.1K) - 3D plotting and mesh analysis through a streamlined interface for.. MIT -- [GitHub](https://github.com/pyvista/pyvista) (πŸ‘¨β€πŸ’» 68 Β· πŸ”€ 210 Β· πŸ“₯ 390 Β· πŸ“¦ 560 Β· πŸ“‹ 660 - 26% open Β· ⏱️ 11.01.2022): +- [GitHub](https://github.com/pyvista/pyvista) (πŸ‘¨β€πŸ’» 70 Β· πŸ”€ 210 Β· πŸ“₯ 490 Β· πŸ“¦ 600 Β· πŸ“‹ 690 - 25% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/pyvista/pyvista ``` -- [PyPi](https://pypi.org/project/pyvista) (πŸ“₯ 32K / month Β· πŸ“¦ 85 Β· ⏱️ 11.01.2022): +- [PyPi](https://pypi.org/project/pyvista) (πŸ“₯ 42K / month Β· πŸ“¦ 85 Β· ⏱️ 11.01.2022): ``` pip install pyvista ``` @@ -984,21 +1008,21 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge pyvista ```
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FiftyOne (πŸ₯ˆ31 Β· ⭐ 930) - Visualize, create, and debug image and video datasets.. Apache-2 +
FiftyOne (πŸ₯ˆ31 Β· ⭐ 980) - Visualize, create, and debug image and video datasets.. Apache-2 -- [GitHub](https://github.com/voxel51/fiftyone) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 110 Β· πŸ“¦ 71 Β· πŸ“‹ 650 - 30% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/voxel51/fiftyone) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 120 Β· πŸ“¦ 80 Β· πŸ“‹ 680 - 31% open Β· ⏱️ 07.02.2022): ``` git clone https://github.com/voxel51/fiftyone ``` -- [PyPi](https://pypi.org/project/fiftyone) (πŸ“₯ 18K / month Β· πŸ“¦ 1 Β· ⏱️ 13.01.2022): +- [PyPi](https://pypi.org/project/fiftyone) (πŸ“₯ 22K / month Β· πŸ“¦ 1 Β· ⏱️ 07.02.2022): ``` pip install fiftyone ```
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datashader (πŸ₯‰30 Β· ⭐ 2.7K) - Quickly and accurately render even the largest data. BSD-3 +
datashader (πŸ₯ˆ30 Β· ⭐ 2.7K) - Quickly and accurately render even the largest data. BSD-3 -- [GitHub](https://github.com/holoviz/datashader) (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 330 Β· πŸ“¦ 930 Β· πŸ“‹ 480 - 26% open Β· ⏱️ 25.12.2021): +- [GitHub](https://github.com/holoviz/datashader) (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 330 Β· πŸ“¦ 950 Β· πŸ“‹ 480 - 26% open Β· ⏱️ 08.02.2022): ``` git clone https://github.com/holoviz/datashader @@ -1007,43 +1031,43 @@ _General-purpose and task-specific data visualization libraries._ ``` pip install datashader ``` -- [Conda](https://anaconda.org/conda-forge/datashader) (πŸ“₯ 250K Β· ⏱️ 10.06.2021): +- [Conda](https://anaconda.org/conda-forge/datashader) (πŸ“₯ 260K Β· ⏱️ 10.06.2021): ``` conda install -c conda-forge datashader ```
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Cufflinks (πŸ₯‰30 Β· ⭐ 2.5K Β· πŸ’€) - Productivity Tools for Plotly + Pandas. MIT +
Cufflinks (πŸ₯ˆ30 Β· ⭐ 2.5K Β· πŸ’€) - Productivity Tools for Plotly + Pandas. MIT -- [GitHub](https://github.com/santosjorge/cufflinks) (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 580 Β· πŸ“¦ 5K Β· πŸ“‹ 220 - 42% open Β· ⏱️ 25.02.2021): +- [GitHub](https://github.com/santosjorge/cufflinks) (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 580 Β· πŸ“¦ 5.2K Β· πŸ“‹ 220 - 42% open Β· ⏱️ 25.02.2021): ``` git clone https://github.com/santosjorge/cufflinks ``` -- [PyPi](https://pypi.org/project/cufflinks) (πŸ“₯ 230K / month Β· πŸ“¦ 160 Β· ⏱️ 15.12.2021): +- [PyPi](https://pypi.org/project/cufflinks) (πŸ“₯ 280K / month Β· πŸ“¦ 160 Β· ⏱️ 15.12.2021): ``` pip install cufflinks ```
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data-validation (πŸ₯‰30 Β· ⭐ 600) - Library for exploring and validating machine learning.. Apache-2 +
data-validation (πŸ₯ˆ30 Β· ⭐ 600) - Library for exploring and validating machine learning.. Apache-2 -- [GitHub](https://github.com/tensorflow/data-validation) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 110 Β· πŸ“₯ 290 Β· πŸ“¦ 370 Β· πŸ“‹ 150 - 25% open Β· ⏱️ 07.01.2022): +- [GitHub](https://github.com/tensorflow/data-validation) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 110 Β· πŸ“₯ 300 Β· πŸ“¦ 380 Β· πŸ“‹ 150 - 24% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/tensorflow/data-validation ``` -- [PyPi](https://pypi.org/project/tensorflow-data-validation) (πŸ“₯ 6.7M / month Β· πŸ“¦ 24 Β· ⏱️ 01.12.2021): +- [PyPi](https://pypi.org/project/tensorflow-data-validation) (πŸ“₯ 7.3M / month Β· πŸ“¦ 26 Β· ⏱️ 21.01.2022): ``` pip install tensorflow-data-validation ```
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missingno (πŸ₯‰29 Β· ⭐ 3K) - Missing data visualization module for Python. MIT +
missingno (πŸ₯‰29 Β· ⭐ 3.1K Β· πŸ’€) - Missing data visualization module for Python. MIT -- [GitHub](https://github.com/ResidentMario/missingno) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 380 Β· πŸ“¦ 5.9K Β· πŸ“‹ 110 - 9% open Β· ⏱️ 04.07.2021): +- [GitHub](https://github.com/ResidentMario/missingno) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 380 Β· πŸ“¦ 6.2K Β· πŸ“‹ 110 - 10% open Β· ⏱️ 04.07.2021): ``` git clone https://github.com/ResidentMario/missingno ``` -- [PyPi](https://pypi.org/project/missingno) (πŸ“₯ 650K / month Β· πŸ“¦ 110 Β· ⏱️ 04.07.2021): +- [PyPi](https://pypi.org/project/missingno) (πŸ“₯ 810K / month Β· πŸ“¦ 110 Β· ⏱️ 04.07.2021): ``` pip install missingno ``` @@ -1052,26 +1076,14 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge missingno ```
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Facets Overview (πŸ₯‰28 Β· ⭐ 6.8K Β· πŸ’€) - Visualizations for machine learning datasets. Apache-2 - -- [GitHub](https://github.com/PAIR-code/facets) (πŸ‘¨β€πŸ’» 28 Β· πŸ”€ 830 Β· πŸ“¦ 95 Β· πŸ“‹ 150 - 50% open Β· ⏱️ 06.05.2021): - - ``` - git clone https://github.com/pair-code/facets - ``` -- [PyPi](https://pypi.org/project/facets-overview) (πŸ“₯ 100K / month Β· πŸ“¦ 4 Β· ⏱️ 24.07.2019): - ``` - pip install facets-overview - ``` -
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D-Tale (πŸ₯‰28 Β· ⭐ 2.9K) - Visualizer for pandas data structures. ❗️LGPL-2.1 +
D-Tale (πŸ₯‰29 Β· ⭐ 3.1K) - Visualizer for pandas data structures. ❗️LGPL-2.1 -- [GitHub](https://github.com/man-group/dtale) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 220 Β· πŸ“¦ 280 Β· πŸ“‹ 440 - 9% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/man-group/dtale) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 230 Β· πŸ“¦ 280 Β· πŸ“‹ 440 - 9% open Β· ⏱️ 08.02.2022): ``` git clone https://github.com/man-group/dtale ``` -- [PyPi](https://pypi.org/project/dtale) (πŸ“₯ 47K / month Β· πŸ“¦ 11 Β· ⏱️ 18.11.2021): +- [PyPi](https://pypi.org/project/dtale) (πŸ“₯ 56K / month Β· πŸ“¦ 11 Β· ⏱️ 18.11.2021): ``` pip install dtale ``` @@ -1080,46 +1092,54 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge dtale ```
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hvPlot (πŸ₯‰27 Β· ⭐ 500) - A high-level plotting API for pandas, dask, xarray, and networkx built on.. BSD-3 +
hvPlot (πŸ₯‰28 Β· ⭐ 520) - A high-level plotting API for pandas, dask, xarray, and networkx built on.. BSD-3 -- [GitHub](https://github.com/holoviz/hvplot) (πŸ‘¨β€πŸ’» 33 Β· πŸ”€ 62 Β· πŸ“¦ 970 Β· πŸ“‹ 400 - 35% open Β· ⏱️ 16.12.2021): +- [GitHub](https://github.com/holoviz/hvplot) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 64 Β· πŸ“¦ 1K Β· πŸ“‹ 410 - 35% open Β· ⏱️ 08.02.2022): ``` git clone https://github.com/holoviz/hvplot ``` -- [PyPi](https://pypi.org/project/hvplot) (πŸ“₯ 87K / month Β· πŸ“¦ 55 Β· ⏱️ 09.12.2021): +- [PyPi](https://pypi.org/project/hvplot) (πŸ“₯ 96K / month Β· πŸ“¦ 55 Β· ⏱️ 09.12.2021): ``` pip install hvplot ``` -- [Conda](https://anaconda.org/conda-forge/hvplot) (πŸ“₯ 140K Β· ⏱️ 23.07.2021): +- [Conda](https://anaconda.org/conda-forge/hvplot) (πŸ“₯ 150K Β· ⏱️ 23.07.2021): ``` conda install -c conda-forge hvplot ```
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openTSNE (πŸ₯‰26 Β· ⭐ 940) - Extensible, parallel implementations of t-SNE. BSD-3 +
Facets Overview (πŸ₯‰27 Β· ⭐ 6.8K Β· πŸ’€) - Visualizations for machine learning datasets. Apache-2 -- [GitHub](https://github.com/pavlin-policar/openTSNE) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 99 Β· πŸ“¦ 270 Β· πŸ“‹ 99 - 4% open Β· ⏱️ 25.10.2021): +- [GitHub](https://github.com/PAIR-code/facets) (πŸ‘¨β€πŸ’» 28 Β· πŸ”€ 830 Β· πŸ“¦ 100 Β· πŸ“‹ 150 - 50% open Β· ⏱️ 06.05.2021): ``` - git clone https://github.com/pavlin-policar/openTSNE + git clone https://github.com/pair-code/facets ``` -- [PyPi](https://pypi.org/project/opentsne) (πŸ“₯ 15K / month Β· πŸ“¦ 8 Β· ⏱️ 25.10.2021): +- [PyPi](https://pypi.org/project/facets-overview) (πŸ“₯ 150K / month Β· πŸ“¦ 4 Β· ⏱️ 24.07.2019): ``` - pip install opentsne + pip install facets-overview ``` -- [Conda](https://anaconda.org/conda-forge/opentsne) (πŸ“₯ 130K Β· ⏱️ 13.11.2021): +
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HyperTools (πŸ₯‰26 Β· ⭐ 1.7K) - A Python toolbox for gaining geometric insights into high-dimensional.. MIT + +- [GitHub](https://github.com/ContextLab/hypertools) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 150 Β· πŸ“₯ 8 Β· πŸ“¦ 160 Β· πŸ“‹ 190 - 35% open Β· ⏱️ 09.02.2022): + ``` - conda install -c conda-forge opentsne + git clone https://github.com/ContextLab/hypertools + ``` +- [PyPi](https://pypi.org/project/hypertools) (πŸ“₯ 1.5K / month Β· πŸ“¦ 9 Β· ⏱️ 15.06.2021): + ``` + pip install hypertools ```
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pythreejs (πŸ₯‰26 Β· ⭐ 780) - A Jupyter - Three.js bridge. BSD-3 +
pythreejs (πŸ₯‰26 Β· ⭐ 790) - A Jupyter - Three.js bridge. BSD-3 - [GitHub](https://github.com/jupyter-widgets/pythreejs) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 160 Β· πŸ“¦ 19 Β· πŸ“‹ 210 - 31% open Β· ⏱️ 06.12.2021): ``` git clone https://github.com/jupyter-widgets/pythreejs ``` -- [PyPi](https://pypi.org/project/pythreejs) (πŸ“₯ 28K / month Β· πŸ“¦ 34 Β· ⏱️ 26.02.2021): +- [PyPi](https://pypi.org/project/pythreejs) (πŸ“₯ 39K / month Β· πŸ“¦ 34 Β· ⏱️ 26.02.2021): ``` pip install pythreejs ``` @@ -1127,187 +1147,203 @@ _General-purpose and task-specific data visualization libraries._ ``` conda install -c conda-forge pythreejs ``` -- [npm](https://www.npmjs.com/package/jupyter-threejs) (πŸ“₯ 4.5K / month Β· πŸ“¦ 7 Β· ⏱️ 26.02.2021): +- [npm](https://www.npmjs.com/package/jupyter-threejs) (πŸ“₯ 5.6K / month Β· πŸ“¦ 7 Β· ⏱️ 26.02.2021): ``` npm install jupyter-threejs ```
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lets-plot (πŸ₯‰26 Β· ⭐ 710) - An open-source plotting library for statistical data. MIT +
lets-plot (πŸ₯‰26 Β· ⭐ 720) - An open-source plotting library for statistical data. MIT -- [GitHub](https://github.com/JetBrains/lets-plot) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 32 Β· πŸ“₯ 170 Β· πŸ“¦ 12 Β· πŸ“‹ 230 - 32% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/JetBrains/lets-plot) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 32 Β· πŸ“₯ 200 Β· πŸ“¦ 13 Β· πŸ“‹ 230 - 30% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/JetBrains/lets-plot ``` -- [PyPi](https://pypi.org/project/lets-plot) (πŸ“₯ 1.5K / month Β· πŸ“¦ 1 Β· ⏱️ 10.12.2021): +- [PyPi](https://pypi.org/project/lets-plot) (πŸ“₯ 2.5K / month Β· πŸ“¦ 1 Β· ⏱️ 10.12.2021): ``` pip install lets-plot ```
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HyperTools (πŸ₯‰25 Β· ⭐ 1.7K) - A Python toolbox for gaining geometric insights into high-dimensional.. MIT +
Chartify (πŸ₯‰25 Β· ⭐ 3.1K Β· πŸ’€) - Python library that makes it easy for data scientists to create.. Apache-2 -- [GitHub](https://github.com/ContextLab/hypertools) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 160 Β· πŸ“₯ 8 Β· πŸ“¦ 160 Β· πŸ“‹ 190 - 35% open Β· ⏱️ 19.07.2021): +- [GitHub](https://github.com/spotify/chartify) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 280 Β· πŸ“¦ 61 Β· πŸ“‹ 72 - 56% open Β· ⏱️ 05.02.2021): ``` - git clone https://github.com/ContextLab/hypertools + git clone https://github.com/spotify/chartify ``` -- [PyPi](https://pypi.org/project/hypertools) (πŸ“₯ 1.3K / month Β· πŸ“¦ 9 Β· ⏱️ 15.06.2021): +- [PyPi](https://pypi.org/project/chartify) (πŸ“₯ 1.8K / month Β· πŸ“¦ 5 Β· ⏱️ 02.11.2020): ``` - pip install hypertools + pip install chartify + ``` +- [Conda](https://anaconda.org/conda-forge/chartify) (πŸ“₯ 18K Β· ⏱️ 07.11.2020): + ``` + conda install -c conda-forge chartify ```
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Chartify (πŸ₯‰24 Β· ⭐ 3.1K Β· πŸ’€) - Python library that makes it easy for data scientists to create.. Apache-2 +
vega (πŸ₯‰25 Β· ⭐ 320) - IPython/Jupyter notebook module for Vega and Vega-Lite. BSD-3 -- [GitHub](https://github.com/spotify/chartify) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 270 Β· πŸ“¦ 61 Β· πŸ“‹ 72 - 56% open Β· ⏱️ 05.02.2021): +- [GitHub](https://github.com/vega/ipyvega) (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 59 Β· πŸ“‹ 94 - 12% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/spotify/chartify + git clone https://github.com/vega/ipyvega ``` -- [PyPi](https://pypi.org/project/chartify) (πŸ“₯ 1.3K / month Β· πŸ“¦ 5 Β· ⏱️ 02.11.2020): +- [PyPi](https://pypi.org/project/vega) (πŸ“₯ 9.6K / month Β· πŸ“¦ 84 Β· ⏱️ 10.02.2022): ``` - pip install chartify + pip install vega ``` -- [Conda](https://anaconda.org/conda-forge/chartify) (πŸ“₯ 18K Β· ⏱️ 07.11.2020): +- [Conda](https://anaconda.org/conda-forge/vega) (πŸ“₯ 470K Β· ⏱️ 10.02.2022): ``` - conda install -c conda-forge chartify + conda install -c conda-forge vega ```
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HiPlot (πŸ₯‰24 Β· ⭐ 2.2K) - HiPlot makes understanding high dimensional data easy. MIT +
HiPlot (πŸ₯‰24 Β· ⭐ 2.3K) - HiPlot makes understanding high dimensional data easy. MIT -- [GitHub](https://github.com/facebookresearch/hiplot) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 110 Β· πŸ“¦ 3 Β· πŸ“‹ 71 - 14% open Β· ⏱️ 05.11.2021): +- [GitHub](https://github.com/facebookresearch/hiplot) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 110 Β· πŸ“¦ 3 Β· πŸ“‹ 73 - 16% open Β· ⏱️ 07.02.2022): ``` git clone https://github.com/facebookresearch/hiplot ``` -- [PyPi](https://pypi.org/project/hiplot) (πŸ“₯ 9.3K / month Β· πŸ“¦ 9 Β· ⏱️ 05.11.2021): +- [PyPi](https://pypi.org/project/hiplot) (πŸ“₯ 11K / month Β· πŸ“¦ 9 Β· ⏱️ 05.11.2021): ``` pip install hiplot ``` -- [Conda](https://anaconda.org/conda-forge/hiplot) (πŸ“₯ 75K Β· ⏱️ 05.11.2021): +- [Conda](https://anaconda.org/conda-forge/hiplot) (πŸ“₯ 76K Β· ⏱️ 05.11.2021): ``` conda install -c conda-forge hiplot ```
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AutoViz (πŸ₯‰24 Β· ⭐ 600) - Automatically Visualize any dataset, any size with a single line of.. Apache-2 +
openTSNE (πŸ₯‰24 Β· ⭐ 940 Β· πŸ“‰) - Extensible, parallel implementations of t-SNE. BSD-3 -- [GitHub](https://github.com/AutoViML/AutoViz) (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 91 Β· πŸ“¦ 130 Β· πŸ“‹ 46 - 13% open Β· ⏱️ 25.12.2021): +- [GitHub](https://github.com/pavlin-policar/openTSNE) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 100 Β· πŸ“¦ 280 Β· πŸ“‹ 100 - 5% open Β· ⏱️ 25.10.2021): ``` - git clone https://github.com/AutoViML/AutoViz + git clone https://github.com/pavlin-policar/openTSNE ``` -- [PyPi](https://pypi.org/project/autoviz) (πŸ“₯ 22K / month Β· πŸ“¦ 3 Β· ⏱️ 25.12.2021): +- [PyPi](https://pypi.org/project/opentsne) (πŸ“₯ 23K / month Β· πŸ“¦ 8 Β· ⏱️ 25.10.2021): ``` - pip install autoviz + pip install opentsne + ``` +- [Conda](https://anaconda.org/conda-forge/opentsne) (πŸ“₯ 130K Β· ⏱️ 13.11.2021): + ``` + conda install -c conda-forge opentsne ```
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vega (πŸ₯‰24 Β· ⭐ 320) - IPython/Jupyter notebook module for Vega and Vega-Lite. BSD-3 +
AutoViz (πŸ₯‰24 Β· ⭐ 630) - Automatically Visualize any dataset, any size with a single line of.. Apache-2 -- [GitHub](https://github.com/vega/ipyvega) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 55 Β· πŸ“‹ 95 - 14% open Β· ⏱️ 02.01.2022): +- [GitHub](https://github.com/AutoViML/AutoViz) (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 92 Β· πŸ“¦ 130 Β· πŸ“‹ 47 - 12% open Β· ⏱️ 05.02.2022): ``` - git clone https://github.com/vega/ipyvega + git clone https://github.com/AutoViML/AutoViz ``` -- [PyPi](https://pypi.org/project/vega) (πŸ“₯ 13K / month Β· πŸ“¦ 82 Β· ⏱️ 03.06.2021): +- [PyPi](https://pypi.org/project/autoviz) (πŸ“₯ 37K / month Β· πŸ“¦ 3 Β· ⏱️ 25.12.2021): ``` - pip install vega + pip install autoviz ``` -- [Conda](https://anaconda.org/conda-forge/vega) (πŸ“₯ 470K Β· ⏱️ 18.11.2021): +- [Conda](https://anaconda.org/conda-forge/autoviz) (πŸ“₯ 2.1K Β· ⏱️ 25.12.2021): ``` - conda install -c conda-forge vega + conda install -c conda-forge autoviz ```
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Pandas-Bokeh (πŸ₯‰23 Β· ⭐ 740) - Bokeh Plotting Backend for Pandas and GeoPandas. MIT +
Pandas-Bokeh (πŸ₯‰23 Β· ⭐ 760) - Bokeh Plotting Backend for Pandas and GeoPandas. MIT -- [GitHub](https://github.com/PatrikHlobil/Pandas-Bokeh) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 94 Β· πŸ“¦ 270 Β· πŸ“‹ 95 - 30% open Β· ⏱️ 11.01.2022): +- [GitHub](https://github.com/PatrikHlobil/Pandas-Bokeh) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 95 Β· πŸ“¦ 280 Β· πŸ“‹ 95 - 30% open Β· ⏱️ 11.01.2022): ``` git clone https://github.com/PatrikHlobil/Pandas-Bokeh ``` -- [PyPi](https://pypi.org/project/pandas-bokeh) (πŸ“₯ 10K / month Β· πŸ“¦ 11 Β· ⏱️ 11.04.2021): +- [PyPi](https://pypi.org/project/pandas-bokeh) (πŸ“₯ 16K / month Β· πŸ“¦ 11 Β· ⏱️ 11.04.2021): ``` pip install pandas-bokeh ```
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joypy (πŸ₯‰23 Β· ⭐ 390) - Joyplots in Python with matplotlib & pandas. MIT +
python-ternary (πŸ₯‰23 Β· ⭐ 510) - Ternary plotting library for python with matplotlib. MIT -- [GitHub](https://github.com/leotac/joypy) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 44 Β· πŸ“¦ 110 Β· πŸ“‹ 48 - 22% open Β· ⏱️ 19.12.2021): +- [GitHub](https://github.com/marcharper/python-ternary) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 130 Β· πŸ“₯ 17 Β· πŸ“¦ 84 Β· πŸ“‹ 120 - 20% open Β· ⏱️ 21.10.2021): ``` - git clone https://github.com/leotac/joypy + git clone https://github.com/marcharper/python-ternary ``` -- [PyPi](https://pypi.org/project/joypy) (πŸ“₯ 20K / month Β· πŸ“¦ 5 Β· ⏱️ 19.12.2021): +- [PyPi](https://pypi.org/project/python-ternary) (πŸ“₯ 16K / month Β· πŸ“¦ 21 Β· ⏱️ 17.02.2021): ``` - pip install joypy + pip install python-ternary ``` -- [Conda](https://anaconda.org/conda-forge/joypy) (πŸ“₯ 12K Β· ⏱️ 28.12.2020): +- [Conda](https://anaconda.org/conda-forge/python-ternary) (πŸ“₯ 61K Β· ⏱️ 17.02.2021): ``` - conda install -c conda-forge joypy + conda install -c conda-forge python-ternary ```
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PDPbox (πŸ₯‰22 Β· ⭐ 650 Β· πŸ’€) - python partial dependence plot toolbox. MIT +
joypy (πŸ₯‰23 Β· ⭐ 400) - Joyplots in Python with matplotlib & pandas. MIT -- [GitHub](https://github.com/SauceCat/PDPbox) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 100 Β· πŸ“¦ 470 Β· πŸ“‹ 58 - 34% open Β· ⏱️ 14.03.2021): +- [GitHub](https://github.com/leotac/joypy) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 44 Β· πŸ“¦ 120 Β· πŸ“‹ 48 - 22% open Β· ⏱️ 19.12.2021): ``` - git clone https://github.com/SauceCat/PDPbox + git clone https://github.com/leotac/joypy ``` -- [PyPi](https://pypi.org/project/pdpbox) (πŸ“₯ 52K / month Β· πŸ“¦ 25 Β· ⏱️ 14.03.2021): +- [PyPi](https://pypi.org/project/joypy) (πŸ“₯ 36K / month Β· πŸ“¦ 5 Β· ⏱️ 19.12.2021): ``` - pip install pdpbox + pip install joypy ``` -- [Conda](https://anaconda.org/conda-forge/pdpbox) (πŸ“₯ 10K Β· ⏱️ 14.03.2021): +- [Conda](https://anaconda.org/conda-forge/joypy) (πŸ“₯ 12K Β· ⏱️ 28.12.2020): ``` - conda install -c conda-forge pdpbox + conda install -c conda-forge joypy ```
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python-ternary (πŸ₯‰22 Β· ⭐ 510) - Ternary plotting library for python with matplotlib. MIT +
Sweetviz (πŸ₯‰22 Β· ⭐ 1.9K Β· πŸ’€) - Visualize and compare datasets, target values and associations, with.. MIT -- [GitHub](https://github.com/marcharper/python-ternary) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 130 Β· πŸ“₯ 17 Β· πŸ“¦ 81 Β· πŸ“‹ 120 - 21% open Β· ⏱️ 21.10.2021): +- [GitHub](https://github.com/fbdesignpro/sweetviz) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 190 Β· πŸ“‹ 97 - 27% open Β· ⏱️ 08.07.2021): ``` - git clone https://github.com/marcharper/python-ternary + git clone https://github.com/fbdesignpro/sweetviz ``` -- [PyPi](https://pypi.org/project/python-ternary) (πŸ“₯ 15K / month Β· πŸ“¦ 21 Β· ⏱️ 17.02.2021): +- [PyPi](https://pypi.org/project/sweetviz) (πŸ“₯ 66K / month Β· πŸ“¦ 5 Β· ⏱️ 08.07.2021): ``` - pip install python-ternary + pip install sweetviz ``` -- [Conda](https://anaconda.org/conda-forge/python-ternary) (πŸ“₯ 61K Β· ⏱️ 17.02.2021): +- [Conda](https://anaconda.org/conda-forge/sweetviz) (πŸ“₯ 8.6K Β· ⏱️ 09.07.2021): ``` - conda install -c conda-forge python-ternary + conda install -c conda-forge sweetviz ```
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Sweetviz (πŸ₯‰21 Β· ⭐ 1.9K) - Visualize and compare datasets, target values and associations, with one.. MIT +
PDPbox (πŸ₯‰22 Β· ⭐ 650 Β· πŸ’€) - python partial dependence plot toolbox. MIT -- [GitHub](https://github.com/fbdesignpro/sweetviz) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 190 Β· πŸ“‹ 97 - 27% open Β· ⏱️ 08.07.2021): +- [GitHub](https://github.com/SauceCat/PDPbox) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 110 Β· πŸ“¦ 470 Β· πŸ“‹ 58 - 34% open Β· ⏱️ 14.03.2021): ``` - git clone https://github.com/fbdesignpro/sweetviz + git clone https://github.com/SauceCat/PDPbox ``` -- [PyPi](https://pypi.org/project/sweetviz) (πŸ“₯ 52K / month Β· πŸ“¦ 5 Β· ⏱️ 08.07.2021): +- [PyPi](https://pypi.org/project/pdpbox) (πŸ“₯ 58K / month Β· πŸ“¦ 25 Β· ⏱️ 14.03.2021): ``` - pip install sweetviz + pip install pdpbox + ``` +- [Conda](https://anaconda.org/conda-forge/pdpbox) (πŸ“₯ 11K Β· ⏱️ 14.03.2021): + ``` + conda install -c conda-forge pdpbox ```
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PyWaffle (πŸ₯‰21 Β· ⭐ 460) - Make Waffle Charts in Python. MIT +
PyWaffle (πŸ₯‰21 Β· ⭐ 470) - Make Waffle Charts in Python. MIT -- [GitHub](https://github.com/gyli/PyWaffle) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 80 Β· πŸ“¦ 110 Β· πŸ“‹ 15 - 20% open Β· ⏱️ 21.12.2021): +- [GitHub](https://github.com/gyli/PyWaffle) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 81 Β· πŸ“¦ 110 Β· πŸ“‹ 16 - 25% open Β· ⏱️ 21.12.2021): ``` git clone https://github.com/gyli/PyWaffle ``` -- [PyPi](https://pypi.org/project/pywaffle) (πŸ“₯ 2.4K / month Β· πŸ“¦ 1 Β· ⏱️ 21.12.2021): +- [PyPi](https://pypi.org/project/pywaffle) (πŸ“₯ 2.9K / month Β· πŸ“¦ 1 Β· ⏱️ 21.12.2021): ``` pip install pywaffle ``` +- [Conda](https://anaconda.org/conda-forge/pywaffle) (πŸ“₯ 4.2K Β· ⏱️ 22.12.2021): + ``` + conda install -c conda-forge pywaffle + ```
Show 11 hidden projects... -- plotnine (πŸ₯ˆ31 Β· ⭐ 2.9K) - A grammar of graphics for Python. ❗️GPL-2.0 -- cartopy (πŸ₯ˆ31 Β· ⭐ 980) - Cartopy - a cartographic python library with matplotlib support. ❗️LGPL-3.0 -- PandasGUI (πŸ₯‰25 Β· ⭐ 2.5K) - A GUI for Pandas DataFrames. ❗️MIT-0 +- cartopy (πŸ₯ˆ32 Β· ⭐ 990) - Cartopy - a cartographic python library with matplotlib support. ❗️LGPL-3.0 +- plotnine (πŸ₯ˆ30 Β· ⭐ 2.9K) - A grammar of graphics for Python. ❗️GPL-2.0 - Multicore-TSNE (πŸ₯‰24 Β· ⭐ 1.7K Β· πŸ’€) - Parallel t-SNE implementation with Python and Torch.. BSD-3 -- pivottablejs (πŸ₯‰22 Β· ⭐ 450 Β· πŸ’€) - Dragndrop Pivot Tables and Charts for Jupyter/IPython.. MIT -- ivis (πŸ₯‰19 Β· ⭐ 250) - Dimensionality reduction in very large datasets using Siamese.. Apache-2 +- PandasGUI (πŸ₯‰23 Β· ⭐ 2.6K) - A GUI for Pandas DataFrames. ❗️MIT-0 +- pivottablejs (πŸ₯‰23 Β· ⭐ 460 Β· πŸ’€) - Dragndrop Pivot Tables and Charts for Jupyter/IPython.. MIT +- ivis (πŸ₯‰18 Β· ⭐ 260) - Dimensionality reduction in very large datasets using Siamese.. Apache-2 - animatplot (πŸ₯‰17 Β· ⭐ 390 Β· πŸ’€) - A python package for animating plots build on matplotlib. MIT - nx-altair (πŸ₯‰17 Β· ⭐ 190 Β· πŸ’€) - Draw interactive NetworkX graphs with Altair. MIT - pdvega (πŸ₯‰16 Β· ⭐ 340 Β· πŸ’€) - Interactive plotting for Pandas using Vega-Lite. MIT @@ -1322,30 +1358,30 @@ _General-purpose and task-specific data visualization libraries._ _Libraries for processing, cleaning, manipulating, and analyzing text data as well as libraries for NLP tasks such as language detection, fuzzy matching, classification, seq2seq learning, conversational AI, keyword extraction, and translation._ -
transformers (πŸ₯‡47 Β· ⭐ 57K) - Transformers: State-of-the-art Machine Learning for.. Apache-2 +
transformers (πŸ₯‡48 Β· ⭐ 58K) - Transformers: State-of-the-art Machine Learning for.. Apache-2 -- [GitHub](https://github.com/huggingface/transformers) (πŸ‘¨β€πŸ’» 1.1K Β· πŸ”€ 13K Β· πŸ“₯ 1.4K Β· πŸ“¦ 21K Β· πŸ“‹ 8.6K - 4% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/huggingface/transformers) (πŸ‘¨β€πŸ’» 1.1K Β· πŸ”€ 14K Β· πŸ“₯ 1.4K Β· πŸ“¦ 22K Β· πŸ“‹ 8.8K - 5% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/huggingface/transformers ``` -- [PyPi](https://pypi.org/project/transformers) (πŸ“₯ 2.8M / month Β· πŸ“¦ 720 Β· ⏱️ 22.12.2021): +- [PyPi](https://pypi.org/project/transformers) (πŸ“₯ 3.5M / month Β· πŸ“¦ 760 Β· ⏱️ 31.01.2022): ``` pip install transformers ``` -- [Conda](https://anaconda.org/conda-forge/transformers) (πŸ“₯ 90K Β· ⏱️ 23.12.2021): +- [Conda](https://anaconda.org/conda-forge/transformers) (πŸ“₯ 95K Β· ⏱️ 31.01.2022): ``` conda install -c conda-forge transformers ```
nltk (πŸ₯‡45 Β· ⭐ 10K) - Suite of libraries and programs for symbolic and statistical natural.. Apache-2 -- [GitHub](https://github.com/nltk/nltk) (πŸ‘¨β€πŸ’» 410 Β· πŸ”€ 2.5K Β· πŸ“¦ 130K Β· πŸ“‹ 1.6K - 13% open Β· ⏱️ 11.01.2022): +- [GitHub](https://github.com/nltk/nltk) (πŸ‘¨β€πŸ’» 410 Β· πŸ”€ 2.5K Β· πŸ“¦ 130K Β· πŸ“‹ 1.6K - 13% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/nltk/nltk ``` -- [PyPi](https://pypi.org/project/nltk) (πŸ“₯ 9.3M / month Β· πŸ“¦ 12K Β· ⏱️ 28.12.2021): +- [PyPi](https://pypi.org/project/nltk) (πŸ“₯ 11M / month Β· πŸ“¦ 12K Β· ⏱️ 09.02.2022): ``` pip install nltk ``` @@ -1356,83 +1392,95 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we
spaCy (πŸ₯‡44 Β· ⭐ 22K) - Industrial-strength Natural Language Processing (NLP) in Python. MIT -- [GitHub](https://github.com/explosion/spaCy) (πŸ‘¨β€πŸ’» 640 Β· πŸ”€ 3.7K Β· πŸ“₯ 3.1K Β· πŸ“¦ 34K Β· πŸ“‹ 5K - 2% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/explosion/spaCy) (πŸ‘¨β€πŸ’» 650 Β· πŸ”€ 3.7K Β· πŸ“₯ 3.1K Β· πŸ“¦ 35K Β· πŸ“‹ 5K - 2% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/explosion/spaCy ``` -- [PyPi](https://pypi.org/project/spacy) (πŸ“₯ 4M / month Β· πŸ“¦ 2.2K Β· ⏱️ 15.12.2021): +- [PyPi](https://pypi.org/project/spacy) (πŸ“₯ 3.9M / month Β· πŸ“¦ 2.2K Β· ⏱️ 15.12.2021): ``` pip install spacy ``` -- [Conda](https://anaconda.org/conda-forge/spacy) (πŸ“₯ 2.5M Β· ⏱️ 14.12.2021): +- [Conda](https://anaconda.org/conda-forge/spacy) (πŸ“₯ 2.5M Β· ⏱️ 14.01.2022): ``` conda install -c conda-forge spacy ```
gensim (πŸ₯‡41 Β· ⭐ 13K) - Topic Modelling for Humans. ❗️LGPL-2.1 -- [GitHub](https://github.com/RaRe-Technologies/gensim) (πŸ‘¨β€πŸ’» 420 Β· πŸ”€ 4.1K Β· πŸ“₯ 3.5K Β· πŸ“¦ 30K Β· πŸ“‹ 1.7K - 21% open Β· ⏱️ 24.12.2021): +- [GitHub](https://github.com/RaRe-Technologies/gensim) (πŸ‘¨β€πŸ’» 420 Β· πŸ”€ 4.1K Β· πŸ“₯ 3.5K Β· πŸ“¦ 30K Β· πŸ“‹ 1.7K - 21% open Β· ⏱️ 25.01.2022): ``` git clone https://github.com/RaRe-Technologies/gensim ``` -- [PyPi](https://pypi.org/project/gensim) (πŸ“₯ 10M / month Β· πŸ“¦ 2.8K Β· ⏱️ 17.09.2021): +- [PyPi](https://pypi.org/project/gensim) (πŸ“₯ 9.6M / month Β· πŸ“¦ 2.8K Β· ⏱️ 17.09.2021): ``` pip install gensim ``` -- [Conda](https://anaconda.org/conda-forge/gensim) (πŸ“₯ 760K Β· ⏱️ 09.11.2021): +- [Conda](https://anaconda.org/conda-forge/gensim) (πŸ“₯ 770K Β· ⏱️ 09.11.2021): ``` conda install -c conda-forge gensim ```
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Rasa (πŸ₯‡39 Β· ⭐ 13K Β· πŸ“‰) - Open source machine learning framework to automate text- and.. Apache-2 +
Rasa (πŸ₯‡39 Β· ⭐ 14K) - Open source machine learning framework to automate text- and voice-.. Apache-2 -- [GitHub](https://github.com/RasaHQ/rasa) (πŸ‘¨β€πŸ’» 520 Β· πŸ”€ 3.9K Β· πŸ“‹ 6.5K - 15% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/RasaHQ/rasa) (πŸ‘¨β€πŸ’» 530 Β· πŸ”€ 3.9K Β· πŸ“‹ 6.5K - 14% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/RasaHQ/rasa ``` -- [PyPi](https://pypi.org/project/rasa) (πŸ“₯ 210K / month Β· πŸ“¦ 56 Β· ⏱️ 23.12.2021): +- [PyPi](https://pypi.org/project/rasa) (πŸ“₯ 230K / month Β· πŸ“¦ 57 Β· ⏱️ 28.01.2022): ``` pip install rasa ```
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flair (πŸ₯‡38 Β· ⭐ 11K) - A very simple framework for state-of-the-art Natural Language Processing.. MIT +
flair (πŸ₯‡39 Β· ⭐ 11K) - A very simple framework for state-of-the-art Natural Language Processing.. MIT -- [GitHub](https://github.com/flairNLP/flair) (πŸ‘¨β€πŸ’» 220 Β· πŸ”€ 1.8K Β· πŸ“¦ 1.1K Β· πŸ“‹ 1.7K - 5% open Β· ⏱️ 05.01.2022): +- [GitHub](https://github.com/flairNLP/flair) (πŸ‘¨β€πŸ’» 220 Β· πŸ”€ 1.8K Β· πŸ“¦ 1.2K Β· πŸ“‹ 1.8K - 5% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/flairNLP/flair ``` -- [PyPi](https://pypi.org/project/flair) (πŸ“₯ 58K / month Β· πŸ“¦ 66 Β· ⏱️ 18.11.2021): +- [PyPi](https://pypi.org/project/flair) (πŸ“₯ 76K / month Β· πŸ“¦ 66 Β· ⏱️ 18.11.2021): ``` pip install flair ``` +- [Conda](https://anaconda.org/conda-forge/python-flair) (πŸ“₯ 6.7K Β· ⏱️ 18.11.2021): + ``` + conda install -c conda-forge python-flair + ```
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AllenNLP (πŸ₯‡37 Β· ⭐ 11K) - An open-source NLP research library, built on PyTorch. Apache-2 +
AllenNLP (πŸ₯‡38 Β· ⭐ 11K) - An open-source NLP research library, built on PyTorch. Apache-2 -- [GitHub](https://github.com/allenai/allennlp) (πŸ‘¨β€πŸ’» 260 Β· πŸ”€ 2.2K Β· πŸ“₯ 43 Β· πŸ“¦ 2.2K Β· πŸ“‹ 2.5K - 4% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/allenai/allennlp) (πŸ‘¨β€πŸ’» 260 Β· πŸ”€ 2.2K Β· πŸ“₯ 44 Β· πŸ“¦ 2.2K Β· πŸ“‹ 2.5K - 4% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/allenai/allennlp ``` -- [PyPi](https://pypi.org/project/allennlp) (πŸ“₯ 30K / month Β· πŸ“¦ 180 Β· ⏱️ 13.01.2022): +- [PyPi](https://pypi.org/project/allennlp) (πŸ“₯ 37K / month Β· πŸ“¦ 180 Β· ⏱️ 27.01.2022): ``` pip install allennlp ``` +- [Conda](https://anaconda.org/conda-forge/allennlp) (πŸ“₯ 40K Β· ⏱️ 06.02.2022): + ``` + conda install -c conda-forge allennlp + ```
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fairseq (πŸ₯‡36 Β· ⭐ 15K) - Facebook AI Research Sequence-to-Sequence Toolkit written in Python. MIT +
fairseq (πŸ₯‡36 Β· ⭐ 16K) - Facebook AI Research Sequence-to-Sequence Toolkit written in Python. MIT -- [GitHub](https://github.com/pytorch/fairseq) (πŸ‘¨β€πŸ’» 370 Β· πŸ”€ 3.8K Β· πŸ“₯ 160 Β· πŸ“¦ 630 Β· πŸ“‹ 3.1K - 35% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/pytorch/fairseq) (πŸ‘¨β€πŸ’» 370 Β· πŸ”€ 4K Β· πŸ“₯ 170 Β· πŸ“¦ 650 Β· πŸ“‹ 3.2K - 36% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/pytorch/fairseq ``` -- [PyPi](https://pypi.org/project/fairseq) (πŸ“₯ 27K / month Β· πŸ“¦ 28 Β· ⏱️ 05.01.2021): +- [PyPi](https://pypi.org/project/fairseq) (πŸ“₯ 35K / month Β· πŸ“¦ 28 Β· ⏱️ 05.01.2021): ``` pip install fairseq ``` +- [Conda](https://anaconda.org/conda-forge/fairseq) (πŸ“₯ 13K Β· ⏱️ 28.04.2021): + ``` + conda install -c conda-forge fairseq + ```
ChatterBot (πŸ₯‡35 Β· ⭐ 12K Β· πŸ’€) - ChatterBot is a machine learning, conversational dialog engine.. BSD-3 @@ -1441,31 +1489,31 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we ``` git clone https://github.com/gunthercox/ChatterBot ``` -- [PyPi](https://pypi.org/project/chatterbot) (πŸ“₯ 28K / month Β· πŸ“¦ 350 Β· ⏱️ 22.08.2020): +- [PyPi](https://pypi.org/project/chatterbot) (πŸ“₯ 31K / month Β· πŸ“¦ 350 Β· ⏱️ 22.08.2020): ``` pip install chatterbot ```
ParlAI (πŸ₯‡35 Β· ⭐ 8.6K) - A framework for training and evaluating AI models on a variety of.. MIT -- [GitHub](https://github.com/facebookresearch/ParlAI) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 1.7K Β· πŸ“¦ 57 Β· πŸ“‹ 1.2K - 7% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/facebookresearch/ParlAI) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 1.7K Β· πŸ“¦ 59 Β· πŸ“‹ 1.2K - 7% open Β· ⏱️ 08.02.2022): ``` git clone https://github.com/facebookresearch/ParlAI ``` -- [PyPi](https://pypi.org/project/parlai) (πŸ“₯ 2.4K / month Β· πŸ“¦ 3 Β· ⏱️ 12.10.2021): +- [PyPi](https://pypi.org/project/parlai) (πŸ“₯ 6.8K / month Β· πŸ“¦ 3 Β· ⏱️ 12.10.2021): ``` pip install parlai ```
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TextBlob (πŸ₯ˆ34 Β· ⭐ 8K) - Simple, Pythonic, text processing--Sentiment analysis, part-of-speech.. MIT +
TextBlob (πŸ₯‡35 Β· ⭐ 8K) - Simple, Pythonic, text processing--Sentiment analysis, part-of-speech.. MIT - [GitHub](https://github.com/sloria/TextBlob) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 1.1K Β· πŸ“₯ 97 Β· πŸ“¦ 17K Β· πŸ“‹ 260 - 39% open Β· ⏱️ 22.10.2021): ``` git clone https://github.com/sloria/TextBlob ``` -- [PyPi](https://pypi.org/project/textblob) (πŸ“₯ 750K / month Β· πŸ“¦ 1.4K Β· ⏱️ 15.12.2021): +- [PyPi](https://pypi.org/project/textblob) (πŸ“₯ 1.1M / month Β· πŸ“¦ 1.4K Β· ⏱️ 15.12.2021): ``` pip install textblob ``` @@ -1474,122 +1522,114 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge textblob ```
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sentence-transformers (πŸ₯ˆ34 Β· ⭐ 6.8K) - Multilingual Sentence & Image Embeddings with BERT. Apache-2 +
sentence-transformers (πŸ₯ˆ34 Β· ⭐ 7K) - Multilingual Sentence & Image Embeddings with BERT. Apache-2 -- [GitHub](https://github.com/UKPLab/sentence-transformers) (πŸ‘¨β€πŸ’» 70 Β· πŸ”€ 1.3K Β· πŸ“¦ 2.2K Β· πŸ“‹ 1.2K - 49% open Β· ⏱️ 06.01.2022): +- [GitHub](https://github.com/UKPLab/sentence-transformers) (πŸ‘¨β€πŸ’» 73 Β· πŸ”€ 1.4K Β· πŸ“¦ 2.4K Β· πŸ“‹ 1.3K - 50% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/UKPLab/sentence-transformers ``` -- [PyPi](https://pypi.org/project/sentence-transformers) (πŸ“₯ 530K / month Β· πŸ“¦ 80 Β· ⏱️ 01.10.2021): +- [PyPi](https://pypi.org/project/sentence-transformers) (πŸ“₯ 780K / month Β· πŸ“¦ 80 Β· ⏱️ 01.10.2021): ``` pip install sentence-transformers ``` +- [Conda](https://anaconda.org/conda-forge/sentence-transformers) (πŸ“₯ 14K Β· ⏱️ 30.11.2021): + ``` + conda install -c conda-forge sentence-transformers + ```
spark-nlp (πŸ₯ˆ34 Β· ⭐ 2.6K) - State of the Art Natural Language Processing. Apache-2 -- [GitHub](https://github.com/JohnSnowLabs/spark-nlp) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 530 Β· πŸ“‹ 610 - 14% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/JohnSnowLabs/spark-nlp) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 530 Β· πŸ“‹ 620 - 13% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/JohnSnowLabs/spark-nlp ``` -- [PyPi](https://pypi.org/project/spark-nlp) (πŸ“₯ 1.4M / month Β· πŸ“¦ 8 Β· ⏱️ 05.01.2022): +- [PyPi](https://pypi.org/project/spark-nlp) (πŸ“₯ 1.4M / month Β· πŸ“¦ 9 Β· ⏱️ 08.02.2022): ``` pip install spark-nlp ```
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sentencepiece (πŸ₯ˆ33 Β· ⭐ 5.6K Β· πŸ“ˆ) - Unsupervised text tokenizer for Neural Network-based.. Apache-2 +
sentencepiece (πŸ₯ˆ33 Β· ⭐ 5.7K Β· πŸ’€) - Unsupervised text tokenizer for Neural Network-based.. Apache-2 -- [GitHub](https://github.com/google/sentencepiece) (πŸ‘¨β€πŸ’» 57 Β· πŸ”€ 740 Β· πŸ“₯ 19K Β· πŸ“¦ 12K Β· πŸ“‹ 490 - 9% open Β· ⏱️ 02.07.2021): +- [GitHub](https://github.com/google/sentencepiece) (πŸ‘¨β€πŸ’» 57 Β· πŸ”€ 790 Β· πŸ“₯ 20K Β· πŸ“¦ 13K Β· πŸ“‹ 500 - 11% open Β· ⏱️ 02.07.2021): ``` git clone https://github.com/google/sentencepiece ``` -- [PyPi](https://pypi.org/project/sentencepiece) (πŸ“₯ 3.4M / month Β· πŸ“¦ 280 Β· ⏱️ 18.06.2021): +- [PyPi](https://pypi.org/project/sentencepiece) (πŸ“₯ 4.3M / month Β· πŸ“¦ 350 Β· ⏱️ 18.06.2021): ``` pip install sentencepiece ``` -- [Conda](https://anaconda.org/conda-forge/sentencepiece) (πŸ“₯ 140K Β· ⏱️ 05.11.2021): +- [Conda](https://anaconda.org/conda-forge/sentencepiece) (πŸ“₯ 150K Β· ⏱️ 07.02.2022): ``` conda install -c conda-forge sentencepiece ```
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OpenNMT (πŸ₯ˆ33 Β· ⭐ 5.4K Β· πŸ“ˆ) - Open Source Neural Machine Translation in PyTorch. MIT +
OpenNMT (πŸ₯ˆ33 Β· ⭐ 5.4K) - Open Source Neural Machine Translation in PyTorch. MIT -- [GitHub](https://github.com/OpenNMT/OpenNMT-py) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 2K Β· πŸ“¦ 120 Β· πŸ“‹ 1.3K - 9% open Β· ⏱️ 11.01.2022): +- [GitHub](https://github.com/OpenNMT/OpenNMT-py) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 2K Β· πŸ“¦ 120 Β· πŸ“‹ 1.3K - 9% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/OpenNMT/OpenNMT-py ``` -- [PyPi](https://pypi.org/project/OpenNMT-py) (πŸ“₯ 15K / month Β· πŸ“¦ 8 Β· ⏱️ 14.09.2021): +- [PyPi](https://pypi.org/project/OpenNMT-py) (πŸ“₯ 20K / month Β· πŸ“¦ 8 Β· ⏱️ 14.09.2021): ``` pip install OpenNMT-py ```
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Tokenizers (πŸ₯ˆ33 Β· ⭐ 5.1K) - Fast State-of-the-Art Tokenizers optimized for Research and.. Apache-2 +
Tokenizers (πŸ₯ˆ33 Β· ⭐ 5.2K) - Fast State-of-the-Art Tokenizers optimized for Research and.. Apache-2 -- [GitHub](https://github.com/huggingface/tokenizers) (πŸ‘¨β€πŸ’» 50 Β· πŸ”€ 420 Β· πŸ“¦ 40 Β· πŸ“‹ 560 - 28% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/huggingface/tokenizers) (πŸ‘¨β€πŸ’» 50 Β· πŸ”€ 430 Β· πŸ“¦ 40 Β· πŸ“‹ 560 - 27% open Β· ⏱️ 28.01.2022): ``` git clone https://github.com/huggingface/tokenizers ``` -- [PyPi](https://pypi.org/project/tokenizers) (πŸ“₯ 3.6M / month Β· πŸ“¦ 93 Β· ⏱️ 04.01.2022): +- [PyPi](https://pypi.org/project/tokenizers) (πŸ“₯ 4.4M / month Β· πŸ“¦ 93 Β· ⏱️ 17.01.2022): ``` pip install tokenizers ``` -- [Conda](https://anaconda.org/conda-forge/tokenizers) (πŸ“₯ 110K Β· ⏱️ 05.01.2022): +- [Conda](https://anaconda.org/conda-forge/tokenizers) (πŸ“₯ 110K Β· ⏱️ 18.01.2022): ``` conda install -c conda-forge tokenizers ```
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torchtext (πŸ₯ˆ33 Β· ⭐ 2.9K) - Data loaders and abstractions for text and NLP. BSD-3 +
Dedupe (πŸ₯ˆ33 Β· ⭐ 3.3K) - A python library for accurate and scalable fuzzy matching, record.. MIT -- [GitHub](https://github.com/pytorch/text) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 680 Β· πŸ“‹ 680 - 50% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/dedupeio/dedupe) (πŸ‘¨β€πŸ’» 63 Β· πŸ”€ 460 Β· πŸ“¦ 210 Β· πŸ“‹ 680 - 4% open Β· ⏱️ 08.02.2022): ``` - git clone https://github.com/pytorch/text - ``` -- [PyPi](https://pypi.org/project/torchtext) (πŸ“₯ 110K / month Β· πŸ“¦ 430 Β· ⏱️ 15.12.2021): - ``` - pip install torchtext + git clone https://github.com/dedupeio/dedupe ``` -
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TensorFlow Text (πŸ₯ˆ32 Β· ⭐ 880) - Making text a first-class citizen in TensorFlow. Apache-2 - -- [GitHub](https://github.com/tensorflow/text) (πŸ‘¨β€πŸ’» 67 Β· πŸ”€ 170 Β· πŸ“¦ 1.3K Β· πŸ“‹ 180 - 31% open Β· ⏱️ 06.01.2022): - +- [PyPi](https://pypi.org/project/dedupe) (πŸ“₯ 280K / month Β· πŸ“¦ 47 Β· ⏱️ 03.02.2022): ``` - git clone https://github.com/tensorflow/text + pip install dedupe ``` -- [PyPi](https://pypi.org/project/tensorflow-text) (πŸ“₯ 1.5M / month Β· πŸ“¦ 66 Β· ⏱️ 19.11.2021): +- [Conda](https://anaconda.org/conda-forge/dedupe) (πŸ“₯ 1.2K Β· ⏱️ 04.02.2022): ``` - pip install tensorflow-text + conda install -c conda-forge dedupe ```
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snowballstemmer (πŸ₯ˆ32 Β· ⭐ 540 Β· πŸ“‰) - Snowball compiler and stemming algorithms. BSD-3 +
torchtext (πŸ₯ˆ33 Β· ⭐ 2.9K) - Data loaders and abstractions for text and NLP. BSD-3 -- [GitHub](https://github.com/snowballstem/snowball) (πŸ‘¨β€πŸ’» 28 Β· πŸ”€ 150 Β· πŸ“¦ 4 Β· πŸ“‹ 69 - 36% open Β· ⏱️ 17.12.2021): +- [GitHub](https://github.com/pytorch/text) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 680 Β· πŸ“‹ 690 - 47% open Β· ⏱️ 09.02.2022): ``` - git clone https://github.com/snowballstem/snowball - ``` -- [PyPi](https://pypi.org/project/snowballstemmer) (πŸ“₯ 4.9M / month Β· πŸ“¦ 6.7K Β· ⏱️ 16.11.2021): - ``` - pip install snowballstemmer + git clone https://github.com/pytorch/text ``` -- [Conda](https://anaconda.org/conda-forge/snowballstemmer) (πŸ“₯ 3.6M Β· ⏱️ 17.11.2021): +- [PyPi](https://pypi.org/project/torchtext) (πŸ“₯ 140K / month Β· πŸ“¦ 430 Β· ⏱️ 27.01.2022): ``` - conda install -c conda-forge snowballstemmer + pip install torchtext ```
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stanza (πŸ₯ˆ31 Β· ⭐ 5.9K) - Official Stanford NLP Python Library for Many Human Languages. Apache-2 +
stanza (πŸ₯ˆ32 Β· ⭐ 6K) - Official Stanford NLP Python Library for Many Human Languages. Apache-2 -- [GitHub](https://github.com/stanfordnlp/stanza) (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 750 Β· πŸ“¦ 810 Β· πŸ“‹ 620 - 11% open Β· ⏱️ 18.11.2021): +- [GitHub](https://github.com/stanfordnlp/stanza) (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 750 Β· πŸ“¦ 840 Β· πŸ“‹ 640 - 10% open Β· ⏱️ 26.01.2022): ``` git clone https://github.com/stanfordnlp/stanza ``` -- [PyPi](https://pypi.org/project/stanza) (πŸ“₯ 310K / month Β· πŸ“¦ 49 Β· ⏱️ 05.10.2021): +- [PyPi](https://pypi.org/project/stanza) (πŸ“₯ 380K / month Β· πŸ“¦ 49 Β· ⏱️ 05.10.2021): ``` pip install stanza ``` @@ -1598,54 +1638,46 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c stanfordnlp stanza ```
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DeepPavlov (πŸ₯ˆ31 Β· ⭐ 5.6K) - An open source library for deep learning end-to-end dialog.. Apache-2 +
ftfy (πŸ₯ˆ31 Β· ⭐ 3.2K) - Fixes mojibake and other glitches in Unicode text, after the fact. MIT -- [GitHub](https://github.com/deepmipt/DeepPavlov) (πŸ‘¨β€πŸ’» 67 Β· πŸ”€ 990 Β· πŸ“¦ 240 Β· πŸ“‹ 610 - 18% open Β· ⏱️ 16.12.2021): +- [GitHub](https://github.com/rspeer/python-ftfy) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 110 Β· πŸ“¦ 4.8K Β· πŸ“‹ 130 - 7% open Β· ⏱️ 09.02.2022): ``` - git clone https://github.com/deepmipt/DeepPavlov - ``` -- [PyPi](https://pypi.org/project/deeppavlov) (πŸ“₯ 9.6K / month Β· πŸ“¦ 6 Β· ⏱️ 16.12.2021): - ``` - pip install deeppavlov + git clone https://github.com/rspeer/python-ftfy ``` -
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Dedupe (πŸ₯ˆ31 Β· ⭐ 3.3K) - A python library for accurate and scalable fuzzy matching, record.. MIT - -- [GitHub](https://github.com/dedupeio/dedupe) (πŸ‘¨β€πŸ’» 62 Β· πŸ”€ 450 Β· πŸ“¦ 210 Β· πŸ“‹ 670 - 9% open Β· ⏱️ 09.01.2022): - +- [PyPi](https://pypi.org/project/ftfy) (πŸ“₯ 1.5M / month Β· πŸ“¦ 490 Β· ⏱️ 09.02.2022): ``` - git clone https://github.com/dedupeio/dedupe + pip install ftfy ``` -- [PyPi](https://pypi.org/project/dedupe) (πŸ“₯ 250K / month Β· πŸ“¦ 47 Β· ⏱️ 17.04.2021): +- [Conda](https://anaconda.org/conda-forge/ftfy) (πŸ“₯ 140K Β· ⏱️ 25.05.2021): ``` - pip install dedupe + conda install -c conda-forge ftfy ```
textacy (πŸ₯ˆ31 Β· ⭐ 1.9K) - NLP, before and after spaCy. Apache-2 -- [GitHub](https://github.com/chartbeat-labs/textacy) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 230 Β· πŸ“‹ 240 - 10% open Β· ⏱️ 06.12.2021): +- [GitHub](https://github.com/chartbeat-labs/textacy) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 230 Β· πŸ“‹ 250 - 10% open Β· ⏱️ 06.12.2021): ``` git clone https://github.com/chartbeat-labs/textacy ``` -- [PyPi](https://pypi.org/project/textacy) (πŸ“₯ 25K / month Β· πŸ“¦ 100 Β· ⏱️ 06.12.2021): +- [PyPi](https://pypi.org/project/textacy) (πŸ“₯ 45K / month Β· πŸ“¦ 100 Β· ⏱️ 06.12.2021): ``` pip install textacy ``` -- [Conda](https://anaconda.org/conda-forge/textacy) (πŸ“₯ 100K Β· ⏱️ 13.04.2021): +- [Conda](https://anaconda.org/conda-forge/textacy) (πŸ“₯ 100K Β· ⏱️ 06.02.2022): ``` conda install -c conda-forge textacy ```
jellyfish (πŸ₯ˆ31 Β· ⭐ 1.6K) - a python library for doing approximate and phonetic matching of.. BSD-2 -- [GitHub](https://github.com/jamesturk/jellyfish) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 150 Β· πŸ“¦ 3.1K Β· πŸ“‹ 110 - 7% open Β· ⏱️ 07.01.2022): +- [GitHub](https://github.com/jamesturk/jellyfish) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 150 Β· πŸ“¦ 3.2K Β· πŸ“‹ 110 - 8% open Β· ⏱️ 07.01.2022): ``` git clone https://github.com/jamesturk/jellyfish ``` -- [PyPi](https://pypi.org/project/jellyfish) (πŸ“₯ 1.6M / month Β· πŸ“¦ 400 Β· ⏱️ 07.01.2022): +- [PyPi](https://pypi.org/project/jellyfish) (πŸ“₯ 1.8M / month Β· πŸ“¦ 400 Β· ⏱️ 07.01.2022): ``` pip install jellyfish ``` @@ -1654,264 +1686,316 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge jellyfish ```
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nlpaug (πŸ₯ˆ30 Β· ⭐ 2.8K) - Data augmentation for NLP. MIT +
TensorFlow Text (πŸ₯ˆ31 Β· ⭐ 890) - Making text a first-class citizen in TensorFlow. Apache-2 -- [GitHub](https://github.com/makcedward/nlpaug) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 320 Β· πŸ“¦ 230 Β· πŸ“‹ 160 - 14% open Β· ⏱️ 04.01.2022): +- [GitHub](https://github.com/tensorflow/text) (πŸ‘¨β€πŸ’» 73 Β· πŸ”€ 180 Β· πŸ“¦ 1.4K Β· πŸ“‹ 190 - 35% open Β· ⏱️ 06.02.2022): ``` - git clone https://github.com/makcedward/nlpaug + git clone https://github.com/tensorflow/text ``` -- [PyPi](https://pypi.org/project/nlpaug) (πŸ“₯ 30K / month Β· πŸ“¦ 14 Β· ⏱️ 23.12.2021): +- [PyPi](https://pypi.org/project/tensorflow-text) (πŸ“₯ 2M / month Β· πŸ“¦ 69 Β· ⏱️ 04.02.2022): ``` - pip install nlpaug + pip install tensorflow-text ```
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NeMo (πŸ₯ˆ29 Β· ⭐ 3.8K) - NeMo: a toolkit for conversational AI. Apache-2 +
DeepPavlov (πŸ₯ˆ30 Β· ⭐ 5.6K) - An open source library for deep learning end-to-end dialog.. Apache-2 -- [GitHub](https://github.com/NVIDIA/NeMo) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 850 Β· πŸ“₯ 18K Β· πŸ“‹ 920 - 7% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/deepmipt/DeepPavlov) (πŸ‘¨β€πŸ’» 67 Β· πŸ”€ 990 Β· πŸ“¦ 240 Β· πŸ“‹ 620 - 18% open Β· ⏱️ 16.12.2021): ``` - git clone https://github.com/NVIDIA/NeMo + git clone https://github.com/deepmipt/DeepPavlov ``` -- [PyPi](https://pypi.org/project/nemo-toolkit) (πŸ“₯ 7.8K / month Β· πŸ“¦ 7 Β· ⏱️ 04.12.2021): +- [PyPi](https://pypi.org/project/deeppavlov) (πŸ“₯ 9.5K / month Β· πŸ“¦ 6 Β· ⏱️ 16.12.2021): ``` - pip install nemo-toolkit + pip install deeppavlov ```
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haystack (πŸ₯ˆ29 Β· ⭐ 3.6K) - Haystack is an open source NLP framework that leverages Transformer.. Apache-2 +
NeMo (πŸ₯ˆ30 Β· ⭐ 3.9K) - NeMo: a toolkit for conversational AI. Apache-2 -- [GitHub](https://github.com/deepset-ai/haystack) (πŸ‘¨β€πŸ’» 94 Β· πŸ”€ 610 Β· πŸ“¦ 99 Β· πŸ“‹ 1.1K - 14% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/NVIDIA/NeMo) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 850 Β· πŸ“₯ 4K Β· πŸ“‹ 970 - 7% open Β· ⏱️ 09.02.2022): ``` - git clone https://github.com/deepset-ai/haystack + git clone https://github.com/NVIDIA/NeMo ``` -- [PyPi](https://pypi.org/project/haystack) (πŸ“₯ 1.2K / month Β· πŸ“¦ 85 Β· ⏱️ 15.12.2021): +- [PyPi](https://pypi.org/project/nemo-toolkit) (πŸ“₯ 12K / month Β· πŸ“¦ 7 Β· ⏱️ 05.02.2022): ``` - pip install haystack + pip install nemo-toolkit ```
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ftfy (πŸ₯ˆ29 Β· ⭐ 3.2K Β· πŸ’€) - Fixes mojibake and other glitches in Unicode text, after the fact. MIT +
nlpaug (πŸ₯ˆ30 Β· ⭐ 2.9K) - Data augmentation for NLP. MIT -- [GitHub](https://github.com/rspeer/python-ftfy) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 110 Β· πŸ“¦ 4.6K Β· πŸ“‹ 120 - 9% open Β· ⏱️ 17.05.2021): +- [GitHub](https://github.com/makcedward/nlpaug) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 330 Β· πŸ“¦ 250 Β· πŸ“‹ 170 - 16% open Β· ⏱️ 04.01.2022): ``` - git clone https://github.com/LuminosoInsight/python-ftfy + git clone https://github.com/makcedward/nlpaug ``` -- [PyPi](https://pypi.org/project/ftfy) (πŸ“₯ 1.1M / month Β· πŸ“¦ 480 Β· ⏱️ 24.05.2021): +- [PyPi](https://pypi.org/project/nlpaug) (πŸ“₯ 41K / month Β· πŸ“¦ 14 Β· ⏱️ 23.12.2021): ``` - pip install ftfy + pip install nlpaug ``` -- [Conda](https://anaconda.org/conda-forge/ftfy) (πŸ“₯ 140K Β· ⏱️ 25.05.2021): +- [Conda](https://anaconda.org/conda-forge/nlpaug) (πŸ“₯ 1.2K Β· ⏱️ 25.12.2021): ``` - conda install -c conda-forge ftfy + conda install -c conda-forge nlpaug ```
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Sumy (πŸ₯ˆ29 Β· ⭐ 2.7K) - Module for automatic summarization of text documents and HTML pages. Apache-2 +
snowballstemmer (πŸ₯ˆ30 Β· ⭐ 540 Β· πŸ“‰) - Snowball compiler and stemming algorithms. BSD-3 -- [GitHub](https://github.com/miso-belica/sumy) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 460 Β· πŸ“¦ 1.1K Β· πŸ“‹ 96 - 15% open Β· ⏱️ 23.11.2021): +- [GitHub](https://github.com/snowballstem/snowball) (πŸ‘¨β€πŸ’» 28 Β· πŸ”€ 150 Β· πŸ“¦ 4 Β· πŸ“‹ 69 - 36% open Β· ⏱️ 17.12.2021): ``` - git clone https://github.com/miso-belica/sumy + git clone https://github.com/snowballstem/snowball ``` -- [PyPi](https://pypi.org/project/sumy) (πŸ“₯ 20K / month Β· πŸ“¦ 100 Β· ⏱️ 21.10.2021): +- [PyPi](https://pypi.org/project/snowballstemmer) (πŸ“₯ 6.2M / month Β· πŸ“¦ 6.7K Β· ⏱️ 16.11.2021): ``` - pip install sumy + pip install snowballstemmer + ``` +- [Conda](https://anaconda.org/conda-forge/snowballstemmer) (πŸ“₯ 3.8M Β· ⏱️ 17.11.2021): + ``` + conda install -c conda-forge snowballstemmer ```
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TextDistance (πŸ₯ˆ29 Β· ⭐ 2.6K) - Compute distance between sequences. 30+ algorithms, pure python.. MIT +
GluonNLP (πŸ₯ˆ29 Β· ⭐ 2.4K) - Toolkit that enables easy text preprocessing, datasets loading.. Apache-2 -- [GitHub](https://github.com/life4/textdistance) (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 200 Β· πŸ“₯ 440 Β· πŸ“¦ 1.5K Β· ⏱️ 29.11.2021): +- [GitHub](https://github.com/dmlc/gluon-nlp) (πŸ‘¨β€πŸ’» 82 Β· πŸ”€ 520 Β· πŸ“¦ 710 Β· πŸ“‹ 560 - 46% open Β· ⏱️ 24.08.2021): ``` - git clone https://github.com/life4/textdistance - ``` -- [PyPi](https://pypi.org/project/textdistance) (πŸ“₯ 260K / month Β· πŸ“¦ 39 Β· ⏱️ 27.10.2021): - ``` - pip install textdistance + git clone https://github.com/dmlc/gluon-nlp ``` -- [Conda](https://anaconda.org/conda-forge/textdistance) (πŸ“₯ 69K Β· ⏱️ 27.10.2021): +- [PyPi](https://pypi.org/project/gluonnlp) (πŸ“₯ 99K / month Β· πŸ“¦ 22 Β· ⏱️ 13.08.2020): ``` - conda install -c conda-forge textdistance + pip install gluonnlp ```
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GluonNLP (πŸ₯ˆ29 Β· ⭐ 2.4K) - Toolkit that enables easy text preprocessing, datasets loading.. Apache-2 +
CLTK (πŸ₯ˆ29 Β· ⭐ 710) - The Classical Language Toolkit. MIT -- [GitHub](https://github.com/dmlc/gluon-nlp) (πŸ‘¨β€πŸ’» 82 Β· πŸ”€ 520 Β· πŸ“¦ 690 Β· πŸ“‹ 560 - 46% open Β· ⏱️ 24.08.2021): +- [GitHub](https://github.com/cltk/cltk) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 310 Β· πŸ“₯ 25 Β· πŸ“¦ 190 Β· πŸ“‹ 510 - 4% open Β· ⏱️ 06.02.2022): ``` - git clone https://github.com/dmlc/gluon-nlp + git clone https://github.com/cltk/cltk ``` -- [PyPi](https://pypi.org/project/gluonnlp) (πŸ“₯ 100K / month Β· πŸ“¦ 22 Β· ⏱️ 13.08.2020): +- [PyPi](https://pypi.org/project/cltk) (πŸ“₯ 2.5K / month Β· πŸ“¦ 42 Β· ⏱️ 04.02.2022): ``` - pip install gluonnlp + pip install cltk ```
PyText (πŸ₯ˆ28 Β· ⭐ 6.3K) - A natural language modeling framework based on PyTorch. BSD-3 -- [GitHub](https://github.com/facebookresearch/pytext) (πŸ‘¨β€πŸ’» 220 Β· πŸ”€ 800 Β· πŸ“₯ 280 Β· πŸ“¦ 100 Β· πŸ“‹ 220 - 66% open Β· ⏱️ 09.01.2022): +- [GitHub](https://github.com/facebookresearch/pytext) (πŸ‘¨β€πŸ’» 220 Β· πŸ”€ 800 Β· πŸ“₯ 290 Β· πŸ“¦ 100 Β· πŸ“‹ 220 - 66% open Β· ⏱️ 08.02.2022): ``` git clone https://github.com/facebookresearch/pytext ``` -- [PyPi](https://pypi.org/project/pytext-nlp) (πŸ“₯ 210 / month Β· πŸ“¦ 1 Β· ⏱️ 08.06.2020): +- [PyPi](https://pypi.org/project/pytext-nlp) (πŸ“₯ 280 / month Β· πŸ“¦ 1 Β· ⏱️ 08.06.2020): ``` pip install pytext-nlp ```
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haystack (πŸ₯ˆ28 Β· ⭐ 4.1K) - Haystack is an open source NLP framework that leverages Transformer.. Apache-2 + +- [GitHub](https://github.com/deepset-ai/haystack) (πŸ‘¨β€πŸ’» 97 Β· πŸ”€ 670 Β· πŸ“₯ 3 Β· πŸ“‹ 1.2K - 14% open Β· ⏱️ 10.02.2022): + + ``` + git clone https://github.com/deepset-ai/haystack + ``` +- [PyPi](https://pypi.org/project/haystack) (πŸ“₯ 840 / month Β· πŸ“¦ 85 Β· ⏱️ 15.12.2021): + ``` + pip install haystack + ``` +
T5 (πŸ₯ˆ28 Β· ⭐ 3.9K) - Code for the paper Exploring the Limits of Transfer Learning with a.. Apache-2 -- [GitHub](https://github.com/google-research/text-to-text-transfer-transformer) (πŸ‘¨β€πŸ’» 44 Β· πŸ”€ 530 Β· πŸ“¦ 78 Β· πŸ“‹ 400 - 16% open Β· ⏱️ 11.01.2022): +- [GitHub](https://github.com/google-research/text-to-text-transfer-transformer) (πŸ‘¨β€πŸ’» 44 Β· πŸ”€ 540 Β· πŸ“¦ 82 Β· πŸ“‹ 400 - 16% open Β· ⏱️ 04.02.2022): ``` git clone https://github.com/google-research/text-to-text-transfer-transformer ``` -- [PyPi](https://pypi.org/project/t5) (πŸ“₯ 5.7K / month Β· πŸ“¦ 2 Β· ⏱️ 18.10.2021): +- [PyPi](https://pypi.org/project/t5) (πŸ“₯ 6.1K / month Β· πŸ“¦ 2 Β· ⏱️ 18.10.2021): ``` pip install t5 ```
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CLTK (πŸ₯ˆ28 Β· ⭐ 700) - The Classical Language Toolkit. MIT +
Sumy (πŸ₯ˆ28 Β· ⭐ 2.7K) - Module for automatic summarization of text documents and HTML pages. Apache-2 -- [GitHub](https://github.com/cltk/cltk) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 300 Β· πŸ“₯ 22 Β· πŸ“¦ 190 Β· πŸ“‹ 520 - 5% open Β· ⏱️ 05.01.2022): +- [GitHub](https://github.com/miso-belica/sumy) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 460 Β· πŸ“¦ 1.1K Β· πŸ“‹ 98 - 15% open Β· ⏱️ 23.11.2021): ``` - git clone https://github.com/cltk/cltk + git clone https://github.com/miso-belica/sumy ``` -- [PyPi](https://pypi.org/project/cltk) (πŸ“₯ 1.6K / month Β· πŸ“¦ 42 Β· ⏱️ 05.01.2022): +- [PyPi](https://pypi.org/project/sumy) (πŸ“₯ 26K / month Β· πŸ“¦ 100 Β· ⏱️ 21.10.2021): ``` - pip install cltk + pip install sumy + ``` +- [Conda](https://anaconda.org/conda-forge/sumy) (πŸ“₯ 620 Β· ⏱️ 22.10.2021): + ``` + conda install -c conda-forge sumy ```
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vaderSentiment (πŸ₯‰27 Β· ⭐ 3.3K Β· πŸ’€) - VADER Sentiment Analysis. VADER (Valence Aware Dictionary.. MIT +
TextDistance (πŸ₯ˆ28 Β· ⭐ 2.6K) - Compute distance between sequences. 30+ algorithms, pure python.. MIT -- [GitHub](https://github.com/cjhutto/vaderSentiment) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 830 Β· πŸ“¦ 3.4K Β· πŸ“‹ 110 - 30% open Β· ⏱️ 15.03.2021): +- [GitHub](https://github.com/life4/textdistance) (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 200 Β· πŸ“₯ 460 Β· πŸ“¦ 1.7K Β· ⏱️ 29.11.2021): ``` - git clone https://github.com/cjhutto/vaderSentiment + git clone https://github.com/life4/textdistance ``` -- [PyPi](https://pypi.org/project/vadersentiment) (πŸ“₯ 210K / month Β· πŸ“¦ 170 Β· ⏱️ 22.05.2020): +- [PyPi](https://pypi.org/project/textdistance) (πŸ“₯ 290K / month Β· πŸ“¦ 39 Β· ⏱️ 27.10.2021): ``` - pip install vadersentiment + pip install textdistance + ``` +- [Conda](https://anaconda.org/conda-forge/textdistance) (πŸ“₯ 73K Β· ⏱️ 27.10.2021): + ``` + conda install -c conda-forge textdistance ```
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neuralcoref (πŸ₯‰27 Β· ⭐ 2.5K Β· πŸ’€) - Fast Coreference Resolution in spaCy with Neural Networks. MIT +
PyTextRank (πŸ₯ˆ28 Β· ⭐ 1.7K) - Python implementation of TextRank for phrase extraction and.. MIT -- [GitHub](https://github.com/huggingface/neuralcoref) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 430 Β· πŸ“₯ 300 Β· πŸ“¦ 440 Β· πŸ“‹ 290 - 16% open Β· ⏱️ 22.06.2021): +- [GitHub](https://github.com/DerwenAI/pytextrank) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 320 Β· πŸ“¦ 230 Β· πŸ“‹ 83 - 27% open Β· ⏱️ 04.02.2022): ``` - git clone https://github.com/huggingface/neuralcoref + git clone https://github.com/DerwenAI/pytextrank ``` -- [PyPi](https://pypi.org/project/neuralcoref) (πŸ“₯ 28K / month Β· πŸ“¦ 14 Β· ⏱️ 08.04.2019): +- [PyPi](https://pypi.org/project/pytextrank) (πŸ“₯ 21K / month Β· πŸ“¦ 12 Β· ⏱️ 10.10.2021): ``` - pip install neuralcoref + pip install pytextrank ``` -- [Conda](https://anaconda.org/conda-forge/neuralcoref) (πŸ“₯ 10K Β· ⏱️ 21.02.2020): +
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Ciphey (πŸ₯ˆ27 Β· ⭐ 9.4K) - Automatically decrypt encryptions without knowing the key or cipher,.. MIT + +- [GitHub](https://github.com/Ciphey/Ciphey) (πŸ‘¨β€πŸ’» 46 Β· πŸ”€ 580 Β· πŸ“‹ 290 - 17% open Β· ⏱️ 03.11.2021): + ``` - conda install -c conda-forge neuralcoref + git clone https://github.com/Ciphey/Ciphey + ``` +- [PyPi](https://pypi.org/project/ciphey) (πŸ“₯ 11K / month Β· ⏱️ 06.06.2021): + ``` + pip install ciphey + ``` +- [Docker Hub](https://hub.docker.com/r/remnux/ciphey) (πŸ“₯ 15K Β· ⭐ 5 Β· ⏱️ 05.02.2022): + ``` + docker pull remnux/ciphey ```
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fastNLP (πŸ₯‰27 Β· ⭐ 2.5K) - fastNLP: A Modularized and Extensible NLP Framework. Currently still.. Apache-2 +
vaderSentiment (πŸ₯ˆ27 Β· ⭐ 3.4K Β· πŸ’€) - VADER Sentiment Analysis. VADER (Valence Aware Dictionary.. MIT -- [GitHub](https://github.com/fastnlp/fastNLP) (πŸ‘¨β€πŸ’» 54 Β· πŸ”€ 400 Β· πŸ“₯ 65 Β· πŸ“¦ 55 Β· πŸ“‹ 180 - 19% open Β· ⏱️ 06.12.2021): +- [GitHub](https://github.com/cjhutto/vaderSentiment) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 830 Β· πŸ“¦ 3.5K Β· πŸ“‹ 110 - 30% open Β· ⏱️ 15.03.2021): ``` - git clone https://github.com/fastnlp/fastNLP + git clone https://github.com/cjhutto/vaderSentiment ``` -- [PyPi](https://pypi.org/project/fastnlp) (πŸ“₯ 1.3K / month Β· πŸ“¦ 3 Β· ⏱️ 04.02.2019): +- [PyPi](https://pypi.org/project/vadersentiment) (πŸ“₯ 440K / month Β· πŸ“¦ 170 Β· ⏱️ 22.05.2020): ``` - pip install fastnlp + pip install vadersentiment + ``` +- [Conda](https://anaconda.org/conda-forge/vadersentiment) (πŸ“₯ 8K Β· ⏱️ 22.03.2021): + ``` + conda install -c conda-forge vadersentiment ```
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PyTextRank (πŸ₯‰27 Β· ⭐ 1.7K) - Python implementation of TextRank for phrase extraction and.. MIT +
neuralcoref (πŸ₯ˆ27 Β· ⭐ 2.5K Β· πŸ’€) - Fast Coreference Resolution in spaCy with Neural Networks. MIT -- [GitHub](https://github.com/DerwenAI/pytextrank) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 320 Β· πŸ“¦ 220 Β· πŸ“‹ 79 - 25% open Β· ⏱️ 01.01.2022): +- [GitHub](https://github.com/huggingface/neuralcoref) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 430 Β· πŸ“₯ 310 Β· πŸ“¦ 440 Β· πŸ“‹ 290 - 16% open Β· ⏱️ 22.06.2021): ``` - git clone https://github.com/DerwenAI/pytextrank + git clone https://github.com/huggingface/neuralcoref ``` -- [PyPi](https://pypi.org/project/pytextrank) (πŸ“₯ 16K / month Β· πŸ“¦ 11 Β· ⏱️ 10.10.2021): +- [PyPi](https://pypi.org/project/neuralcoref) (πŸ“₯ 55K / month Β· πŸ“¦ 14 Β· ⏱️ 08.04.2019): ``` - pip install pytextrank + pip install neuralcoref + ``` +- [Conda](https://anaconda.org/conda-forge/neuralcoref) (πŸ“₯ 11K Β· ⏱️ 21.02.2020): + ``` + conda install -c conda-forge neuralcoref ```
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spacy-transformers (πŸ₯‰27 Β· ⭐ 1.1K) - Use pretrained transformers like BERT, XLNet and GPT-2.. MIT spacy +
english-words (πŸ₯‰26 Β· ⭐ 6.5K) - A text file containing 479k English words for all your.. Unlicense -- [GitHub](https://github.com/explosion/spacy-transformers) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 130 Β· πŸ“¦ 360 Β· ⏱️ 16.12.2021): +- [GitHub](https://github.com/dwyl/english-words) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 1.3K Β· πŸ“‹ 73 - 61% open Β· ⏱️ 20.10.2021): ``` - git clone https://github.com/explosion/spacy-transformers + git clone https://github.com/dwyl/english-words ``` -- [PyPi](https://pypi.org/project/spacy-transformers) (πŸ“₯ 63K / month Β· πŸ“¦ 13 Β· ⏱️ 07.12.2021): +- [PyPi](https://pypi.org/project/english-words) (πŸ“₯ 17K / month Β· πŸ“¦ 6 Β· ⏱️ 29.01.2022): ``` - pip install spacy-transformers + pip install english-words ```
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Ciphey (πŸ₯‰26 Β· ⭐ 9.3K) - Automatically decrypt encryptions without knowing the key or cipher,.. MIT +
spacy-transformers (πŸ₯‰26 Β· ⭐ 1.1K) - Use pretrained transformers like BERT, XLNet and GPT-2.. MIT spacy -- [GitHub](https://github.com/Ciphey/Ciphey) (πŸ‘¨β€πŸ’» 46 Β· πŸ”€ 580 Β· πŸ“‹ 280 - 17% open Β· ⏱️ 03.11.2021): +- [GitHub](https://github.com/explosion/spacy-transformers) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 140 Β· πŸ“¦ 390 Β· ⏱️ 13.01.2022): ``` - git clone https://github.com/Ciphey/Ciphey + git clone https://github.com/explosion/spacy-transformers ``` -- [PyPi](https://pypi.org/project/ciphey) (πŸ“₯ 10K / month Β· ⏱️ 06.06.2021): +- [PyPi](https://pypi.org/project/spacy-transformers) (πŸ“₯ 87K / month Β· πŸ“¦ 13 Β· ⏱️ 14.01.2022): ``` - pip install ciphey + pip install spacy-transformers ``` -- [Docker Hub](https://hub.docker.com/r/remnux/ciphey) (πŸ“₯ 14K Β· ⭐ 5 Β· ⏱️ 16.11.2021): +- [Conda](https://anaconda.org/conda-forge/spacy-transformers) (πŸ“₯ 380 Β· ⏱️ 14.01.2022): ``` - docker pull remnux/ciphey + conda install -c conda-forge spacy-transformers ```
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Snips NLU (πŸ₯‰26 Β· ⭐ 3.6K Β· πŸ’€) - Snips Python library to extract meaning from text. Apache-2 +
Snips NLU (πŸ₯‰25 Β· ⭐ 3.6K Β· πŸ’€) - Snips Python library to extract meaning from text. Apache-2 -- [GitHub](https://github.com/snipsco/snips-nlu) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 500 Β· πŸ“‹ 250 - 22% open Β· ⏱️ 03.05.2021): +- [GitHub](https://github.com/snipsco/snips-nlu) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 500 Β· πŸ“‹ 260 - 23% open Β· ⏱️ 03.05.2021): ``` git clone https://github.com/snipsco/snips-nlu ``` -- [PyPi](https://pypi.org/project/snips-nlu) (πŸ“₯ 3.1K / month Β· πŸ“¦ 11 Β· ⏱️ 15.01.2020): +- [PyPi](https://pypi.org/project/snips-nlu) (πŸ“₯ 4.2K / month Β· πŸ“¦ 11 Β· ⏱️ 15.01.2020): ``` pip install snips-nlu ```
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scattertext (πŸ₯‰26 Β· ⭐ 1.7K) - Beautiful visualizations of how language differs among document.. Apache-2 +
fastNLP (πŸ₯‰25 Β· ⭐ 2.5K Β· πŸ“‰) - fastNLP: A Modularized and Extensible NLP Framework. Currently.. Apache-2 -- [GitHub](https://github.com/JasonKessler/scattertext) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 240 Β· πŸ“¦ 250 Β· πŸ“‹ 85 - 20% open Β· ⏱️ 15.11.2021): +- [GitHub](https://github.com/fastnlp/fastNLP) (πŸ‘¨β€πŸ’» 54 Β· πŸ”€ 400 Β· πŸ“₯ 65 Β· πŸ“¦ 55 Β· πŸ“‹ 180 - 19% open Β· ⏱️ 06.12.2021): ``` - git clone https://github.com/JasonKessler/scattertext + git clone https://github.com/fastnlp/fastNLP ``` -- [PyPi](https://pypi.org/project/scattertext) (πŸ“₯ 3.3K / month Β· πŸ“¦ 10 Β· ⏱️ 15.11.2021): +- [PyPi](https://pypi.org/project/fastnlp) (πŸ“₯ 1.1K / month Β· πŸ“¦ 3 Β· ⏱️ 04.02.2019): ``` - pip install scattertext + pip install fastnlp + ``` +
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pytorch-nlp (πŸ₯‰25 Β· ⭐ 2K Β· πŸ’€) - Basic Utilities for PyTorch Natural Language Processing.. BSD-3 + +- [GitHub](https://github.com/PetrochukM/PyTorch-NLP) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 240 Β· πŸ“¦ 330 Β· πŸ“‹ 67 - 26% open Β· ⏱️ 10.07.2021): + + ``` + git clone https://github.com/PetrochukM/PyTorch-NLP ``` -- [Conda](https://anaconda.org/conda-forge/scattertext) (πŸ“₯ 59K Β· ⏱️ 15.11.2021): +- [PyPi](https://pypi.org/project/pytorch-nlp) (πŸ“₯ 7.1K / month Β· πŸ“¦ 17 Β· ⏱️ 04.11.2019): ``` - conda install -c conda-forge scattertext + pip install pytorch-nlp ```
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SciSpacy (πŸ₯‰26 Β· ⭐ 1.1K) - A full spaCy pipeline and models for scientific/biomedical documents. Apache-2 +
scattertext (πŸ₯‰25 Β· ⭐ 1.7K) - Beautiful visualizations of how language differs among document.. Apache-2 -- [GitHub](https://github.com/allenai/scispacy) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 140 Β· πŸ“¦ 380 Β· πŸ“‹ 230 - 15% open Β· ⏱️ 15.07.2021): +- [GitHub](https://github.com/JasonKessler/scattertext) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 240 Β· πŸ“¦ 260 Β· πŸ“‹ 85 - 20% open Β· ⏱️ 15.11.2021): ``` - git clone https://github.com/allenai/scispacy + git clone https://github.com/JasonKessler/scattertext ``` -- [PyPi](https://pypi.org/project/scispacy) (πŸ“₯ 19K / month Β· πŸ“¦ 11 Β· ⏱️ 12.02.2021): +- [PyPi](https://pypi.org/project/scattertext) (πŸ“₯ 3.9K / month Β· πŸ“¦ 10 Β· ⏱️ 15.11.2021): ``` - pip install scispacy + pip install scattertext + ``` +- [Conda](https://anaconda.org/conda-forge/scattertext) (πŸ“₯ 60K Β· ⏱️ 15.11.2021): + ``` + conda install -c conda-forge scattertext ```
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english-words (πŸ₯‰24 Β· ⭐ 6K) - A text file containing 479k English words for all your.. Unlicense +
SciSpacy (πŸ₯‰25 Β· ⭐ 1.1K) - A full spaCy pipeline and models for scientific/biomedical documents. Apache-2 -- [GitHub](https://github.com/dwyl/english-words) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 1.2K Β· πŸ“‹ 73 - 61% open Β· ⏱️ 20.10.2021): +- [GitHub](https://github.com/allenai/scispacy) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 150 Β· πŸ“¦ 400 Β· πŸ“‹ 240 - 14% open Β· ⏱️ 03.02.2022): ``` - git clone https://github.com/dwyl/english-words + git clone https://github.com/allenai/scispacy ``` -- [PyPi](https://pypi.org/project/english-words) (πŸ“₯ 7.3K / month Β· πŸ“¦ 4 Β· ⏱️ 02.08.2021): +- [PyPi](https://pypi.org/project/scispacy) (πŸ“₯ 26K / month Β· πŸ“¦ 11 Β· ⏱️ 12.02.2021): ``` - pip install english-words + pip install scispacy ```
MatchZoo (πŸ₯‰24 Β· ⭐ 3.6K Β· πŸ’€) - Facilitating the design, comparison and sharing of deep.. Apache-2 @@ -1921,95 +2005,103 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we ``` git clone https://github.com/NTMC-Community/MatchZoo ``` -- [PyPi](https://pypi.org/project/matchzoo) (πŸ“₯ 120 / month Β· ⏱️ 24.10.2019): +- [PyPi](https://pypi.org/project/matchzoo) (πŸ“₯ 91 / month Β· ⏱️ 24.10.2019): ``` pip install matchzoo ```
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pytorch-nlp (πŸ₯‰24 Β· ⭐ 2K) - Basic Utilities for PyTorch Natural Language Processing (NLP). BSD-3 +
sense2vec (πŸ₯‰24 Β· ⭐ 1.3K) - Contextually-keyed word vectors. MIT -- [GitHub](https://github.com/PetrochukM/PyTorch-NLP) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 240 Β· πŸ“¦ 320 Β· πŸ“‹ 67 - 26% open Β· ⏱️ 10.07.2021): +- [GitHub](https://github.com/explosion/sense2vec) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 220 Β· πŸ“₯ 25K Β· πŸ“¦ 120 Β· πŸ“‹ 110 - 17% open Β· ⏱️ 16.08.2021): ``` - git clone https://github.com/PetrochukM/PyTorch-NLP + git clone https://github.com/explosion/sense2vec ``` -- [PyPi](https://pypi.org/project/pytorch-nlp) (πŸ“₯ 6.7K / month Β· πŸ“¦ 17 Β· ⏱️ 04.11.2019): +- [PyPi](https://pypi.org/project/sense2vec) (πŸ“₯ 9.3K / month Β· πŸ“¦ 8 Β· ⏱️ 19.04.2021): ``` - pip install pytorch-nlp + pip install sense2vec + ``` +- [Conda](https://anaconda.org/conda-forge/sense2vec) (πŸ“₯ 24K Β· ⏱️ 14.07.2021): + ``` + conda install -c conda-forge sense2vec ```
Sockeye (πŸ₯‰24 Β· ⭐ 1K) - Sequence-to-sequence framework with a focus on Neural Machine.. Apache-2 -- [GitHub](https://github.com/awslabs/sockeye) (πŸ‘¨β€πŸ’» 54 Β· πŸ”€ 300 Β· πŸ“₯ 14 Β· πŸ“‹ 270 - 3% open Β· ⏱️ 11.01.2022): +- [GitHub](https://github.com/awslabs/sockeye) (πŸ‘¨β€πŸ’» 55 Β· πŸ”€ 300 Β· πŸ“₯ 14 Β· πŸ“‹ 270 - 3% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/awslabs/sockeye ``` -- [PyPi](https://pypi.org/project/sockeye) (πŸ“₯ 1.1K / month Β· πŸ“¦ 2 Β· ⏱️ 20.12.2021): +- [PyPi](https://pypi.org/project/sockeye) (πŸ“₯ 1.3K / month Β· πŸ“¦ 2 Β· ⏱️ 09.02.2022): ``` pip install sockeye ```
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Kashgari (πŸ₯‰23 Β· ⭐ 2.2K) - Kashgari is a production-level NLP Transfer learning framework.. Apache-2 +
Kashgari (πŸ₯‰23 Β· ⭐ 2.3K Β· πŸ’€) - Kashgari is a production-level NLP Transfer learning.. Apache-2 -- [GitHub](https://github.com/BrikerMan/Kashgari) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 420 Β· πŸ“¦ 49 Β· πŸ“‹ 360 - 9% open Β· ⏱️ 09.07.2021): +- [GitHub](https://github.com/BrikerMan/Kashgari) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 430 Β· πŸ“¦ 50 Β· πŸ“‹ 360 - 10% open Β· ⏱️ 09.07.2021): ``` git clone https://github.com/BrikerMan/Kashgari ``` -- [PyPi](https://pypi.org/project/kashgari-tf) (πŸ“₯ 78 / month Β· πŸ“¦ 2 Β· ⏱️ 18.10.2019): +- [PyPi](https://pypi.org/project/kashgari-tf) (πŸ“₯ 100 / month Β· πŸ“¦ 2 Β· ⏱️ 18.10.2019): ``` pip install kashgari-tf ```
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lightseq (πŸ₯‰23 Β· ⭐ 1.9K) - LightSeq: A High Performance Library for Sequence Processing and.. Apache-2 +
lightseq (πŸ₯‰23 Β· ⭐ 2K) - LightSeq: A High Performance Library for Sequence Processing and.. Apache-2 -- [GitHub](https://github.com/bytedance/lightseq) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 200 Β· πŸ“₯ 550 Β· πŸ“‹ 140 - 51% open Β· ⏱️ 10.01.2022): +- [GitHub](https://github.com/bytedance/lightseq) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 210 Β· πŸ“₯ 560 Β· πŸ“‹ 150 - 53% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/bytedance/lightseq ``` -- [PyPi](https://pypi.org/project/lightseq) (πŸ“₯ 1.3K / month Β· ⏱️ 30.11.2021): +- [PyPi](https://pypi.org/project/lightseq) (πŸ“₯ 1.7K / month Β· ⏱️ 26.01.2022): ``` pip install lightseq ```
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FARM (πŸ₯‰23 Β· ⭐ 1.4K) - Fast & easy transfer learning for NLP. Harvesting language models.. Apache-2 +
rubrix (πŸ₯‰23 Β· ⭐ 840 Β· βž•) - Python framework for data-centric NLP. Apache-2 -- [GitHub](https://github.com/deepset-ai/FARM) (πŸ‘¨β€πŸ’» 37 Β· πŸ”€ 210 Β· πŸ“‹ 420 - 8% open Β· ⏱️ 23.11.2021): +- [GitHub](https://github.com/recognai/rubrix) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 72 Β· πŸ“‹ 420 - 17% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/deepset-ai/FARM + git clone https://github.com/recognai/rubrix ``` -- [PyPi](https://pypi.org/project/farm) (πŸ“₯ 2.9K / month Β· πŸ“¦ 2 Β· ⏱️ 10.06.2021): +- [PyPi](https://pypi.org/project/rubrix) (πŸ“₯ 1.4K / month Β· ⏱️ 02.02.2022): ``` - pip install farm + pip install rubrix + ``` +- [Conda](https://anaconda.org/conda-forge/rubrix) (πŸ“₯ 170 Β· ⏱️ 03.02.2022): + ``` + conda install -c conda-forge rubrix ```
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sense2vec (πŸ₯‰23 Β· ⭐ 1.3K) - Contextually-keyed word vectors. MIT +
pySBD (πŸ₯‰23 Β· ⭐ 410 Β· πŸ’€) - pySBD (Python Sentence Boundary Disambiguation) is a rule-based sentence.. MIT -- [GitHub](https://github.com/explosion/sense2vec) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 220 Β· πŸ“₯ 24K Β· πŸ“¦ 110 Β· πŸ“‹ 110 - 17% open Β· ⏱️ 16.08.2021): +- [GitHub](https://github.com/nipunsadvilkar/pySBD) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 48 Β· πŸ“¦ 280 Β· πŸ“‹ 60 - 20% open Β· ⏱️ 11.02.2021): ``` - git clone https://github.com/explosion/sense2vec + git clone https://github.com/nipunsadvilkar/pySBD ``` -- [PyPi](https://pypi.org/project/sense2vec) (πŸ“₯ 3.4K / month Β· πŸ“¦ 8 Β· ⏱️ 19.04.2021): +- [PyPi](https://pypi.org/project/pysbd) (πŸ“₯ 45K / month Β· πŸ“¦ 3 Β· ⏱️ 11.02.2021): ``` - pip install sense2vec + pip install pysbd ``` -- [Conda](https://anaconda.org/conda-forge/sense2vec) (πŸ“₯ 24K Β· ⏱️ 14.07.2021): +- [Conda](https://anaconda.org/conda-forge/pysbd) (πŸ“₯ 210 Β· ⏱️ 11.10.2021): ``` - conda install -c conda-forge sense2vec + conda install -c conda-forge pysbd ```
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gpt-2-simple (πŸ₯‰22 Β· ⭐ 2.8K) - Python package to easily retrain OpenAIs GPT-2 text-.. MIT +
gpt-2-simple (πŸ₯‰22 Β· ⭐ 2.9K) - Python package to easily retrain OpenAIs GPT-2 text-.. MIT -- [GitHub](https://github.com/minimaxir/gpt-2-simple) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 590 Β· πŸ“₯ 280 Β· πŸ“‹ 240 - 61% open Β· ⏱️ 18.10.2021): +- [GitHub](https://github.com/minimaxir/gpt-2-simple) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 590 Β· πŸ“₯ 290 Β· πŸ“‹ 240 - 61% open Β· ⏱️ 18.10.2021): ``` git clone https://github.com/minimaxir/gpt-2-simple ``` -- [PyPi](https://pypi.org/project/gpt-2-simple) (πŸ“₯ 4.7K / month Β· πŸ“¦ 5 Β· ⏱️ 18.10.2021): +- [PyPi](https://pypi.org/project/gpt-2-simple) (πŸ“₯ 5.5K / month Β· πŸ“¦ 5 Β· ⏱️ 18.10.2021): ``` pip install gpt-2-simple ``` @@ -2021,19 +2113,19 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we ``` git clone https://github.com/IntelLabs/nlp-architect ``` -- [PyPi](https://pypi.org/project/nlp-architect) (πŸ“₯ 320 / month Β· ⏱️ 12.04.2020): +- [PyPi](https://pypi.org/project/nlp-architect) (πŸ“₯ 290 / month Β· ⏱️ 12.04.2020): ``` pip install nlp-architect ```
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Texthero (πŸ₯‰22 Β· ⭐ 2.4K) - Text preprocessing, representation and visualization from zero to hero. MIT +
Texthero (πŸ₯‰22 Β· ⭐ 2.4K Β· πŸ’€) - Text preprocessing, representation and visualization from zero to.. MIT - [GitHub](https://github.com/jbesomi/texthero) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 210 Β· πŸ“₯ 87 Β· πŸ“‹ 140 - 56% open Β· ⏱️ 19.07.2021): ``` git clone https://github.com/jbesomi/texthero ``` -- [PyPi](https://pypi.org/project/texthero) (πŸ“₯ 9.2K / month Β· πŸ“¦ 4 Β· ⏱️ 01.07.2021): +- [PyPi](https://pypi.org/project/texthero) (πŸ“₯ 24K / month Β· πŸ“¦ 4 Β· ⏱️ 01.07.2021): ``` pip install texthero ``` @@ -2045,33 +2137,37 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we ``` git clone https://github.com/utterworks/fast-bert ``` -- [PyPi](https://pypi.org/project/fast-bert) (πŸ“₯ 1.9K / month Β· πŸ“¦ 2 Β· ⏱️ 10.01.2022): +- [PyPi](https://pypi.org/project/fast-bert) (πŸ“₯ 1.5K / month Β· πŸ“¦ 2 Β· ⏱️ 10.01.2022): ``` pip install fast-bert ```
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YouTokenToMe (πŸ₯‰22 Β· ⭐ 780 Β· πŸ’€) - Unsupervised text tokenizer focused on computational efficiency. MIT +
FARM (πŸ₯‰22 Β· ⭐ 1.5K) - Fast & easy transfer learning for NLP. Harvesting language models.. Apache-2 -- [GitHub](https://github.com/VKCOM/YouTokenToMe) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 57 Β· πŸ“¦ 200 Β· πŸ“‹ 51 - 54% open Β· ⏱️ 28.01.2021): +- [GitHub](https://github.com/deepset-ai/FARM) (πŸ‘¨β€πŸ’» 37 Β· πŸ”€ 210 Β· πŸ“‹ 430 - 8% open Β· ⏱️ 23.11.2021): ``` - git clone https://github.com/vkcom/youtokentome + git clone https://github.com/deepset-ai/FARM + ``` +- [PyPi](https://pypi.org/project/farm) (πŸ“₯ 8.1K / month Β· πŸ“¦ 2 Β· ⏱️ 10.06.2021): + ``` + pip install farm ``` -- [PyPi](https://pypi.org/project/youtokentome) (πŸ“₯ 32K / month Β· πŸ“¦ 15 Β· ⏱️ 12.02.2020): +- [Conda](https://anaconda.org/conda-forge/farm) (πŸ“₯ 890 Β· ⏱️ 14.06.2021): ``` - pip install youtokentome + conda install -c conda-forge farm ```
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pySBD (πŸ₯‰22 Β· ⭐ 400 Β· πŸ’€) - pySBD (Python Sentence Boundary Disambiguation) is a rule-based sentence.. MIT +
anaGo (πŸ₯‰22 Β· ⭐ 1.4K Β· πŸ’€) - Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition,.. MIT -- [GitHub](https://github.com/nipunsadvilkar/pySBD) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 46 Β· πŸ“¦ 260 Β· πŸ“‹ 60 - 20% open Β· ⏱️ 11.02.2021): +- [GitHub](https://github.com/Hironsan/anago) (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 360 Β· πŸ“¦ 27 Β· πŸ“‹ 110 - 33% open Β· ⏱️ 01.04.2021): ``` - git clone https://github.com/nipunsadvilkar/pySBD + git clone https://github.com/Hironsan/anago ``` -- [PyPi](https://pypi.org/project/pysbd) (πŸ“₯ 32K / month Β· πŸ“¦ 3 Β· ⏱️ 11.02.2021): +- [PyPi](https://pypi.org/project/anago) (πŸ“₯ 510 / month Β· πŸ“¦ 5 Β· ⏱️ 17.07.2018): ``` - pip install pysbd + pip install anago ```
DeepMatcher (πŸ₯‰21 Β· ⭐ 4K Β· πŸ’€) - Python package for performing Entity and Text Matching using.. BSD-3 @@ -2081,62 +2177,82 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we ``` git clone https://github.com/anhaidgroup/deepmatcher ``` -- [PyPi](https://pypi.org/project/deepmatcher) (πŸ“₯ 500 / month Β· ⏱️ 13.06.2021): +- [PyPi](https://pypi.org/project/deepmatcher) (πŸ“₯ 530 / month Β· ⏱️ 13.06.2021): ``` pip install deepmatcher ```
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anaGo (πŸ₯‰21 Β· ⭐ 1.4K Β· πŸ’€) - Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition,.. MIT +
jiant (πŸ₯‰21 Β· ⭐ 1.4K) - jiant is an nlp toolkit. MIT -- [GitHub](https://github.com/Hironsan/anago) (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 360 Β· πŸ“¦ 27 Β· πŸ“‹ 110 - 33% open Β· ⏱️ 01.04.2021): +- [GitHub](https://github.com/nyu-mll/jiant) (πŸ‘¨β€πŸ’» 56 Β· πŸ”€ 260 Β· πŸ“¦ 2 Β· πŸ“‹ 550 - 11% open Β· ⏱️ 03.02.2022): ``` - git clone https://github.com/Hironsan/anago + git clone https://github.com/nyu-mll/jiant ``` -- [PyPi](https://pypi.org/project/anago) (πŸ“₯ 400 / month Β· πŸ“¦ 5 Β· ⏱️ 17.07.2018): +- [PyPi](https://pypi.org/project/jiant) (πŸ“₯ 110 / month Β· ⏱️ 10.05.2021): ``` - pip install anago + pip install jiant ```
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jiant (πŸ₯‰21 Β· ⭐ 1.4K) - jiant is an nlp toolkit. MIT +
OpenPrompt (πŸ₯‰21 Β· ⭐ 1.1K Β· 🐣) - An Open-Source Framework for Prompt-Learning. Apache-2 -- [GitHub](https://github.com/nyu-mll/jiant) (πŸ‘¨β€πŸ’» 56 Β· πŸ”€ 260 Β· πŸ“¦ 2 Β· πŸ“‹ 550 - 11% open Β· ⏱️ 31.12.2021): +- [GitHub](https://github.com/thunlp/OpenPrompt) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 110 Β· πŸ“¦ 6 Β· πŸ“‹ 91 - 20% open Β· ⏱️ 24.01.2022): ``` - git clone https://github.com/nyu-mll/jiant + git clone https://github.com/thunlp/OpenPrompt ``` -- [PyPi](https://pypi.org/project/jiant) (πŸ“₯ 120 / month Β· ⏱️ 10.05.2021): +- [PyPi](https://pypi.org/project/openprompt) (πŸ“₯ 330 / month Β· ⏱️ 09.12.2021): ``` - pip install jiant + pip install openprompt + ``` +
+
detoxify (πŸ₯‰21 Β· ⭐ 380 Β· βž•) - Trained models & code to predict toxic comments on all 3 Jigsaw.. Apache-2 + +- [GitHub](https://github.com/unitaryai/detoxify) (πŸ‘¨β€πŸ’» 4 Β· πŸ”€ 41 Β· πŸ“₯ 32K Β· πŸ“¦ 33 Β· πŸ“‹ 23 - 43% open Β· ⏱️ 14.01.2022): + + ``` + git clone https://github.com/unitaryai/detoxify + ``` +- [PyPi](https://pypi.org/project/detoxify) (πŸ“₯ 5.8K / month Β· πŸ“¦ 1 Β· ⏱️ 27.10.2021): + ``` + pip install detoxify + ``` +
+
qdrant (πŸ₯‰20 Β· ⭐ 1.1K Β· βž•) - Qdrant - vector similarity search engine with extended filtering.. Apache-2 + +- [GitHub](https://github.com/qdrant/qdrant) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 71 Β· πŸ“‹ 89 - 26% open Β· ⏱️ 09.02.2022): + + ``` + git clone https://github.com/qdrant/qdrant ```
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finetune (πŸ₯‰21 Β· ⭐ 660) - Scikit-learn style model finetuning for NLP. MPL-2.0 +
finetune (πŸ₯‰20 Β· ⭐ 660) - Scikit-learn style model finetuning for NLP. MPL-2.0 - [GitHub](https://github.com/IndicoDataSolutions/finetune) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 71 Β· πŸ“¦ 9 Β· πŸ“‹ 140 - 15% open Β· ⏱️ 20.12.2021): ``` git clone https://github.com/IndicoDataSolutions/finetune ``` -- [PyPi](https://pypi.org/project/finetune) (πŸ“₯ 210 / month Β· πŸ“¦ 2 Β· ⏱️ 20.12.2021): +- [PyPi](https://pypi.org/project/finetune) (πŸ“₯ 86 / month Β· πŸ“¦ 2 Β· ⏱️ 20.12.2021): ``` pip install finetune ```
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TextBox (πŸ₯‰18 Β· ⭐ 320) - TextBox is an open-source library for building text generation system. MIT +
TextBox (πŸ₯‰18 Β· ⭐ 340) - TextBox is an open-source library for building text generation system. MIT -- [GitHub](https://github.com/RUCAIBox/TextBox) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 57 Β· πŸ“¦ 5 Β· πŸ“‹ 18 - 16% open Β· ⏱️ 26.12.2021): +- [GitHub](https://github.com/RUCAIBox/TextBox) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 58 Β· πŸ“¦ 5 Β· πŸ“‹ 18 - 16% open Β· ⏱️ 08.02.2022): ``` git clone https://github.com/RUCAIBox/TextBox ``` -- [PyPi](https://pypi.org/project/textbox) (πŸ“₯ 51 / month Β· ⏱️ 15.04.2021): +- [PyPi](https://pypi.org/project/textbox) (πŸ“₯ 46 / month Β· ⏱️ 15.04.2021): ``` pip install textbox ```
OpenNRE (πŸ₯‰17 Β· ⭐ 3.5K) - An Open-Source Package for Neural Relation Extraction (NRE). MIT -- [GitHub](https://github.com/thunlp/OpenNRE) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 910 Β· πŸ“‹ 340 - 6% open Β· ⏱️ 09.12.2021): +- [GitHub](https://github.com/thunlp/OpenNRE) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 920 Β· πŸ“‹ 340 - 6% open Β· ⏱️ 09.12.2021): ``` git clone https://github.com/thunlp/OpenNRE @@ -2144,7 +2260,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we
Camphr (πŸ₯‰16 Β· ⭐ 340) - Camphr - NLP libary for creating pipeline components. Apache-2 spacy -- [GitHub](https://github.com/PKSHATechnology-Research/camphr) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 17 Β· πŸ“‹ 27 - 7% open Β· ⏱️ 18.08.2021): +- [GitHub](https://github.com/PKSHATechnology-Research/camphr) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 17 Β· πŸ“‹ 28 - 7% open Β· ⏱️ 18.08.2021): ``` git clone https://github.com/PKSHATechnology-Research/camphr @@ -2161,56 +2277,59 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we ``` git clone https://github.com/pytorch/translate ``` -- [PyPi](https://pypi.org/project/pytorch-translate) (πŸ“₯ 4 / month Β· ⏱️ 01.05.2018): +- [PyPi](https://pypi.org/project/pytorch-translate) (πŸ“₯ 3 / month Β· ⏱️ 01.05.2018): ``` pip install pytorch-translate ```
VizSeq (πŸ₯‰14 Β· ⭐ 380) - An Analysis Toolkit for Natural Language Generation (Translation,.. MIT -- [GitHub](https://github.com/facebookresearch/vizseq) (πŸ‘¨β€πŸ’» 3 Β· πŸ”€ 44 Β· πŸ“¦ 3 Β· πŸ“‹ 16 - 43% open Β· ⏱️ 02.09.2021): +- [GitHub](https://github.com/facebookresearch/vizseq) (πŸ‘¨β€πŸ’» 3 Β· πŸ”€ 45 Β· πŸ“¦ 3 Β· πŸ“‹ 16 - 43% open Β· ⏱️ 15.01.2022): ``` git clone https://github.com/facebookresearch/vizseq ``` -- [PyPi](https://pypi.org/project/vizseq) (πŸ“₯ 73 / month Β· ⏱️ 07.08.2020): +- [PyPi](https://pypi.org/project/vizseq) (πŸ“₯ 91 / month Β· ⏱️ 07.08.2020): ``` pip install vizseq ```
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BLINK (πŸ₯‰13 Β· ⭐ 780 Β· πŸ’€) - Entity Linker solution. MIT +
BLINK (πŸ₯‰13 Β· ⭐ 810 Β· πŸ’€) - Entity Linker solution. MIT -- [GitHub](https://github.com/facebookresearch/BLINK) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 140 Β· πŸ“‹ 77 - 62% open Β· ⏱️ 02.04.2021): +- [GitHub](https://github.com/facebookresearch/BLINK) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 140 Β· πŸ“‹ 79 - 60% open Β· ⏱️ 02.04.2021): ``` git clone https://github.com/facebookresearch/BLINK ```
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Show 23 hidden projects... +
Show 26 hidden projects... -- fastText (πŸ₯ˆ33 Β· ⭐ 23K Β· πŸ’€) - Library for fast text representation and classification. MIT -- fuzzywuzzy (πŸ₯ˆ33 Β· ⭐ 8.6K) - Fuzzy String Matching in Python. ❗️GPL-2.0 -- langid (πŸ₯‰27 Β· ⭐ 1.9K Β· πŸ’€) - Stand-alone language identification system. BSD-3 -- polyglot (πŸ₯‰26 Β· ⭐ 1.9K Β· πŸ’€) - Multilingual text (NLP) processing toolkit. ❗️GPL-3.0 +- fastText (πŸ₯ˆ34 Β· ⭐ 23K Β· πŸ’€) - Library for fast text representation and classification. MIT +- fuzzywuzzy (πŸ₯ˆ32 Β· ⭐ 8.6K) - Fuzzy String Matching in Python. ❗️GPL-2.0 +- langid (πŸ₯ˆ27 Β· ⭐ 1.9K Β· πŸ’€) - Stand-alone language identification system. BSD-3 +- polyglot (πŸ₯‰26 Β· ⭐ 2K Β· πŸ’€) - Multilingual text (NLP) processing toolkit. ❗️GPL-3.0 - flashtext (πŸ₯‰25 Β· ⭐ 5K Β· πŸ’€) - Extract Keywords from sentence or Replace keywords in sentences. MIT - textgenrnn (πŸ₯‰25 Β· ⭐ 4.6K Β· πŸ’€) - Easily train your own text-generating neural network of any.. MIT -- Texar (πŸ₯‰23 Β· ⭐ 2.2K Β· πŸ’€) - Toolkit for Machine Learning, Natural Language Processing, and.. Apache-2 -- stop-words (πŸ₯‰23 Β· ⭐ 140 Β· πŸ’€) - Get list of common stop words in various languages in Python. BSD-3 +- whoosh (πŸ₯‰23 Β· ⭐ 190 Β· βž•) - Pure-Python full-text search library. ❗️BSD-1-Clause +- Texar (πŸ₯‰22 Β· ⭐ 2.2K Β· πŸ’€) - Toolkit for Machine Learning, Natural Language Processing, and.. Apache-2 +- YouTokenToMe (πŸ₯‰22 Β· ⭐ 790 Β· πŸ’€) - Unsupervised text tokenizer focused on computational efficiency. MIT +- happy-transformer (πŸ₯‰22 Β· ⭐ 260 Β· βž•) - A package built on top of Hugging Faces transformers.. Apache-2 huggingface +- stop-words (πŸ₯‰22 Β· ⭐ 140 Β· πŸ’€) - Get list of common stop words in various languages in Python. BSD-3 - DELTA (πŸ₯‰21 Β· ⭐ 1.5K Β· πŸ’€) - DELTA is a deep learning based natural language and speech.. Apache-2 -- textpipe (πŸ₯‰20 Β· ⭐ 290 Β· πŸ’€) - Textpipe: clean and extract metadata from text. MIT - pyfasttext (πŸ₯‰20 Β· ⭐ 230 Β· πŸ’€) - Yet another Python binding for fastText. ❗️GPL-3.0 -- fastT5 (πŸ₯‰19 Β· ⭐ 240) - boost inference speed of T5 models by 5x & reduce the model size by 3x. Apache-2 -- skift (πŸ₯‰18 Β· ⭐ 220) - scikit-learn wrappers for Python fastText. MIT -- NeuroNER (πŸ₯‰17 Β· ⭐ 1.6K Β· πŸ’€) - Named-entity recognition using neural networks. Easy-to-use and.. MIT -- nboost (πŸ₯‰17 Β· ⭐ 600 Β· πŸ’€) - NBoost is a scalable, search-api-boosting platform for deploying.. Apache-2 -- textaugment (πŸ₯‰17 Β· ⭐ 200) - TextAugment: Text Augmentation Library. MIT +- textpipe (πŸ₯‰19 Β· ⭐ 290 Β· πŸ’€) - Textpipe: clean and extract metadata from text. MIT +- fastT5 (πŸ₯‰19 Β· ⭐ 250) - boost inference speed of T5 models by 5x & reduce the model size by 3x. Apache-2 +- NeuroNER (πŸ₯‰18 Β· ⭐ 1.6K Β· πŸ’€) - Named-entity recognition using neural networks. Easy-to-use and.. MIT +- skift (πŸ₯‰18 Β· ⭐ 230) - scikit-learn wrappers for Python fastText. MIT +- nboost (πŸ₯‰17 Β· ⭐ 610 Β· πŸ’€) - NBoost is a scalable, search-api-boosting platform for deploying.. Apache-2 +- textaugment (πŸ₯‰17 Β· ⭐ 210) - TextAugment: Text Augmentation Library. MIT - NeuralQA (πŸ₯‰15 Β· ⭐ 220 Β· πŸ’€) - NeuralQA: A Usable Library for Question Answering on Large Datasets.. MIT +- TransferNLP (πŸ₯‰14 Β· ⭐ 290 Β· πŸ’€) - NLP library designed for reproducible experimentation.. MIT - Headliner (πŸ₯‰14 Β· ⭐ 230 Β· πŸ’€) - Easy training and deployment of seq2seq models. MIT -- numerizer (πŸ₯‰14 Β· ⭐ 130) - A Python module to convert natural language numerics into ints and.. MIT -- TransferNLP (πŸ₯‰13 Β· ⭐ 290 Β· πŸ’€) - NLP library designed for reproducible experimentation.. MIT -- ONNX-T5 (πŸ₯‰13 Β· ⭐ 190 Β· πŸ’€) - Summarization, translation, sentiment-analysis, text-generation.. Apache-2 +- numerizer (πŸ₯‰14 Β· ⭐ 140) - A Python module to convert natural language numerics into ints and.. MIT +- ONNX-T5 (πŸ₯‰13 Β· ⭐ 190 Β· πŸ’€) - Summarization, translation, sentiment-analysis, text-generation.. Apache-2 - textvec (πŸ₯‰13 Β· ⭐ 180 Β· πŸ’€) - Text vectorization tool to outperform TFIDF for classification.. MIT -- spacy-dbpedia-spotlight (πŸ₯‰9 Β· ⭐ 48) - A spaCy wrapper for DBpedia Spotlight. MIT spacy +- spacy-dbpedia-spotlight (πŸ₯‰9 Β· ⭐ 50) - A spaCy wrapper for DBpedia Spotlight. MIT spacy

@@ -2220,114 +2339,122 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we _Libraries for image & video processing, manipulation, and augmentation as well as libraries for computer vision tasks such as facial recognition, object detection, and classification._ -
Pillow (πŸ₯‡45 Β· ⭐ 9.3K) - The friendly PIL fork (Python Imaging Library). ❗️PIL +
Pillow (πŸ₯‡45 Β· ⭐ 9.4K) - The friendly PIL fork (Python Imaging Library). ❗️PIL -- [GitHub](https://github.com/python-pillow/Pillow) (πŸ‘¨β€πŸ’» 380 Β· πŸ”€ 1.8K Β· πŸ“‹ 2.4K - 6% open Β· ⏱️ 11.01.2022): +- [GitHub](https://github.com/python-pillow/Pillow) (πŸ‘¨β€πŸ’» 380 Β· πŸ”€ 1.8K Β· πŸ“‹ 2.4K - 6% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/python-pillow/Pillow ``` -- [PyPi](https://pypi.org/project/Pillow) (πŸ“₯ 31M / month Β· πŸ“¦ 62K Β· ⏱️ 02.01.2022): +- [PyPi](https://pypi.org/project/Pillow) (πŸ“₯ 37M / month Β· πŸ“¦ 62K Β· ⏱️ 03.02.2022): ``` pip install Pillow ``` -- [Conda](https://anaconda.org/conda-forge/pillow) (πŸ“₯ 12M Β· ⏱️ 10.11.2021): +- [Conda](https://anaconda.org/conda-forge/pillow) (πŸ“₯ 13M Β· ⏱️ 10.02.2022): ``` conda install -c conda-forge pillow ```
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scikit-image (πŸ₯‡44 Β· ⭐ 4.7K) - Image processing in Python. BSD-2 +
scikit-image (πŸ₯‡44 Β· ⭐ 4.8K) - Image processing in Python. BSD-2 -- [GitHub](https://github.com/scikit-image/scikit-image) (πŸ‘¨β€πŸ’» 540 Β· πŸ”€ 1.9K Β· πŸ“¦ 90K Β· πŸ“‹ 2.3K - 13% open Β· ⏱️ 11.01.2022): +- [GitHub](https://github.com/scikit-image/scikit-image) (πŸ‘¨β€πŸ’» 540 Β· πŸ”€ 1.9K Β· πŸ“¦ 93K Β· πŸ“‹ 2.4K - 13% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/scikit-image/scikit-image ``` -- [PyPi](https://pypi.org/project/scikit-image) (πŸ“₯ 4.9M / month Β· πŸ“¦ 9K Β· ⏱️ 15.12.2021): +- [PyPi](https://pypi.org/project/scikit-image) (πŸ“₯ 5M / month Β· πŸ“¦ 9K Β· ⏱️ 15.12.2021): ``` pip install scikit-image ``` -- [Conda](https://anaconda.org/conda-forge/scikit-image) (πŸ“₯ 3.1M Β· ⏱️ 17.12.2021): +- [Conda](https://anaconda.org/conda-forge/scikit-image) (πŸ“₯ 3.2M Β· ⏱️ 17.12.2021): ``` conda install -c conda-forge scikit-image ```
torchvision (πŸ₯‡41 Β· ⭐ 11K) - Datasets, Transforms and Models specific to Computer Vision. BSD-3 -- [GitHub](https://github.com/pytorch/vision) (πŸ‘¨β€πŸ’» 450 Β· πŸ”€ 5.4K Β· πŸ“‹ 2.1K - 27% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/pytorch/vision) (πŸ‘¨β€πŸ’» 460 Β· πŸ”€ 5.6K Β· πŸ“‹ 2.3K - 28% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/pytorch/vision ``` -- [PyPi](https://pypi.org/project/torchvision) (πŸ“₯ 2.9M / month Β· πŸ“¦ 3.4K Β· ⏱️ 15.12.2021): +- [PyPi](https://pypi.org/project/torchvision) (πŸ“₯ 2.9M / month Β· πŸ“¦ 3.5K Β· ⏱️ 27.01.2022): ``` pip install torchvision ``` -- [Conda](https://anaconda.org/conda-forge/torchvision) (πŸ“₯ 160K Β· ⏱️ 27.09.2021): +- [Conda](https://anaconda.org/conda-forge/torchvision) (πŸ“₯ 170K Β· ⏱️ 06.02.2022): ``` conda install -c conda-forge torchvision ```
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imageio (πŸ₯‡37 Β· ⭐ 980 Β· πŸ“ˆ) - Python library for reading and writing image data. BSD-2 +
MMDetection (πŸ₯‡37 Β· ⭐ 18K Β· πŸ“ˆ) - OpenMMLab Detection Toolbox and Benchmark. Apache-2 -- [GitHub](https://github.com/imageio/imageio) (πŸ‘¨β€πŸ’» 83 Β· πŸ”€ 190 Β· πŸ“₯ 100 Β· πŸ“¦ 54K Β· πŸ“‹ 410 - 17% open Β· ⏱️ 11.01.2022): +- [GitHub](https://github.com/open-mmlab/mmdetection) (πŸ‘¨β€πŸ’» 300 Β· πŸ”€ 6.6K Β· πŸ“¦ 250 Β· πŸ“‹ 5.2K - 9% open Β· ⏱️ 08.02.2022): ``` - git clone https://github.com/imageio/imageio - ``` -- [PyPi](https://pypi.org/project/imageio) (πŸ“₯ 16M / month Β· πŸ“¦ 2.5K Β· ⏱️ 23.12.2021): - ``` - pip install imageio + git clone https://github.com/open-mmlab/mmdetection ``` -- [Conda](https://anaconda.org/conda-forge/imageio) (πŸ“₯ 2.5M Β· ⏱️ 29.12.2021): +- [PyPi](https://pypi.org/project/mmdet) (πŸ“₯ 33K / month Β· πŸ“¦ 6 Β· ⏱️ 08.02.2022): ``` - conda install -c conda-forge imageio + pip install mmdet ```
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detectron2 (πŸ₯‡35 Β· ⭐ 20K) - Detectron2 is a platform for object detection, segmentation.. Apache-2 +
PyTorch Image Models (πŸ₯‡37 Β· ⭐ 16K) - PyTorch image models, scripts, pretrained weights --.. Apache-2 -- [GitHub](https://github.com/facebookresearch/detectron2) (πŸ‘¨β€πŸ’» 200 Β· πŸ”€ 5K Β· πŸ“¦ 470 Β· πŸ“‹ 2.8K - 5% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/rwightman/pytorch-image-models) (πŸ‘¨β€πŸ’» 65 Β· πŸ”€ 2.6K Β· πŸ“₯ 900K Β· πŸ“¦ 1.9K Β· πŸ“‹ 460 - 14% open Β· ⏱️ 02.02.2022): ``` - git clone https://github.com/facebookresearch/detectron2 + git clone https://github.com/rwightman/pytorch-image-models ``` -- [Conda](https://anaconda.org/conda-forge/detectron2) (πŸ“₯ 37K Β· ⏱️ 11.01.2022): +- [PyPi](https://pypi.org/project/timm) (πŸ“₯ 530K / month Β· πŸ“¦ 67 Β· ⏱️ 17.01.2022): ``` - conda install -c conda-forge detectron2 + pip install timm ``` -
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PyTorch Image Models (πŸ₯‡35 Β· ⭐ 16K) - PyTorch image models, scripts, pretrained weights --.. Apache-2 - -- [GitHub](https://github.com/rwightman/pytorch-image-models) (πŸ‘¨β€πŸ’» 64 Β· πŸ”€ 2.5K Β· πŸ“₯ 830K Β· πŸ“¦ 1.7K Β· πŸ“‹ 440 - 12% open Β· ⏱️ 08.01.2022): - +- [Conda](https://anaconda.org/conda-forge/timm) (πŸ“₯ 12K Β· ⏱️ 30.06.2021): ``` - git clone https://github.com/rwightman/pytorch-image-models + conda install -c conda-forge timm ```
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Albumentations (πŸ₯‡35 Β· ⭐ 9.5K) - Fast image augmentation library and an easy-to-use wrapper.. MIT +
imageio (πŸ₯‡37 Β· ⭐ 980) - Python library for reading and writing image data. BSD-2 -- [GitHub](https://github.com/albumentations-team/albumentations) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 1.2K Β· πŸ“¦ 6.2K Β· πŸ“‹ 570 - 41% open Β· ⏱️ 24.12.2021): +- [GitHub](https://github.com/imageio/imageio) (πŸ‘¨β€πŸ’» 85 Β· πŸ”€ 200 Β· πŸ“₯ 140 Β· πŸ“¦ 56K Β· πŸ“‹ 430 - 17% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/albumentations-team/albumentations + git clone https://github.com/imageio/imageio + ``` +- [PyPi](https://pypi.org/project/imageio) (πŸ“₯ 13M / month Β· πŸ“¦ 2.6K Β· ⏱️ 07.02.2022): + ``` + pip install imageio + ``` +- [Conda](https://anaconda.org/conda-forge/imageio) (πŸ“₯ 2.5M Β· ⏱️ 26.01.2022): + ``` + conda install -c conda-forge imageio + ``` +
+
Albumentations (πŸ₯ˆ35 Β· ⭐ 9.6K) - Fast image augmentation library and an easy-to-use wrapper.. MIT + +- [GitHub](https://github.com/albumentations-team/albumentations) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 1.2K Β· πŸ“¦ 6.5K Β· πŸ“‹ 580 - 41% open Β· ⏱️ 24.12.2021): + ``` -- [PyPi](https://pypi.org/project/albumentations) (πŸ“₯ 190K / month Β· πŸ“¦ 180 Β· ⏱️ 04.10.2021): + git clone https://github.com/albumentations-team/albumentations + ``` +- [PyPi](https://pypi.org/project/albumentations) (πŸ“₯ 290K / month Β· πŸ“¦ 180 Β· ⏱️ 04.10.2021): ``` pip install albumentations ``` -- [Conda](https://anaconda.org/conda-forge/albumentations) (πŸ“₯ 30K Β· ⏱️ 15.07.2021): +- [Conda](https://anaconda.org/conda-forge/albumentations) (πŸ“₯ 31K Β· ⏱️ 15.07.2021): ``` conda install -c conda-forge albumentations ```
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MoviePy (πŸ₯‡35 Β· ⭐ 8.9K) - Video editing with Python. MIT +
MoviePy (πŸ₯ˆ35 Β· ⭐ 8.9K) - Video editing with Python. MIT -- [GitHub](https://github.com/Zulko/moviepy) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 1.2K Β· πŸ“¦ 13K Β· πŸ“‹ 1.1K - 30% open Β· ⏱️ 12.11.2021): +- [GitHub](https://github.com/Zulko/moviepy) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 1.2K Β· πŸ“¦ 13K Β· πŸ“‹ 1.2K - 28% open Β· ⏱️ 12.11.2021): ``` git clone https://github.com/Zulko/moviepy ``` -- [PyPi](https://pypi.org/project/moviepy) (πŸ“₯ 1.5M / month Β· πŸ“¦ 720 Β· ⏱️ 15.12.2021): +- [PyPi](https://pypi.org/project/moviepy) (πŸ“₯ 2.5M / month Β· πŸ“¦ 720 Β· ⏱️ 15.12.2021): ``` pip install moviepy ``` @@ -2336,38 +2463,58 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge moviepy ```
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InsightFace (πŸ₯ˆ34 Β· ⭐ 11K) - State-of-the-art 2D and 3D Face Analysis Project. MIT +
Kornia (πŸ₯ˆ35 Β· ⭐ 5.9K) - Open Source Differentiable Computer Vision Library. Apache-2 -- [GitHub](https://github.com/deepinsight/insightface) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 3.5K Β· πŸ“¦ 130 Β· πŸ“‹ 1.8K - 54% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/kornia/kornia) (πŸ‘¨β€πŸ’» 150 Β· πŸ”€ 570 Β· πŸ“₯ 190 Β· πŸ“¦ 970 Β· πŸ“‹ 540 - 25% open Β· ⏱️ 09.02.2022): ``` - git clone https://github.com/deepinsight/insightface + git clone https://github.com/kornia/kornia ``` -- [PyPi](https://pypi.org/project/insightface) (πŸ“₯ 24K / month Β· πŸ“¦ 5 Β· ⏱️ 21.09.2021): +- [PyPi](https://pypi.org/project/kornia) (πŸ“₯ 290K / month Β· πŸ“¦ 44 Β· ⏱️ 31.01.2022): ``` - pip install insightface + pip install kornia + ``` +- [Conda](https://anaconda.org/conda-forge/kornia) (πŸ“₯ 11K Β· ⏱️ 01.02.2022): + ``` + conda install -c conda-forge kornia ```
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Kornia (πŸ₯ˆ34 Β· ⭐ 5.7K) - Open Source Differentiable Computer Vision Library. Apache-2 +
detectron2 (πŸ₯ˆ34 Β· ⭐ 20K) - Detectron2 is a platform for object detection, segmentation.. Apache-2 -- [GitHub](https://github.com/kornia/kornia) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 560 Β· πŸ“₯ 180 Β· πŸ“¦ 900 Β· πŸ“‹ 530 - 26% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/facebookresearch/detectron2) (πŸ‘¨β€πŸ’» 200 Β· πŸ”€ 5.1K Β· πŸ“¦ 490 Β· πŸ“‹ 2.8K - 5% open Β· ⏱️ 07.02.2022): ``` - git clone https://github.com/kornia/kornia + git clone https://github.com/facebookresearch/detectron2 ``` -- [PyPi](https://pypi.org/project/kornia) (πŸ“₯ 260K / month Β· πŸ“¦ 44 Β· ⏱️ 03.12.2021): +- [PyPi](https://pypi.org/project/detectron2) (πŸ“¦ 2 Β· ⏱️ 06.02.2020): ``` - pip install kornia + pip install detectron2 + ``` +- [Conda](https://anaconda.org/conda-forge/detectron2) (πŸ“₯ 39K Β· ⏱️ 11.01.2022): + ``` + conda install -c conda-forge detectron2 + ``` +
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InsightFace (πŸ₯ˆ34 Β· ⭐ 11K) - State-of-the-art 2D and 3D Face Analysis Project. MIT + +- [GitHub](https://github.com/deepinsight/insightface) (πŸ‘¨β€πŸ’» 37 Β· πŸ”€ 3.6K Β· πŸ“¦ 130 Β· πŸ“‹ 1.8K - 54% open Β· ⏱️ 09.02.2022): + + ``` + git clone https://github.com/deepinsight/insightface + ``` +- [PyPi](https://pypi.org/project/insightface) (πŸ“₯ 22K / month Β· πŸ“¦ 5 Β· ⏱️ 29.01.2022): + ``` + pip install insightface ```
opencv-python (πŸ₯ˆ34 Β· ⭐ 2.5K) - Automated CI toolchain to produce precompiled opencv-python,.. MIT -- [GitHub](https://github.com/opencv/opencv-python) (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 480 Β· πŸ“‹ 500 - 5% open Β· ⏱️ 27.12.2021): +- [GitHub](https://github.com/opencv/opencv-python) (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 490 Β· πŸ“‹ 510 - 6% open Β· ⏱️ 25.01.2022): ``` git clone https://github.com/opencv/opencv-python ``` -- [PyPi](https://pypi.org/project/opencv-python) (πŸ“₯ 4.1M / month Β· πŸ“¦ 8.7K Β· ⏱️ 29.12.2021): +- [PyPi](https://pypi.org/project/opencv-python) (πŸ“₯ 4.9M / month Β· πŸ“¦ 8.7K Β· ⏱️ 29.12.2021): ``` pip install opencv-python ``` @@ -2379,163 +2526,183 @@ _Libraries for image & video processing, manipulation, and augmentation as well ``` git clone https://github.com/ageitgey/face_recognition ``` -- [PyPi](https://pypi.org/project/face_recognition) (πŸ“₯ 46K / month Β· πŸ“¦ 210 Β· ⏱️ 21.08.2018): +- [PyPi](https://pypi.org/project/face_recognition) (πŸ“₯ 44K / month Β· πŸ“¦ 210 Β· ⏱️ 21.08.2018): ``` pip install face_recognition ``` +- [Conda](https://anaconda.org/conda-forge/face_recognition) (πŸ“₯ 4.2K Β· ⏱️ 30.04.2021): + ``` + conda install -c conda-forge face_recognition + ```
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MMDetection (πŸ₯ˆ33 Β· ⭐ 18K) - OpenMMLab Detection Toolbox and Benchmark. Apache-2 +
GluonCV (πŸ₯ˆ32 Β· ⭐ 5.1K) - Gluon CV Toolkit. Apache-2 -- [GitHub](https://github.com/open-mmlab/mmdetection) (πŸ‘¨β€πŸ’» 290 Β· πŸ”€ 6.4K Β· πŸ“¦ 230 Β· πŸ“‹ 5K - 8% open Β· ⏱️ 30.12.2021): +- [GitHub](https://github.com/dmlc/gluon-cv) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 1.1K Β· πŸ“¦ 660 Β· πŸ“‹ 810 - 7% open Β· ⏱️ 02.02.2022): ``` - git clone https://github.com/open-mmlab/mmdetection + git clone https://github.com/dmlc/gluon-cv + ``` +- [PyPi](https://pypi.org/project/gluoncv) (πŸ“₯ 560K / month Β· πŸ“¦ 59 Β· ⏱️ 10.02.2022): + ``` + pip install gluoncv ```
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Wand (πŸ₯ˆ33 Β· ⭐ 1.1K) - The ctypes-based simple ImageMagick binding for Python. MIT +
Wand (πŸ₯ˆ32 Β· ⭐ 1.1K) - The ctypes-based simple ImageMagick binding for Python. MIT -- [GitHub](https://github.com/emcconville/wand) (πŸ‘¨β€πŸ’» 97 Β· πŸ”€ 190 Β· πŸ“₯ 5.5K Β· πŸ“¦ 8.4K Β· πŸ“‹ 360 - 4% open Β· ⏱️ 20.11.2021): +- [GitHub](https://github.com/emcconville/wand) (πŸ‘¨β€πŸ’» 97 Β· πŸ”€ 190 Β· πŸ“₯ 6K Β· πŸ“¦ 9K Β· πŸ“‹ 360 - 4% open Β· ⏱️ 31.01.2022): ``` git clone https://github.com/emcconville/wand ``` -- [PyPi](https://pypi.org/project/wand) (πŸ“₯ 290K / month Β· πŸ“¦ 680 Β· ⏱️ 17.08.2021): +- [PyPi](https://pypi.org/project/wand) (πŸ“₯ 420K / month Β· πŸ“¦ 680 Β· ⏱️ 17.08.2021): ``` pip install wand ``` +- [Conda](https://anaconda.org/conda-forge/wand) (πŸ“₯ 8.6K Β· ⏱️ 30.11.2020): + ``` + conda install -c conda-forge wand + ```
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GluonCV (πŸ₯ˆ32 Β· ⭐ 5K) - Gluon CV Toolkit. Apache-2 +
PaddleSeg (πŸ₯ˆ31 Β· ⭐ 3.7K) - Easy-to-use image segmentation library with awesome pre-.. Apache-2 -- [GitHub](https://github.com/dmlc/gluon-cv) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 1.1K Β· πŸ“¦ 650 Β· πŸ“‹ 810 - 7% open Β· ⏱️ 09.01.2022): +- [GitHub](https://github.com/PaddlePaddle/PaddleSeg) (πŸ‘¨β€πŸ’» 74 Β· πŸ”€ 820 Β· πŸ“¦ 490 Β· πŸ“‹ 880 - 49% open Β· ⏱️ 01.02.2022): ``` - git clone https://github.com/dmlc/gluon-cv + git clone https://github.com/PaddlePaddle/PaddleSeg ``` -- [PyPi](https://pypi.org/project/gluoncv) (πŸ“₯ 510K / month Β· πŸ“¦ 59 Β· ⏱️ 13.01.2022): +- [PyPi](https://pypi.org/project/paddleseg) (πŸ“₯ 1.2K / month Β· πŸ“¦ 2 Β· ⏱️ 20.01.2022): ``` - pip install gluoncv + pip install paddleseg ```
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imageai (πŸ₯ˆ30 Β· ⭐ 6.8K Β· πŸ’€) - A python library built to empower developers to build applications.. MIT +
deepface (πŸ₯ˆ31 Β· ⭐ 3.2K) - A Lightweight Face Recognition and Facial Attribute Analysis (Age,.. MIT -- [GitHub](https://github.com/OlafenwaMoses/ImageAI) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 1.9K Β· πŸ“₯ 690K Β· πŸ“¦ 1K Β· πŸ“‹ 670 - 37% open Β· ⏱️ 08.05.2021): +- [GitHub](https://github.com/serengil/deepface) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 710 Β· πŸ“¦ 410 Β· πŸ“‹ 400 - 0% open Β· ⏱️ 02.02.2022): ``` - git clone https://github.com/OlafenwaMoses/ImageAI + git clone https://github.com/serengil/deepface ``` -- [PyPi](https://pypi.org/project/imageai) (πŸ“₯ 7.8K / month Β· πŸ“¦ 16 Β· ⏱️ 05.01.2021): +- [PyPi](https://pypi.org/project/deepface) (πŸ“₯ 37K / month Β· πŸ“¦ 3 Β· ⏱️ 12.01.2022): ``` - pip install imageai + pip install deepface ```
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imutils (πŸ₯ˆ30 Β· ⭐ 3.9K Β· πŸ’€) - A series of convenience functions to make basic image processing.. MIT +
imageai (πŸ₯ˆ30 Β· ⭐ 6.8K Β· πŸ’€) - A python library built to empower developers to build applications.. MIT -- [GitHub](https://github.com/PyImageSearch/imutils) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 940 Β· πŸ“¦ 22K Β· πŸ“‹ 160 - 52% open Β· ⏱️ 15.01.2021): +- [GitHub](https://github.com/OlafenwaMoses/ImageAI) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 1.9K Β· πŸ“₯ 710K Β· πŸ“¦ 1K Β· πŸ“‹ 680 - 36% open Β· ⏱️ 08.05.2021): ``` - git clone https://github.com/jrosebr1/imutils + git clone https://github.com/OlafenwaMoses/ImageAI ``` -- [PyPi](https://pypi.org/project/imutils) (πŸ“₯ 340K / month Β· πŸ“¦ 760 Β· ⏱️ 15.01.2021): +- [PyPi](https://pypi.org/project/imageai) (πŸ“₯ 7.9K / month Β· πŸ“¦ 16 Β· ⏱️ 05.01.2021): ``` - pip install imutils + pip install imageai ``` -- [Conda](https://anaconda.org/conda-forge/imutils) (πŸ“₯ 75K Β· ⏱️ 09.12.2021): +- [Conda](https://anaconda.org/conda-forge/imageai) (πŸ“₯ 2.4K Β· ⏱️ 30.04.2021): ``` - conda install -c conda-forge imutils + conda install -c conda-forge imageai ```
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PaddleSeg (πŸ₯ˆ30 Β· ⭐ 3.5K) - Easy-to-use image segmentation library with awesome pre-.. Apache-2 +
PaddleDetection (πŸ₯ˆ30 Β· ⭐ 6.3K) - Object Detection toolkit based on PaddlePaddle. It.. Apache-2 -- [GitHub](https://github.com/PaddlePaddle/PaddleSeg) (πŸ‘¨β€πŸ’» 60 Β· πŸ”€ 780 Β· πŸ“¦ 440 Β· πŸ“‹ 840 - 49% open Β· ⏱️ 05.01.2022): +- [GitHub](https://github.com/PaddlePaddle/PaddleDetection) (πŸ‘¨β€πŸ’» 80 Β· πŸ”€ 1.6K Β· πŸ“¦ 8 Β· πŸ“‹ 3K - 30% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/PaddlePaddle/PaddleSeg + git clone https://github.com/PaddlePaddle/PaddleDetection ``` -- [PyPi](https://pypi.org/project/paddleseg) (πŸ“₯ 1.1K / month Β· πŸ“¦ 2 Β· ⏱️ 13.10.2021): +- [PyPi](https://pypi.org/project/paddledet) (πŸ“₯ 310 / month Β· ⏱️ 26.11.2021): ``` - pip install paddleseg + pip install paddledet ```
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deepface (πŸ₯ˆ30 Β· ⭐ 3K) - A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender,.. MIT +
imutils (πŸ₯ˆ30 Β· ⭐ 4K) - A series of convenience functions to make basic image processing operations.. MIT -- [GitHub](https://github.com/serengil/deepface) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 690 Β· πŸ“¦ 370 Β· πŸ“‹ 380 - 1% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/PyImageSearch/imutils) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 940 Β· πŸ“¦ 23K Β· πŸ“‹ 220 - 65% open Β· ⏱️ 27.01.2022): ``` - git clone https://github.com/serengil/deepface + git clone https://github.com/PyImageSearch/imutils ``` -- [PyPi](https://pypi.org/project/deepface) (πŸ“₯ 38K / month Β· πŸ“¦ 3 Β· ⏱️ 12.01.2022): +- [PyPi](https://pypi.org/project/imutils) (πŸ“₯ 310K / month Β· πŸ“¦ 760 Β· ⏱️ 15.01.2021): ``` - pip install deepface + pip install imutils + ``` +- [Conda](https://anaconda.org/conda-forge/imutils) (πŸ“₯ 76K Β· ⏱️ 09.12.2021): + ``` + conda install -c conda-forge imutils ```
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ImageHash (πŸ₯ˆ30 Β· ⭐ 2.2K) - A Python Perceptual Image Hashing Module. BSD-2 +
ImageHash (πŸ₯ˆ30 Β· ⭐ 2.3K) - A Python Perceptual Image Hashing Module. BSD-2 -- [GitHub](https://github.com/JohannesBuchner/imagehash) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 280 Β· πŸ“¦ 4.1K Β· πŸ“‹ 100 - 12% open Β· ⏱️ 07.09.2021): +- [GitHub](https://github.com/JohannesBuchner/imagehash) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 280 Β· πŸ“¦ 4.2K Β· πŸ“‹ 110 - 12% open Β· ⏱️ 07.09.2021): ``` git clone https://github.com/JohannesBuchner/imagehash ``` -- [PyPi](https://pypi.org/project/ImageHash) (πŸ“₯ 1.1M / month Β· πŸ“¦ 320 Β· ⏱️ 15.07.2021): +- [PyPi](https://pypi.org/project/ImageHash) (πŸ“₯ 1.4M / month Β· πŸ“¦ 320 Β· ⏱️ 15.07.2021): ``` pip install ImageHash ``` -- [Conda](https://anaconda.org/conda-forge/imagehash) (πŸ“₯ 160K Β· ⏱️ 15.07.2021): +- [Conda](https://anaconda.org/conda-forge/imagehash) (πŸ“₯ 170K Β· ⏱️ 15.07.2021): ``` conda install -c conda-forge imagehash ```
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vit-pytorch (πŸ₯‰28 Β· ⭐ 8.2K) - Implementation of Vision Transformer, a simple way to achieve.. MIT +
vit-pytorch (πŸ₯‰29 Β· ⭐ 8.5K) - Implementation of Vision Transformer, a simple way to achieve.. MIT -- [GitHub](https://github.com/lucidrains/vit-pytorch) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 1.3K Β· πŸ“¦ 63 Β· πŸ“‹ 160 - 49% open Β· ⏱️ 06.01.2022): +- [GitHub](https://github.com/lucidrains/vit-pytorch) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 1.4K Β· πŸ“¦ 69 Β· πŸ“‹ 170 - 48% open Β· ⏱️ 31.01.2022): ``` git clone https://github.com/lucidrains/vit-pytorch ``` -- [PyPi](https://pypi.org/project/vit-pytorch) (πŸ“₯ 8K / month Β· πŸ“¦ 1 Β· ⏱️ 06.01.2022): +- [PyPi](https://pypi.org/project/vit-pytorch) (πŸ“₯ 15K / month Β· πŸ“¦ 1 Β· ⏱️ 31.01.2022): ``` pip install vit-pytorch ```
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PaddleDetection (πŸ₯‰28 Β· ⭐ 6.1K) - Object Detection toolkit based on PaddlePaddle. It.. Apache-2 +
Face Alignment (πŸ₯‰27 Β· ⭐ 5.5K) - 2D and 3D Face alignment library build using pytorch. BSD-3 -- [GitHub](https://github.com/PaddlePaddle/PaddleDetection) (πŸ‘¨β€πŸ’» 78 Β· πŸ”€ 1.5K Β· πŸ“¦ 7 Β· πŸ“‹ 2.9K - 30% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/1adrianb/face-alignment) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 1.1K Β· πŸ“‹ 270 - 19% open Β· ⏱️ 04.08.2021): ``` - git clone https://github.com/PaddlePaddle/PaddleDetection + git clone https://github.com/1adrianb/face-alignment + ``` +- [PyPi](https://pypi.org/project/face-alignment) (πŸ“₯ 7K / month Β· πŸ“¦ 8 Β· ⏱️ 14.09.2021): + ``` + pip install face-alignment ```
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Face Alignment (πŸ₯‰27 Β· ⭐ 5.5K) - 2D and 3D Face alignment library build using pytorch. BSD-3 +
Augmentor (πŸ₯‰27 Β· ⭐ 4.6K) - Image augmentation library in Python for machine learning. MIT -- [GitHub](https://github.com/1adrianb/face-alignment) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 1.1K Β· πŸ“‹ 270 - 19% open Β· ⏱️ 04.08.2021): +- [GitHub](https://github.com/mdbloice/Augmentor) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 830 Β· πŸ“¦ 400 Β· πŸ“‹ 190 - 63% open Β· ⏱️ 15.10.2021): ``` - git clone https://github.com/1adrianb/face-alignment + git clone https://github.com/mdbloice/Augmentor ``` -- [PyPi](https://pypi.org/project/face-alignment) (πŸ“₯ 6.8K / month Β· πŸ“¦ 8 Β· ⏱️ 14.09.2021): +- [PyPi](https://pypi.org/project/Augmentor) (πŸ“₯ 9.8K / month Β· πŸ“¦ 29 Β· ⏱️ 14.10.2021): ``` - pip install face-alignment + pip install Augmentor ```
vidgear (πŸ₯‰27 Β· ⭐ 2.1K) - A High-performance cross-platform Video Processing Python framework.. Apache-2 -- [GitHub](https://github.com/abhiTronix/vidgear) (πŸ‘¨β€πŸ’» 9 Β· πŸ”€ 160 Β· πŸ“₯ 510 Β· πŸ“¦ 160 Β· πŸ“‹ 190 - 1% open Β· ⏱️ 05.12.2021): +- [GitHub](https://github.com/abhiTronix/vidgear) (πŸ‘¨β€πŸ’» 9 Β· πŸ”€ 160 Β· πŸ“₯ 520 Β· πŸ“¦ 170 Β· πŸ“‹ 200 - 2% open Β· ⏱️ 05.12.2021): ``` git clone https://github.com/abhiTronix/vidgear ``` -- [PyPi](https://pypi.org/project/vidgear) (πŸ“₯ 3.1K / month Β· πŸ“¦ 3 Β· ⏱️ 05.12.2021): +- [PyPi](https://pypi.org/project/vidgear) (πŸ“₯ 4.4K / month Β· πŸ“¦ 3 Β· ⏱️ 05.12.2021): ``` pip install vidgear ```
mahotas (πŸ₯‰27 Β· ⭐ 730) - Computer Vision in Python. MIT -- [GitHub](https://github.com/luispedro/mahotas) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 140 Β· πŸ“¦ 730 Β· πŸ“‹ 77 - 20% open Β· ⏱️ 07.12.2021): +- [GitHub](https://github.com/luispedro/mahotas) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 140 Β· πŸ“¦ 750 Β· πŸ“‹ 77 - 20% open Β· ⏱️ 07.12.2021): ``` git clone https://github.com/luispedro/mahotas ``` -- [PyPi](https://pypi.org/project/mahotas) (πŸ“₯ 8.8K / month Β· πŸ“¦ 110 Β· ⏱️ 14.10.2021): +- [PyPi](https://pypi.org/project/mahotas) (πŸ“₯ 11K / month Β· πŸ“¦ 110 Β· ⏱️ 14.10.2021): ``` pip install mahotas ``` @@ -2546,124 +2713,152 @@ _Libraries for image & video processing, manipulation, and augmentation as well
MMF (πŸ₯‰26 Β· ⭐ 4.8K) - A modular framework for vision & language multimodal research from.. BSD-3 -- [GitHub](https://github.com/facebookresearch/mmf) (πŸ‘¨β€πŸ’» 89 Β· πŸ”€ 780 Β· πŸ“¦ 10 Β· πŸ“‹ 610 - 31% open Β· ⏱️ 11.01.2022): +- [GitHub](https://github.com/facebookresearch/mmf) (πŸ‘¨β€πŸ’» 90 Β· πŸ”€ 790 Β· πŸ“¦ 10 Β· πŸ“‹ 610 - 31% open Β· ⏱️ 02.02.2022): ``` git clone https://github.com/facebookresearch/mmf ``` -- [PyPi](https://pypi.org/project/mmf) (πŸ“₯ 450 / month Β· πŸ“¦ 1 Β· ⏱️ 12.06.2020): +- [PyPi](https://pypi.org/project/mmf) (πŸ“₯ 580 / month Β· πŸ“¦ 1 Β· ⏱️ 12.06.2020): ``` pip install mmf ```
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Augmentor (πŸ₯‰26 Β· ⭐ 4.6K) - Image augmentation library in Python for machine learning. MIT +
lightly (πŸ₯‰26 Β· ⭐ 1.5K) - A python library for self-supervised learning on images. MIT -- [GitHub](https://github.com/mdbloice/Augmentor) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 830 Β· πŸ“¦ 390 Β· πŸ“‹ 190 - 63% open Β· ⏱️ 15.10.2021): +- [GitHub](https://github.com/lightly-ai/lightly) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 97 Β· πŸ“¦ 28 Β· πŸ“‹ 300 - 21% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/mdbloice/Augmentor + git clone https://github.com/lightly-ai/lightly ``` -- [PyPi](https://pypi.org/project/Augmentor) (πŸ“₯ 7.6K / month Β· πŸ“¦ 29 Β· ⏱️ 14.10.2021): +- [PyPi](https://pypi.org/project/lightly) (πŸ“₯ 2.8K / month Β· πŸ“¦ 1 Β· ⏱️ 08.02.2022): ``` - pip install Augmentor + pip install lightly ```
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mtcnn (πŸ₯‰26 Β· ⭐ 1.7K) - MTCNN face detection implementation for TensorFlow, as a PIP package. MIT +
CellProfiler (πŸ₯‰26 Β· ⭐ 650) - An open-source application for biological image analysis. BSD-3 -- [GitHub](https://github.com/ipazc/mtcnn) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 430 Β· πŸ“¦ 1.8K Β· πŸ“‹ 99 - 62% open Β· ⏱️ 09.07.2021): +- [GitHub](https://github.com/CellProfiler/CellProfiler) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 300 Β· πŸ“₯ 2.2K Β· πŸ“¦ 7 Β· πŸ“‹ 3K - 6% open Β· ⏱️ 01.02.2022): ``` - git clone https://github.com/ipazc/mtcnn + git clone https://github.com/CellProfiler/CellProfiler ``` -- [PyPi](https://pypi.org/project/mtcnn) (πŸ“₯ 33K / month Β· πŸ“¦ 43 Β· ⏱️ 09.07.2021): +- [PyPi](https://pypi.org/project/cellprofiler) (πŸ“₯ 760 / month Β· ⏱️ 04.09.2017): ``` - pip install mtcnn + pip install cellprofiler ```
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lightly (πŸ₯‰26 Β· ⭐ 1.4K) - A python library for self-supervised learning on images. MIT +
layout-parser (πŸ₯‰25 Β· ⭐ 2.8K) - A Unified Toolkit for Deep Learning Based Document Image.. Apache-2 -- [GitHub](https://github.com/lightly-ai/lightly) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 93 Β· πŸ“¦ 26 Β· πŸ“‹ 300 - 21% open Β· ⏱️ 06.01.2022): +- [GitHub](https://github.com/Layout-Parser/layout-parser) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 270 Β· πŸ“¦ 43 Β· πŸ“‹ 76 - 50% open Β· ⏱️ 02.02.2022): ``` - git clone https://github.com/lightly-ai/lightly + git clone https://github.com/Layout-Parser/layout-parser ``` -- [PyPi](https://pypi.org/project/lightly) (πŸ“₯ 1.8K / month Β· πŸ“¦ 1 Β· ⏱️ 04.01.2022): +- [PyPi](https://pypi.org/project/layoutparser) (πŸ“₯ 4.8K / month Β· πŸ“¦ 1 Β· ⏱️ 23.09.2021): ``` - pip install lightly + pip install layoutparser ```
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pyvips (πŸ₯‰26 Β· ⭐ 380) - python binding for libvips using cffi. MIT +
facenet-pytorch (πŸ₯‰25 Β· ⭐ 2.7K) - Pretrained Pytorch face detection (MTCNN) and facial.. MIT -- [GitHub](https://github.com/libvips/pyvips) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 33 Β· πŸ“¦ 260 Β· πŸ“‹ 260 - 38% open Β· ⏱️ 15.12.2021): +- [GitHub](https://github.com/timesler/facenet-pytorch) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 570 Β· πŸ“₯ 200K Β· πŸ“¦ 630 Β· πŸ“‹ 140 - 38% open Β· ⏱️ 13.12.2021): ``` - git clone https://github.com/libvips/pyvips + git clone https://github.com/timesler/facenet-pytorch ``` -- [PyPi](https://pypi.org/project/pyvips) (πŸ“₯ 13K / month Β· πŸ“¦ 28 Β· ⏱️ 20.11.2021): +- [PyPi](https://pypi.org/project/facenet-pytorch) (πŸ“₯ 13K / month Β· πŸ“¦ 7 Β· ⏱️ 10.03.2021): ``` - pip install pyvips + pip install facenet-pytorch + ``` +
+
tensorflow-graphics (πŸ₯‰25 Β· ⭐ 2.6K) - TensorFlow Graphics: Differentiable Graphics Layers.. Apache-2 + +- [GitHub](https://github.com/tensorflow/graphics) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 340 Β· πŸ“‹ 220 - 59% open Β· ⏱️ 02.02.2022): + ``` -- [Conda](https://anaconda.org/conda-forge/pyvips) (πŸ“₯ 14K Β· ⏱️ 30.12.2021): + git clone https://github.com/tensorflow/graphics ``` - conda install -c conda-forge pyvips +- [PyPi](https://pypi.org/project/tensorflow-graphics) (πŸ“₯ 2.5K / month Β· πŸ“¦ 4 Β· ⏱️ 03.12.2021): + ``` + pip install tensorflow-graphics ```
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facenet-pytorch (πŸ₯‰25 Β· ⭐ 2.6K) - Pretrained Pytorch face detection (MTCNN) and facial.. MIT +
vissl (πŸ₯‰25 Β· ⭐ 2.3K) - VISSL is FAIRs library of extensible, modular and scalable components.. MIT -- [GitHub](https://github.com/timesler/facenet-pytorch) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 560 Β· πŸ“₯ 180K Β· πŸ“¦ 600 Β· πŸ“‹ 140 - 38% open Β· ⏱️ 13.12.2021): +- [GitHub](https://github.com/facebookresearch/vissl) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 230 Β· πŸ“¦ 5 Β· πŸ“‹ 130 - 33% open Β· ⏱️ 01.02.2022): ``` - git clone https://github.com/timesler/facenet-pytorch + git clone https://github.com/facebookresearch/vissl ``` -- [PyPi](https://pypi.org/project/facenet-pytorch) (πŸ“₯ 12K / month Β· πŸ“¦ 7 Β· ⏱️ 10.03.2021): +- [PyPi](https://pypi.org/project/vissl) (πŸ“₯ 190 / month Β· πŸ“¦ 1 Β· ⏱️ 02.11.2021): ``` - pip install facenet-pytorch + pip install vissl ```
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tensorflow-graphics (πŸ₯‰25 Β· ⭐ 2.6K) - TensorFlow Graphics: Differentiable Graphics Layers.. Apache-2 +
mtcnn (πŸ₯‰25 Β· ⭐ 1.7K Β· πŸ’€) - MTCNN face detection implementation for TensorFlow, as a PIP.. MIT -- [GitHub](https://github.com/tensorflow/graphics) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 340 Β· πŸ“‹ 220 - 59% open Β· ⏱️ 06.01.2022): +- [GitHub](https://github.com/ipazc/mtcnn) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 440 Β· πŸ“¦ 1.9K Β· πŸ“‹ 100 - 62% open Β· ⏱️ 09.07.2021): ``` - git clone https://github.com/tensorflow/graphics + git clone https://github.com/ipazc/mtcnn ``` -- [PyPi](https://pypi.org/project/tensorflow-graphics) (πŸ“₯ 2.6K / month Β· πŸ“¦ 4 Β· ⏱️ 03.12.2021): +- [PyPi](https://pypi.org/project/mtcnn) (πŸ“₯ 27K / month Β· πŸ“¦ 43 Β· ⏱️ 09.07.2021): ``` - pip install tensorflow-graphics + pip install mtcnn + ``` +- [Conda](https://anaconda.org/conda-forge/mtcnn) (πŸ“₯ 4.2K Β· ⏱️ 17.08.2021): + ``` + conda install -c conda-forge mtcnn ```
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pytorchvideo (πŸ₯‰25 Β· ⭐ 2.2K) - A deep learning library for video understanding research. Apache-2 +
icevision (πŸ₯‰25 Β· ⭐ 580 Β· βž•) - An Agnostic Computer Vision Framework - Pluggable to any.. Apache-2 -- [GitHub](https://github.com/facebookresearch/pytorchvideo) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 210 Β· πŸ“‹ 130 - 43% open Β· ⏱️ 11.01.2022): +- [GitHub](https://github.com/airctic/icevision) (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 86 Β· πŸ“‹ 620 - 21% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/facebookresearch/pytorchvideo + git clone https://github.com/airctic/icevision ``` -- [PyPi](https://pypi.org/project/pytorchvideo) (πŸ“₯ 11K / month Β· πŸ“¦ 3 Β· ⏱️ 14.09.2021): +- [PyPi](https://pypi.org/project/icevision) (πŸ“₯ 1.9K / month Β· πŸ“¦ 5 Β· ⏱️ 19.11.2021): ``` - pip install pytorchvideo + pip install icevision ```
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CellProfiler (πŸ₯‰25 Β· ⭐ 640) - An open-source application for biological image analysis. BSD-3 +
pyvips (πŸ₯‰25 Β· ⭐ 390) - python binding for libvips using cffi. MIT -- [GitHub](https://github.com/CellProfiler/CellProfiler) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 290 Β· πŸ“₯ 2.1K Β· πŸ“¦ 6 Β· πŸ“‹ 3K - 6% open Β· ⏱️ 05.11.2021): +- [GitHub](https://github.com/libvips/pyvips) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 37 Β· πŸ“¦ 270 Β· πŸ“‹ 270 - 38% open Β· ⏱️ 15.12.2021): ``` - git clone https://github.com/CellProfiler/CellProfiler + git clone https://github.com/libvips/pyvips ``` -- [PyPi](https://pypi.org/project/cellprofiler) (πŸ“₯ 590 / month Β· ⏱️ 04.09.2017): +- [PyPi](https://pypi.org/project/pyvips) (πŸ“₯ 17K / month Β· πŸ“¦ 28 Β· ⏱️ 20.11.2021): ``` - pip install cellprofiler + pip install pyvips + ``` +- [Conda](https://anaconda.org/conda-forge/pyvips) (πŸ“₯ 15K Β· ⏱️ 30.12.2021): + ``` + conda install -c conda-forge pyvips + ``` +
+
deep-daze (πŸ₯‰24 Β· ⭐ 4.1K) - Simple command line tool for text to image generation using OpenAIs.. MIT + +- [GitHub](https://github.com/lucidrains/deep-daze) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 290 Β· πŸ“¦ 33 Β· πŸ“‹ 160 - 54% open Β· ⏱️ 26.01.2022): + + ``` + git clone https://github.com/lucidrains/deep-daze + ``` +- [PyPi](https://pypi.org/project/deep-daze) (πŸ“₯ 13K / month Β· ⏱️ 26.01.2022): + ``` + pip install deep-daze ```
Image Super-Resolution (πŸ₯‰24 Β· ⭐ 3.4K Β· πŸ’€) - Super-scale your images and run experiments with.. Apache-2 -- [GitHub](https://github.com/idealo/image-super-resolution) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 580 Β· πŸ“¦ 69 Β· πŸ“‹ 190 - 42% open Β· ⏱️ 02.06.2021): +- [GitHub](https://github.com/idealo/image-super-resolution) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 600 Β· πŸ“¦ 71 Β· πŸ“‹ 190 - 43% open Β· ⏱️ 02.06.2021): ``` git clone https://github.com/idealo/image-super-resolution ``` -- [PyPi](https://pypi.org/project/ISR) (πŸ“₯ 5.7K / month Β· πŸ“¦ 5 Β· ⏱️ 08.01.2020): +- [PyPi](https://pypi.org/project/ISR) (πŸ“₯ 4.9K / month Β· πŸ“¦ 5 Β· ⏱️ 08.01.2020): ``` pip install ISR ``` @@ -2672,40 +2867,32 @@ _Libraries for image & video processing, manipulation, and augmentation as well docker pull idealo/image-super-resolution-gpu ```
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vissl (πŸ₯‰24 Β· ⭐ 2.3K) - VISSL is FAIRs library of extensible, modular and scalable components.. MIT +
pytorchvideo (πŸ₯‰24 Β· ⭐ 2.3K) - A deep learning library for video understanding research. Apache-2 -- [GitHub](https://github.com/facebookresearch/vissl) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 220 Β· πŸ“¦ 4 Β· πŸ“‹ 130 - 33% open Β· ⏱️ 10.01.2022): +- [GitHub](https://github.com/facebookresearch/pytorchvideo) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 220 Β· πŸ“‹ 130 - 41% open Β· ⏱️ 08.02.2022): ``` - git clone https://github.com/facebookresearch/vissl + git clone https://github.com/facebookresearch/pytorchvideo ``` -- [PyPi](https://pypi.org/project/vissl) (πŸ“₯ 200 / month Β· πŸ“¦ 1 Β· ⏱️ 02.11.2021): +- [PyPi](https://pypi.org/project/pytorchvideo) (πŸ“₯ 14K / month Β· πŸ“¦ 5 Β· ⏱️ 20.01.2022): ``` - pip install vissl + pip install pytorchvideo ```
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deep-daze (πŸ₯‰23 Β· ⭐ 4K) - Simple command line tool for text to image generation using OpenAIs CLIP.. MIT +
sahi (πŸ₯‰24 Β· ⭐ 540 Β· βž•) - A lightweight vision library for performing large scale object detection/.. MIT -- [GitHub](https://github.com/lucidrains/deep-daze) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 280 Β· πŸ“¦ 32 Β· πŸ“‹ 160 - 53% open Β· ⏱️ 19.10.2021): +- [GitHub](https://github.com/obss/sahi) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 83 Β· πŸ“¦ 19 Β· πŸ“‹ 91 - 8% open Β· ⏱️ 07.02.2022): ``` - git clone https://github.com/lucidrains/deep-daze - ``` -- [PyPi](https://pypi.org/project/deep-daze) (πŸ“₯ 18K / month Β· ⏱️ 19.10.2021): - ``` - pip install deep-daze + git clone https://github.com/obss/sahi ``` -
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layout-parser (πŸ₯‰23 Β· ⭐ 2.8K) - A Unified Toolkit for Deep Learning Based Document Image.. Apache-2 - -- [GitHub](https://github.com/Layout-Parser/layout-parser) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 260 Β· πŸ“¦ 39 Β· πŸ“‹ 75 - 52% open Β· ⏱️ 12.01.2022): - +- [PyPi](https://pypi.org/project/sahi) (πŸ“₯ 12K / month Β· πŸ“¦ 4 Β· ⏱️ 13.01.2022): ``` - git clone https://github.com/Layout-Parser/layout-parser + pip install sahi ``` -- [PyPi](https://pypi.org/project/layoutparser) (πŸ“₯ 3.7K / month Β· πŸ“¦ 1 Β· ⏱️ 23.09.2021): +- [Conda](https://anaconda.org/conda-forge/sahi) (πŸ“₯ 1.3K Β· ⏱️ 13.01.2022): ``` - pip install layoutparser + conda install -c conda-forge sahi ```
Classy Vision (πŸ₯‰22 Β· ⭐ 1.4K) - An end-to-end PyTorch framework for image and video.. MIT @@ -2715,7 +2902,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well ``` git clone https://github.com/facebookresearch/ClassyVision ``` -- [PyPi](https://pypi.org/project/classy_vision) (πŸ“₯ 770 / month Β· πŸ“¦ 2 Β· ⏱️ 09.07.2021): +- [PyPi](https://pypi.org/project/classy_vision) (πŸ“₯ 820 / month Β· πŸ“¦ 2 Β· ⏱️ 09.07.2021): ``` pip install classy_vision ``` @@ -2731,72 +2918,89 @@ _Libraries for image & video processing, manipulation, and augmentation as well ``` git clone https://github.com/ProvenanceLabs/image-match ``` -- [PyPi](https://pypi.org/project/image_match) (πŸ“₯ 780 / month Β· πŸ“¦ 4 Β· ⏱️ 13.02.2017): +- [PyPi](https://pypi.org/project/image_match) (πŸ“₯ 580 / month Β· πŸ“¦ 4 Β· ⏱️ 13.02.2017): ``` pip install image_match ```
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Norfair (πŸ₯‰20 Β· ⭐ 1.2K) - Lightweight Python library for adding real-time object tracking to any.. BSD-3 +
Norfair (πŸ₯‰20 Β· ⭐ 1.3K) - Lightweight Python library for adding real-time object tracking to any.. BSD-3 -- [GitHub](https://github.com/tryolabs/norfair) (πŸ‘¨β€πŸ’» 9 Β· πŸ”€ 97 Β· πŸ“‹ 40 - 22% open Β· ⏱️ 01.10.2021): +- [GitHub](https://github.com/tryolabs/norfair) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 110 Β· πŸ“‹ 41 - 24% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/tryolabs/norfair ``` -- [PyPi](https://pypi.org/project/norfair) (πŸ“₯ 3K / month Β· πŸ“¦ 1 Β· ⏱️ 29.07.2021): +- [PyPi](https://pypi.org/project/norfair) (πŸ“₯ 3.4K / month Β· πŸ“¦ 1 Β· ⏱️ 29.07.2021): ``` pip install norfair ```
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DEβ«ΆTR (πŸ₯‰18 Β· ⭐ 8.2K) - End-to-End Object Detection with Transformers. Apache-2 +
PySlowFast (πŸ₯‰19 Β· ⭐ 4.6K) - PySlowFast: video understanding codebase from FAIR for.. Apache-2 -- [GitHub](https://github.com/facebookresearch/detr) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 1.4K Β· πŸ“‹ 400 - 33% open Β· ⏱️ 18.10.2021): +- [GitHub](https://github.com/facebookresearch/SlowFast) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 860 Β· πŸ“¦ 6 Β· πŸ“‹ 490 - 50% open Β· ⏱️ 28.10.2021): ``` - git clone https://github.com/facebookresearch/detr + git clone https://github.com/facebookresearch/SlowFast + ``` +- [PyPi](https://pypi.org/project/pyslowfast) (πŸ“₯ 15 / month Β· ⏱️ 15.01.2020): + ``` + pip install pyslowfast ```
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PySlowFast (πŸ₯‰18 Β· ⭐ 4.5K) - PySlowFast: video understanding codebase from FAIR for.. Apache-2 +
pycls (πŸ₯‰19 Β· ⭐ 1.8K) - Codebase for Image Classification Research, written in PyTorch. MIT -- [GitHub](https://github.com/facebookresearch/SlowFast) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 850 Β· πŸ“¦ 6 Β· πŸ“‹ 480 - 50% open Β· ⏱️ 28.10.2021): +- [GitHub](https://github.com/facebookresearch/pycls) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 210 Β· πŸ“¦ 5 Β· πŸ“‹ 77 - 27% open Β· ⏱️ 19.08.2021): ``` - git clone https://github.com/facebookresearch/SlowFast + git clone https://github.com/facebookresearch/pycls + ``` +- [PyPi](https://pypi.org/project/pycls) (πŸ“₯ 460 / month Β· ⏱️ 05.09.2020): + ``` + pip install pycls + ``` +
+
DEβ«ΆTR (πŸ₯‰18 Β· ⭐ 8.3K) - End-to-End Object Detection with Transformers. Apache-2 + +- [GitHub](https://github.com/facebookresearch/detr) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 1.4K Β· πŸ“‹ 400 - 33% open Β· ⏱️ 18.10.2021): + + ``` + git clone https://github.com/facebookresearch/detr ```
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Caer (πŸ₯‰18 Β· ⭐ 580) - A lightweight Computer Vision library. Scale your models, not boilerplate. MIT +
Caer (πŸ₯‰18 Β· ⭐ 590) - A lightweight Computer Vision library. Scale your models, not boilerplate. MIT - [GitHub](https://github.com/jasmcaus/caer) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 100 Β· πŸ“₯ 19 Β· πŸ“‹ 15 - 13% open Β· ⏱️ 13.10.2021): ``` git clone https://github.com/jasmcaus/caer ``` -- [PyPi](https://pypi.org/project/caer) (πŸ“₯ 3.8K / month Β· πŸ“¦ 1 Β· ⏱️ 13.10.2021): +- [PyPi](https://pypi.org/project/caer) (πŸ“₯ 4K / month Β· πŸ“¦ 1 Β· ⏱️ 13.10.2021): ``` pip install caer ```
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pycls (πŸ₯‰16 Β· ⭐ 1.8K) - Codebase for Image Classification Research, written in PyTorch. MIT +
scenic (πŸ₯‰17 Β· ⭐ 720 Β· βž•) - Scenic: A Jax Library for Computer Vision Research and Beyond. Apache-2 -- [GitHub](https://github.com/facebookresearch/pycls) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 210 Β· πŸ“¦ 4 Β· πŸ“‹ 77 - 27% open Β· ⏱️ 19.08.2021): +- [GitHub](https://github.com/google-research/scenic) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 74 Β· πŸ“¦ 9 Β· πŸ“‹ 19 - 21% open Β· ⏱️ 09.02.2022): ``` - git clone https://github.com/facebookresearch/pycls + git clone https://github.com/google-research/scenic ```
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Show 11 hidden projects... +
Show 12 hidden projects... -- imgaug (πŸ₯‡35 Β· ⭐ 12K Β· πŸ’€) - Image augmentation for machine learning experiments. MIT -- glfw (πŸ₯‡35 Β· ⭐ 8.5K) - A multi-platform library for OpenGL, OpenGL ES, Vulkan, window and input. ❗️Zlib +- imgaug (πŸ₯ˆ35 Β· ⭐ 12K Β· πŸ’€) - Image augmentation for machine learning experiments. MIT +- glfw (πŸ₯ˆ35 Β· ⭐ 8.6K) - A multi-platform library for OpenGL, OpenGL ES, Vulkan, window and input. ❗️Zlib - Pillow-SIMD (πŸ₯ˆ31 Β· ⭐ 1.7K) - The friendly PIL fork. ❗️PIL -- PyTorch3D (πŸ₯‰28 Β· ⭐ 5.5K) - PyTorch3D is FAIRs library of reusable components for.. ❗Unlicensed +- PyTorch3D (πŸ₯‰28 Β· ⭐ 5.6K) - PyTorch3D is FAIRs library of reusable components for.. ❗Unlicensed - chainercv (πŸ₯‰27 Β· ⭐ 1.5K Β· πŸ’€) - ChainerCV: a Library for Deep Learning in Computer Vision. MIT -- segmentation_models (πŸ₯‰25 Β· ⭐ 3.6K Β· πŸ’€) - Segmentation models with pretrained backbones. Keras.. MIT -- Image Deduplicator (πŸ₯‰23 Β· ⭐ 3.9K Β· πŸ’€) - Finding duplicate images made easy!. Apache-2 +- segmentation_models (πŸ₯‰25 Β· ⭐ 3.7K Β· πŸ’€) - Segmentation models with pretrained backbones. Keras.. MIT +- Image Deduplicator (πŸ₯‰23 Β· ⭐ 4K Β· πŸ’€) - Finding duplicate images made easy!. Apache-2 +- Luminoth (πŸ₯‰22 Β· ⭐ 2.4K Β· πŸ’€) - Deep Learning toolkit for Computer Vision. BSD-3 - nude.py (πŸ₯‰22 Β· ⭐ 830 Β· πŸ’€) - Nudity detection with Python. MIT -- Luminoth (πŸ₯‰21 Β· ⭐ 2.4K Β· πŸ’€) - Deep Learning toolkit for Computer Vision. BSD-3 -- solt (πŸ₯‰16 Β· ⭐ 250 Β· πŸ’€) - Streaming over lightweight data transformations. MIT -- Torch Points 3D (πŸ₯‰13 Β· ⭐ 1 Β· πŸ“‰) - Pytorch framework for doing deep learning on point.. BSD-3 +- solt (πŸ₯‰17 Β· ⭐ 250 Β· πŸ’€) - Streaming over lightweight data transformations. MIT +- Torch Points 3D (πŸ₯‰15 Β· ⭐ 12 Β· 🐣) - Pytorch framework for doing deep learning on point.. BSD-3 +- HugsVision (πŸ₯‰14 Β· ⭐ 140 Β· 🐣) - HugsVision is a easy to use huggingface wrapper for state-of-.. MIT huggingface

@@ -2808,95 +3012,115 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas
networkx (πŸ₯‡44 Β· ⭐ 10K) - Network Analysis in Python. BSD-3 -- [GitHub](https://github.com/networkx/networkx) (πŸ‘¨β€πŸ’» 560 Β· πŸ”€ 2.5K Β· πŸ“₯ 57 Β· πŸ“¦ 95K Β· πŸ“‹ 2.8K - 11% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/networkx/networkx) (πŸ‘¨β€πŸ’» 570 Β· πŸ”€ 2.5K Β· πŸ“₯ 57 Β· πŸ“¦ 98K Β· πŸ“‹ 2.8K - 12% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/networkx/networkx ``` -- [PyPi](https://pypi.org/project/networkx) (πŸ“₯ 14M / month Β· πŸ“¦ 13K Β· ⏱️ 15.12.2021): +- [PyPi](https://pypi.org/project/networkx) (πŸ“₯ 16M / month Β· πŸ“¦ 13K Β· ⏱️ 15.12.2021): ``` pip install networkx ``` -- [Conda](https://anaconda.org/conda-forge/networkx) (πŸ“₯ 5.3M Β· ⏱️ 26.10.2021): +- [Conda](https://anaconda.org/conda-forge/networkx) (πŸ“₯ 5.5M Β· ⏱️ 26.10.2021): ``` conda install -c conda-forge networkx ```
PyTorch Geometric (πŸ₯‡35 Β· ⭐ 14K) - Graph Neural Network Library for PyTorch. MIT -- [GitHub](https://github.com/pyg-team/pytorch_geometric) (πŸ‘¨β€πŸ’» 230 Β· πŸ”€ 2.3K Β· πŸ“‹ 2.4K - 36% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/pyg-team/pytorch_geometric) (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 2.4K Β· πŸ“‹ 2.4K - 37% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/rusty1s/pytorch_geometric + git clone https://github.com/pyg-team/pytorch_geometric ``` -- [PyPi](https://pypi.org/project/torch-geometric) (πŸ“₯ 40K / month Β· πŸ“¦ 31 Β· ⏱️ 22.12.2021): +- [PyPi](https://pypi.org/project/torch-geometric) (πŸ“₯ 45K / month Β· πŸ“¦ 33 Β· ⏱️ 22.12.2021): ``` pip install torch-geometric ``` +- [Conda](https://anaconda.org/conda-forge/pytorch_geometric) (πŸ“₯ 5.6K Β· ⏱️ 19.01.2022): + ``` + conda install -c conda-forge pytorch_geometric + ```
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dgl (πŸ₯‡35 Β· ⭐ 8.8K) - Python package built to ease deep learning on graph, on top of existing.. Apache-2 +
dgl (πŸ₯‡35 Β· ⭐ 8.9K) - Python package built to ease deep learning on graph, on top of existing.. Apache-2 -- [GitHub](https://github.com/dmlc/dgl) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 1.9K Β· πŸ“‹ 1.3K - 22% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/dmlc/dgl) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 2K Β· πŸ“‹ 1.4K - 24% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/dmlc/dgl ``` -- [PyPi](https://pypi.org/project/dgl) (πŸ“₯ 71K / month Β· πŸ“¦ 36 Β· ⏱️ 27.05.2021): +- [PyPi](https://pypi.org/project/dgl) (πŸ“₯ 64K / month Β· πŸ“¦ 39 Β· ⏱️ 27.05.2021): ``` pip install dgl ```
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StellarGraph (πŸ₯ˆ27 Β· ⭐ 2.3K) - StellarGraph - Machine Learning on Graphs. Apache-2 +
StellarGraph (πŸ₯ˆ28 Β· ⭐ 2.3K) - StellarGraph - Machine Learning on Graphs. Apache-2 -- [GitHub](https://github.com/stellargraph/stellargraph) (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 330 Β· πŸ“¦ 110 Β· πŸ“‹ 980 - 25% open Β· ⏱️ 29.10.2021): +- [GitHub](https://github.com/stellargraph/stellargraph) (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 340 Β· πŸ“¦ 120 Β· πŸ“‹ 990 - 25% open Β· ⏱️ 29.10.2021): ``` git clone https://github.com/stellargraph/stellargraph ``` -- [PyPi](https://pypi.org/project/stellargraph) (πŸ“₯ 12K / month Β· πŸ“¦ 3 Β· ⏱️ 30.06.2020): +- [PyPi](https://pypi.org/project/stellargraph) (πŸ“₯ 40K / month Β· πŸ“¦ 3 Β· ⏱️ 30.06.2020): ``` pip install stellargraph ```
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ogb (πŸ₯ˆ27 Β· ⭐ 1.2K) - Benchmark datasets, data loaders, and evaluators for graph machine learning. MIT +
ogb (πŸ₯ˆ28 Β· ⭐ 1.2K) - Benchmark datasets, data loaders, and evaluators for graph machine learning. MIT -- [GitHub](https://github.com/snap-stanford/ogb) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 250 Β· πŸ“¦ 200 Β· ⏱️ 07.01.2022): +- [GitHub](https://github.com/snap-stanford/ogb) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 250 Β· πŸ“¦ 220 Β· πŸ“‹ 180 - 0% open Β· ⏱️ 14.01.2022): ``` git clone https://github.com/snap-stanford/ogb ``` -- [PyPi](https://pypi.org/project/ogb) (πŸ“₯ 7.1K / month Β· πŸ“¦ 13 Β· ⏱️ 29.09.2021): +- [PyPi](https://pypi.org/project/ogb) (πŸ“₯ 25K / month Β· πŸ“¦ 13 Β· ⏱️ 29.09.2021): ``` pip install ogb ``` +- [Conda](https://anaconda.org/conda-forge/ogb) (πŸ“₯ 6.5K Β· ⏱️ 29.09.2021): + ``` + conda install -c conda-forge ogb + ```
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Paddle Graph Learning (πŸ₯ˆ27 Β· ⭐ 1.2K) - Paddle Graph Learning (PGL) is an efficient and.. Apache-2 +
Paddle Graph Learning (πŸ₯ˆ26 Β· ⭐ 1.2K) - Paddle Graph Learning (PGL) is an efficient and.. Apache-2 -- [GitHub](https://github.com/PaddlePaddle/PGL) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 190 Β· πŸ“¦ 23 Β· πŸ“‹ 100 - 36% open Β· ⏱️ 29.12.2021): +- [GitHub](https://github.com/PaddlePaddle/PGL) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 200 Β· πŸ“¦ 24 Β· πŸ“‹ 100 - 36% open Β· ⏱️ 29.12.2021): ``` git clone https://github.com/PaddlePaddle/PGL ``` -- [PyPi](https://pypi.org/project/pgl) (πŸ“₯ 1.3K / month Β· πŸ“¦ 2 Β· ⏱️ 20.12.2021): +- [PyPi](https://pypi.org/project/pgl) (πŸ“₯ 980 / month Β· πŸ“¦ 2 Β· ⏱️ 20.12.2021): ``` pip install pgl ```
+
PyKEEN (πŸ₯ˆ26 Β· ⭐ 700) - A Python library for learning and evaluating knowledge graph embeddings. MIT + +- [GitHub](https://github.com/pykeen/pykeen) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 99 Β· πŸ“₯ 92 Β· πŸ“‹ 350 - 32% open Β· ⏱️ 06.02.2022): + + ``` + git clone https://github.com/pykeen/pykeen + ``` +- [PyPi](https://pypi.org/project/pykeen) (πŸ“₯ 1.2K / month Β· πŸ“¦ 3 Β· ⏱️ 11.01.2022): + ``` + pip install pykeen + ``` +
Spektral (πŸ₯ˆ25 Β· ⭐ 2K) - Graph Neural Networks with Keras and Tensorflow 2. MIT -- [GitHub](https://github.com/danielegrattarola/spektral) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 260 Β· πŸ“¦ 91 Β· πŸ“‹ 200 - 18% open Β· ⏱️ 26.10.2021): +- [GitHub](https://github.com/danielegrattarola/spektral) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 270 Β· πŸ“¦ 100 Β· πŸ“‹ 200 - 17% open Β· ⏱️ 26.10.2021): ``` git clone https://github.com/danielegrattarola/spektral ``` -- [PyPi](https://pypi.org/project/spektral) (πŸ“₯ 3.6K / month Β· πŸ“¦ 2 Β· ⏱️ 23.08.2021): +- [PyPi](https://pypi.org/project/spektral) (πŸ“₯ 4.4K / month Β· πŸ“¦ 2 Β· ⏱️ 23.08.2021): ``` pip install spektral ```
pygraphistry (πŸ₯ˆ25 Β· ⭐ 1.5K) - PyGraphistry is a Python library to quickly load, shape,.. BSD-3 -- [GitHub](https://github.com/graphistry/pygraphistry) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 150 Β· πŸ“¦ 54 Β· πŸ“‹ 180 - 40% open Β· ⏱️ 22.12.2021): +- [GitHub](https://github.com/graphistry/pygraphistry) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 150 Β· πŸ“¦ 57 Β· πŸ“‹ 190 - 40% open Β· ⏱️ 22.12.2021): ``` git clone https://github.com/graphistry/pygraphistry @@ -2906,26 +3130,38 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install graphistry ```
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PyKEEN (πŸ₯ˆ25 Β· ⭐ 660) - A Python library for learning and evaluating knowledge graph embeddings. MIT +
pytorch_geometric_temporal (πŸ₯ˆ25 Β· ⭐ 1.3K) - PyTorch Geometric Temporal: Spatiotemporal Signal.. MIT -- [GitHub](https://github.com/pykeen/pykeen) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 96 Β· πŸ“₯ 92 Β· πŸ“‹ 340 - 33% open Β· ⏱️ 11.01.2022): +- [GitHub](https://github.com/benedekrozemberczki/pytorch_geometric_temporal) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 190 Β· πŸ“‹ 81 - 1% open Β· ⏱️ 03.02.2022): ``` - git clone https://github.com/pykeen/pykeen + git clone https://github.com/benedekrozemberczki/pytorch_geometric_temporal ``` -- [PyPi](https://pypi.org/project/pykeen) (πŸ“₯ 670 / month Β· πŸ“¦ 3 Β· ⏱️ 11.01.2022): +- [PyPi](https://pypi.org/project/torch-geometric-temporal) (πŸ“₯ 1.3K / month Β· πŸ“¦ 1 Β· ⏱️ 19.01.2022): ``` - pip install pykeen + pip install torch-geometric-temporal + ``` +
+
graph4nlp (πŸ₯ˆ24 Β· ⭐ 1.2K) - Graph4nlp is the library for the easy use of Graph Neural.. Apache-2 + +- [GitHub](https://github.com/graph4ai/graph4nlp) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 140 Β· πŸ“‹ 100 - 7% open Β· ⏱️ 20.01.2022): + + ``` + git clone https://github.com/graph4ai/graph4nlp + ``` +- [PyPi](https://pypi.org/project/graph4nlp) (πŸ“₯ 150 / month Β· ⏱️ 20.01.2022): + ``` + pip install graph4nlp ```
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Node2Vec (πŸ₯ˆ24 Β· ⭐ 830) - Implementation of the node2vec algorithm. MIT +
Node2Vec (πŸ₯ˆ24 Β· ⭐ 850) - Implementation of the node2vec algorithm. MIT - [GitHub](https://github.com/eliorc/node2vec) (πŸ‘¨β€πŸ’» 9 Β· πŸ”€ 190 Β· ⏱️ 09.10.2021): ``` git clone https://github.com/eliorc/node2vec ``` -- [PyPi](https://pypi.org/project/node2vec) (πŸ“₯ 520K / month Β· πŸ“¦ 14 Β· ⏱️ 09.10.2021): +- [PyPi](https://pypi.org/project/node2vec) (πŸ“₯ 540K / month Β· πŸ“¦ 14 Β· ⏱️ 09.10.2021): ``` pip install node2vec ``` @@ -2934,14 +3170,14 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas conda install -c conda-forge node2vec ```
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PyTorch-BigGraph (πŸ₯‰22 Β· ⭐ 3K) - Generate embeddings from large-scale graph-structured.. BSD-3 +
PyTorch-BigGraph (πŸ₯‰23 Β· ⭐ 3K) - Generate embeddings from large-scale graph-structured.. BSD-3 -- [GitHub](https://github.com/facebookresearch/PyTorch-BigGraph) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 400 Β· πŸ“₯ 120 Β· πŸ“‹ 170 - 31% open Β· ⏱️ 27.10.2021): +- [GitHub](https://github.com/facebookresearch/PyTorch-BigGraph) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 400 Β· πŸ“₯ 120 Β· πŸ“‹ 180 - 32% open Β· ⏱️ 07.02.2022): ``` git clone https://github.com/facebookresearch/PyTorch-BigGraph ``` -- [PyPi](https://pypi.org/project/torchbiggraph) (πŸ“₯ 1.2K / month Β· πŸ“¦ 3 Β· ⏱️ 01.05.2019): +- [PyPi](https://pypi.org/project/torchbiggraph) (πŸ“₯ 13K / month Β· πŸ“¦ 3 Β· ⏱️ 01.05.2019): ``` pip install torchbiggraph ``` @@ -2953,106 +3189,127 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas ``` git clone https://github.com/Accenture/AmpliGraph ``` -- [PyPi](https://pypi.org/project/ampligraph) (πŸ“₯ 720 / month Β· ⏱️ 25.05.2021): +- [PyPi](https://pypi.org/project/ampligraph) (πŸ“₯ 760 / month Β· ⏱️ 25.05.2021): ``` pip install ampligraph ```
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pytorch_geometric_temporal (πŸ₯‰22 Β· ⭐ 1.3K) - PyTorch Geometric Temporal: Spatiotemporal Signal.. MIT +
torch-cluster (πŸ₯‰21 Β· ⭐ 470) - PyTorch Extension Library of Optimized Graph Cluster.. MIT -- [GitHub](https://github.com/benedekrozemberczki/pytorch_geometric_temporal) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 180 Β· πŸ“‹ 74 - 6% open Β· ⏱️ 03.01.2022): +- [GitHub](https://github.com/rusty1s/pytorch_cluster) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 89 Β· πŸ“‹ 95 - 9% open Β· ⏱️ 03.02.2022): ``` - git clone https://github.com/benedekrozemberczki/pytorch_geometric_temporal + git clone https://github.com/rusty1s/pytorch_cluster ``` -- [PyPi](https://pypi.org/project/torch-geometric-temporal) (πŸ“₯ 830 / month Β· πŸ“¦ 1 Β· ⏱️ 31.12.2021): +- [PyPi](https://pypi.org/project/torch-cluster) (πŸ“₯ 10K / month Β· πŸ“¦ 26 Β· ⏱️ 01.03.2021): ``` - pip install torch-geometric-temporal + pip install torch-cluster + ``` +- [Conda](https://anaconda.org/conda-forge/pytorch_cluster) (πŸ“₯ 28K Β· ⏱️ 13.01.2022): + ``` + conda install -c conda-forge pytorch_cluster ```
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graph4nlp (πŸ₯‰21 Β· ⭐ 1.2K) - Graph4nlp is the library for the easy use of Graph Neural.. Apache-2 +
jraph (πŸ₯‰20 Β· ⭐ 820 Β· βž•) - A Graph Neural Network Library in Jax. Apache-2 -- [GitHub](https://github.com/graph4ai/graph4nlp) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 140 Β· πŸ“‹ 97 - 5% open Β· ⏱️ 27.09.2021): +- [GitHub](https://github.com/deepmind/jraph) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 45 Β· πŸ“¦ 11 Β· πŸ“‹ 18 - 50% open Β· ⏱️ 07.02.2022): ``` - git clone https://github.com/graph4ai/graph4nlp + git clone https://github.com/deepmind/jraph ``` -- [PyPi](https://pypi.org/project/graph4nlp) (πŸ“₯ 85 / month Β· ⏱️ 29.09.2021): +- [PyPi](https://pypi.org/project/jraph) (πŸ“₯ 1.2K / month Β· πŸ“¦ 2 Β· ⏱️ 19.11.2021): ``` - pip install graph4nlp + pip install jraph + ``` +- [Conda](https://anaconda.org/conda-forge/jraph) (πŸ“₯ 280 Β· ⏱️ 31.10.2021): + ``` + conda install -c conda-forge jraph ```
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torch-cluster (πŸ₯‰20 Β· ⭐ 460) - PyTorch Extension Library of Optimized Graph Cluster.. MIT +
deepsnap (πŸ₯‰20 Β· ⭐ 390 Β· βž•) - Python library assists deep learning on graphs. MIT -- [GitHub](https://github.com/rusty1s/pytorch_cluster) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 88 Β· πŸ“‹ 93 - 9% open Β· ⏱️ 28.12.2021): +- [GitHub](https://github.com/snap-stanford/deepsnap) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 43 Β· πŸ“₯ 8 Β· πŸ“¦ 15 Β· πŸ“‹ 36 - 36% open Β· ⏱️ 19.09.2021): ``` - git clone https://github.com/rusty1s/pytorch_cluster + git clone https://github.com/snap-stanford/deepsnap ``` -- [PyPi](https://pypi.org/project/torch-cluster) (πŸ“₯ 7.7K / month Β· πŸ“¦ 26 Β· ⏱️ 01.03.2021): +- [PyPi](https://pypi.org/project/deepsnap) (πŸ“₯ 370 / month Β· πŸ“¦ 1 Β· ⏱️ 05.09.2021): ``` - pip install torch-cluster + pip install deepsnap ```
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AutoGL (πŸ₯‰19 Β· ⭐ 750) - An autoML framework & toolkit for machine learning on graphs. Apache-2 +
AutoGL (πŸ₯‰18 Β· ⭐ 760) - An autoML framework & toolkit for machine learning on graphs. Apache-2 -- [GitHub](https://github.com/THUMNLab/AutoGL) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 77 Β· πŸ“‹ 18 - 27% open Β· ⏱️ 31.12.2021): +- [GitHub](https://github.com/THUMNLab/AutoGL) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 80 Β· πŸ“‹ 18 - 27% open Β· ⏱️ 31.12.2021): ``` git clone https://github.com/THUMNLab/AutoGL ``` -- [PyPi](https://pypi.org/project/auto-graph-learning) (πŸ“₯ 35 / month Β· ⏱️ 23.12.2020): +- [PyPi](https://pypi.org/project/auto-graph-learning) (πŸ“₯ 15 / month Β· ⏱️ 23.12.2020): ``` pip install auto-graph-learning ```
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OpenKE (πŸ₯‰15 Β· ⭐ 2.9K Β· πŸ’€) - An Open-Source Package for Knowledge Embedding (KE). MIT +
kglib (πŸ₯‰16 Β· ⭐ 490) - Grakn Knowledge Graph Library (ML R&D). Apache-2 -- [GitHub](https://github.com/thunlp/OpenKE) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 840 Β· πŸ“‹ 380 - 17% open Β· ⏱️ 06.04.2021): +- [GitHub](https://github.com/vaticle/kglib) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 86 Β· πŸ“₯ 210 Β· πŸ“‹ 61 - 19% open Β· ⏱️ 22.10.2021): ``` - git clone https://github.com/thunlp/OpenKE + git clone https://github.com/vaticle/kglib + ``` +- [PyPi](https://pypi.org/project/grakn-kglib) (πŸ“₯ 90 / month Β· ⏱️ 19.08.2020): + ``` + pip install grakn-kglib ```
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kglib (πŸ₯‰15 Β· ⭐ 480) - Grakn Knowledge Graph Library (ML R&D). Apache-2 +
ptgnn (πŸ₯‰16 Β· ⭐ 300 Β· βž•) - A PyTorch Graph Neural Network Library. MIT -- [GitHub](https://github.com/vaticle/kglib) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 86 Β· πŸ“₯ 210 Β· πŸ“‹ 61 - 19% open Β· ⏱️ 22.10.2021): +- [GitHub](https://github.com/microsoft/ptgnn) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 36 Β· πŸ“¦ 1 Β· πŸ“‹ 7 - 28% open Β· ⏱️ 01.02.2022): ``` - git clone https://github.com/vaticle/kglib + git clone https://github.com/microsoft/ptgnn ``` -- [PyPi](https://pypi.org/project/grakn-kglib) (πŸ“₯ 89 / month Β· ⏱️ 19.08.2020): +- [PyPi](https://pypi.org/project/ptgnn) (πŸ“₯ 150 / month Β· ⏱️ 21.10.2021): ``` - pip install grakn-kglib + pip install ptgnn ```
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GraphVite (πŸ₯‰12 Β· ⭐ 990 Β· πŸ’€) - GraphVite: A General and High-performance Graph Embedding.. Apache-2 +
OpenKE (πŸ₯‰15 Β· ⭐ 2.9K Β· πŸ’€) - An Open-Source Package for Knowledge Embedding (KE). MIT -- [GitHub](https://github.com/DeepGraphLearning/graphvite) (πŸ‘¨β€πŸ’» 1 Β· πŸ”€ 130 Β· πŸ“‹ 92 - 39% open Β· ⏱️ 14.01.2021): +- [GitHub](https://github.com/thunlp/OpenKE) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 850 Β· πŸ“‹ 380 - 17% open Β· ⏱️ 06.04.2021): ``` - git clone https://github.com/DeepGraphLearning/graphvite + git clone https://github.com/thunlp/OpenKE ``` -- [Conda](https://anaconda.org/milagraph/graphvite) (πŸ“₯ 4.2K Β· ⏱️ 19.03.2020): +
+
GraphGym (πŸ₯‰14 Β· ⭐ 880 Β· βž•) - Platform for designing and evaluating Graph Neural Networks (GNN). MIT + +- [GitHub](https://github.com/snap-stanford/GraphGym) (πŸ‘¨β€πŸ’» 5 Β· πŸ”€ 100 Β· πŸ“₯ 8 Β· πŸ“¦ 2 Β· πŸ“‹ 25 - 12% open Β· ⏱️ 11.12.2021): + ``` - conda install -c milagraph graphvite + git clone https://github.com/snap-stanford/GraphGym + ``` +- [PyPi](https://pypi.org/project/graphgym) (πŸ“₯ 60 / month Β· ⏱️ 29.06.2021): + ``` + pip install graphgym ```
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Show 13 hidden projects... +
Show 14 hidden projects... -- igraph (πŸ₯‡31 Β· ⭐ 920) - Python interface for igraph. ❗️GPL-2.0 -- pygal (πŸ₯ˆ29 Β· ⭐ 2.4K) - PYthon svg GrAph plotting Library. ❗️LGPL-3.0 +- igraph (πŸ₯‡30 Β· ⭐ 930) - Python interface for igraph. ❗️GPL-2.0 +- pygal (πŸ₯ˆ28 Β· ⭐ 2.4K) - PYthon svg GrAph plotting Library. ❗️LGPL-3.0 - Karate Club (πŸ₯ˆ24 Β· ⭐ 1.5K) - Karate Club: An API Oriented Open-source Python Framework for.. ❗️GPL-3.0 - DeepWalk (πŸ₯‰21 Β· ⭐ 2.4K Β· πŸ’€) - DeepWalk - Deep Learning for Graphs. ❗️GPL-3.0 - graph-nets (πŸ₯‰20 Β· ⭐ 5.1K Β· πŸ’€) - Build Graph Nets in Tensorflow. Apache-2 - DIG (πŸ₯‰20 Β· ⭐ 1K) - A library for graph deep learning research. ❗️GPL-3.0 -- Sematch (πŸ₯‰17 Β· ⭐ 370 Β· πŸ’€) - semantic similarity framework for knowledge graph. Apache-2 -- DeepGraph (πŸ₯‰17 Β· ⭐ 250 Β· πŸ’€) - Analyze Data with Pandas-based Networks. Documentation:. BSD-3 +- Sematch (πŸ₯‰17 Β· ⭐ 380 Β· πŸ’€) - semantic similarity framework for knowledge graph. Apache-2 - Euler (πŸ₯‰16 Β· ⭐ 2.7K Β· πŸ’€) - A distributed graph deep learning framework. Apache-2 -- GraphEmbedding (πŸ₯‰16 Β· ⭐ 2.5K Β· πŸ’€) - Implementation and experiments of graph embedding.. MIT +- GraphEmbedding (πŸ₯‰16 Β· ⭐ 2.6K Β· πŸ’€) - Implementation and experiments of graph embedding.. MIT +- DeepGraph (πŸ₯‰16 Β· ⭐ 250 Β· πŸ’€) - Analyze Data with Pandas-based Networks. Documentation:. BSD-3 - pyRDF2Vec (πŸ₯‰16 Β· ⭐ 140) - Python Implementation and Extension of RDF2Vec. MIT -- GraphSAGE (πŸ₯‰14 Β· ⭐ 2.6K Β· πŸ’€) - Representation learning on large graphs using stochastic.. MIT -- OpenNE (πŸ₯‰14 Β· ⭐ 1.5K Β· πŸ’€) - An Open-Source Package for Network Embedding (NE). MIT +- GraphSAGE (πŸ₯‰15 Β· ⭐ 2.6K Β· πŸ’€) - Representation learning on large graphs using stochastic.. MIT +- OpenNE (πŸ₯‰15 Β· ⭐ 1.5K Β· πŸ’€) - An Open-Source Package for Network Embedding (NE). MIT +- GraphVite (πŸ₯‰12 Β· ⭐ 1K Β· πŸ’€) - GraphVite: A General and High-performance Graph Embedding System. Apache-2

@@ -3062,94 +3319,110 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas _Libraries for audio analysis, manipulation, transformation, and extraction, as well as speech recognition and music generation tasks._ -
espnet (πŸ₯‡35 Β· ⭐ 4.6K) - End-to-End Speech Processing Toolkit. Apache-2 +
espnet (πŸ₯‡35 Β· ⭐ 4.7K) - End-to-End Speech Processing Toolkit. Apache-2 -- [GitHub](https://github.com/espnet/espnet) (πŸ‘¨β€πŸ’» 220 Β· πŸ”€ 1.4K Β· πŸ“₯ 74 Β· πŸ“¦ 30 Β· πŸ“‹ 1.6K - 16% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/espnet/espnet) (πŸ‘¨β€πŸ’» 230 Β· πŸ”€ 1.5K Β· πŸ“₯ 74 Β· πŸ“¦ 32 Β· πŸ“‹ 1.7K - 18% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/espnet/espnet ``` -- [PyPi](https://pypi.org/project/espnet) (πŸ“₯ 2.9K / month Β· πŸ“¦ 1 Β· ⏱️ 31.12.2021): +- [PyPi](https://pypi.org/project/espnet) (πŸ“₯ 5.3K / month Β· πŸ“¦ 1 Β· ⏱️ 08.02.2022): ``` pip install espnet ```
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librosa (πŸ₯‡33 Β· ⭐ 4.9K) - Python library for audio and music analysis. ISC +
librosa (πŸ₯‡34 Β· ⭐ 5K) - Python library for audio and music analysis. ISC -- [GitHub](https://github.com/librosa/librosa) (πŸ‘¨β€πŸ’» 93 Β· πŸ”€ 780 Β· πŸ“‹ 930 - 3% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/librosa/librosa) (πŸ‘¨β€πŸ’» 93 Β· πŸ”€ 790 Β· πŸ“‹ 940 - 3% open Β· ⏱️ 07.02.2022): ``` git clone https://github.com/librosa/librosa ``` -- [PyPi](https://pypi.org/project/librosa) (πŸ“₯ 500K / month Β· πŸ“¦ 1.2K Β· ⏱️ 26.05.2021): +- [PyPi](https://pypi.org/project/librosa) (πŸ“₯ 540K / month Β· πŸ“¦ 1.2K Β· ⏱️ 07.02.2022): ``` pip install librosa ``` -- [Conda](https://anaconda.org/conda-forge/librosa) (πŸ“₯ 420K Β· ⏱️ 26.05.2021): +- [Conda](https://anaconda.org/conda-forge/librosa) (πŸ“₯ 430K Β· ⏱️ 07.02.2022): ``` conda install -c conda-forge librosa ```
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Magenta (πŸ₯‡32 Β· ⭐ 17K Β· πŸ’€) - Magenta: Music and Art Generation with Machine Intelligence. Apache-2 +
DeepSpeech (πŸ₯‡33 Β· ⭐ 19K Β· πŸ“ˆ) - DeepSpeech is an open source embedded (offline, on-.. MPL-2.0 -- [GitHub](https://github.com/magenta/magenta) (πŸ‘¨β€πŸ’» 150 Β· πŸ”€ 3.5K Β· πŸ“¦ 330 Β· πŸ“‹ 890 - 36% open Β· ⏱️ 30.06.2021): +- [GitHub](https://github.com/mozilla/DeepSpeech) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 3.3K Β· πŸ“₯ 790K Β· πŸ“¦ 660 Β· πŸ“‹ 2.1K - 5% open Β· ⏱️ 17.11.2021): ``` - git clone https://github.com/magenta/magenta + git clone https://github.com/mozilla/DeepSpeech ``` -- [PyPi](https://pypi.org/project/magenta) (πŸ“₯ 6.6K / month Β· πŸ“¦ 36 Β· ⏱️ 12.11.2020): +- [PyPi](https://pypi.org/project/deepspeech) (πŸ“₯ 8.4K / month Β· πŸ“¦ 35 Β· ⏱️ 19.12.2020): ``` - pip install magenta + pip install deepspeech + ``` +- [Conda](https://anaconda.org/conda-forge/deepspeech) (πŸ“₯ 340 Β· ⏱️ 29.07.2021): + ``` + conda install -c conda-forge deepspeech ```
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Pydub (πŸ₯‡32 Β· ⭐ 5.8K Β· πŸ’€) - Manipulate audio with a simple and easy high level interface. MIT +
torchaudio (πŸ₯‡33 Β· ⭐ 1.6K) - Data manipulation and transformation for audio signal.. BSD-2 -- [GitHub](https://github.com/jiaaro/pydub) (πŸ‘¨β€πŸ’» 90 Β· πŸ”€ 770 Β· πŸ“¦ 10K Β· πŸ“‹ 460 - 44% open Β· ⏱️ 08.06.2021): +- [GitHub](https://github.com/pytorch/audio) (πŸ‘¨β€πŸ’» 150 Β· πŸ”€ 380 Β· πŸ“‹ 600 - 25% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/jiaaro/pydub + git clone https://github.com/pytorch/audio ``` -- [PyPi](https://pypi.org/project/pydub) (πŸ“₯ 940K / month Β· πŸ“¦ 900 Β· ⏱️ 10.03.2021): +- [PyPi](https://pypi.org/project/torchaudio) (πŸ“₯ 310K / month Β· πŸ“¦ 120 Β· ⏱️ 27.01.2022): ``` - pip install pydub + pip install torchaudio ``` -- [Conda](https://anaconda.org/conda-forge/pydub) (πŸ“₯ 20K Β· ⏱️ 13.03.2021): +
+
Magenta (πŸ₯ˆ32 Β· ⭐ 17K Β· πŸ’€) - Magenta: Music and Art Generation with Machine Intelligence. Apache-2 + +- [GitHub](https://github.com/magenta/magenta) (πŸ‘¨β€πŸ’» 150 Β· πŸ”€ 3.5K Β· πŸ“¦ 330 Β· πŸ“‹ 890 - 36% open Β· ⏱️ 30.06.2021): + ``` - conda install -c conda-forge pydub + git clone https://github.com/magenta/magenta + ``` +- [PyPi](https://pypi.org/project/magenta) (πŸ“₯ 6.3K / month Β· πŸ“¦ 36 Β· ⏱️ 12.11.2020): + ``` + pip install magenta ```
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torchaudio (πŸ₯‡32 Β· ⭐ 1.5K Β· πŸ“‰) - Data manipulation and transformation for audio signal.. BSD-2 +
Pydub (πŸ₯ˆ32 Β· ⭐ 5.9K Β· πŸ’€) - Manipulate audio with a simple and easy high level interface. MIT -- [GitHub](https://github.com/pytorch/audio) (πŸ‘¨β€πŸ’» 150 Β· πŸ”€ 370 Β· πŸ“‹ 590 - 25% open Β· ⏱️ 08.01.2022): +- [GitHub](https://github.com/jiaaro/pydub) (πŸ‘¨β€πŸ’» 90 Β· πŸ”€ 780 Β· πŸ“¦ 11K Β· πŸ“‹ 460 - 44% open Β· ⏱️ 08.06.2021): ``` - git clone https://github.com/pytorch/audio + git clone https://github.com/jiaaro/pydub ``` -- [PyPi](https://pypi.org/project/torchaudio) (πŸ“₯ 240K / month Β· πŸ“¦ 100 Β· ⏱️ 15.12.2021): +- [PyPi](https://pypi.org/project/pydub) (πŸ“₯ 1.7M / month Β· πŸ“¦ 900 Β· ⏱️ 10.03.2021): ``` - pip install torchaudio + pip install pydub + ``` +- [Conda](https://anaconda.org/conda-forge/pydub) (πŸ“₯ 21K Β· ⏱️ 13.03.2021): + ``` + conda install -c conda-forge pydub ```
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speechbrain (πŸ₯ˆ31 Β· ⭐ 3.6K) - A PyTorch-based Speech Toolkit. Apache-2 +
speechbrain (πŸ₯ˆ32 Β· ⭐ 3.7K) - A PyTorch-based Speech Toolkit. Apache-2 -- [GitHub](https://github.com/speechbrain/speechbrain) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 640 Β· πŸ“¦ 110 Β· πŸ“‹ 560 - 19% open Β· ⏱️ 11.01.2022): +- [GitHub](https://github.com/speechbrain/speechbrain) (πŸ‘¨β€πŸ’» 150 Β· πŸ”€ 670 Β· πŸ“¦ 120 Β· πŸ“‹ 590 - 20% open Β· ⏱️ 24.01.2022): ``` git clone https://github.com/speechbrain/speechbrain ``` -- [PyPi](https://pypi.org/project/speechbrain) (πŸ“₯ 4.8K / month Β· πŸ“¦ 2 Β· ⏱️ 20.12.2021): +- [PyPi](https://pypi.org/project/speechbrain) (πŸ“₯ 6.4K / month Β· πŸ“¦ 2 Β· ⏱️ 20.12.2021): ``` pip install speechbrain ```
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SpeechRecognition (πŸ₯ˆ30 Β· ⭐ 6K) - Speech recognition module for Python, supporting several.. BSD-3 +
SpeechRecognition (πŸ₯ˆ31 Β· ⭐ 6.1K) - Speech recognition module for Python, supporting several.. BSD-3 -- [GitHub](https://github.com/Uberi/speech_recognition) (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 2K Β· πŸ“‹ 510 - 45% open Β· ⏱️ 14.12.2021): +- [GitHub](https://github.com/Uberi/speech_recognition) (πŸ‘¨β€πŸ’» 42 Β· πŸ”€ 2K Β· πŸ“‹ 510 - 45% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/Uberi/speech_recognition ``` -- [PyPi](https://pypi.org/project/SpeechRecognition) (πŸ“₯ 250K / month Β· πŸ“¦ 670 Β· ⏱️ 05.12.2017): +- [PyPi](https://pypi.org/project/SpeechRecognition) (πŸ“₯ 270K / month Β· πŸ“¦ 670 Β· ⏱️ 05.12.2017): ``` pip install SpeechRecognition ``` @@ -3158,38 +3431,42 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as conda install -c conda-forge speechrecognition ```
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pyAudioAnalysis (πŸ₯ˆ30 Β· ⭐ 4.5K) - Python Audio Analysis Library: Feature Extraction,.. Apache-2 +
pyAudioAnalysis (πŸ₯ˆ30 Β· ⭐ 4.6K) - Python Audio Analysis Library: Feature Extraction,.. Apache-2 -- [GitHub](https://github.com/tyiannak/pyAudioAnalysis) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 1.1K Β· πŸ“¦ 250 Β· πŸ“‹ 290 - 60% open Β· ⏱️ 09.01.2022): +- [GitHub](https://github.com/tyiannak/pyAudioAnalysis) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 1.1K Β· πŸ“¦ 250 Β· πŸ“‹ 290 - 60% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/tyiannak/pyAudioAnalysis ``` -- [PyPi](https://pypi.org/project/pyAudioAnalysis) (πŸ“₯ 14K / month Β· πŸ“¦ 19 Β· ⏱️ 10.01.2022): +- [PyPi](https://pypi.org/project/pyAudioAnalysis) (πŸ“₯ 11K / month Β· πŸ“¦ 19 Β· ⏱️ 07.02.2022): ``` pip install pyAudioAnalysis ```
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Coqui TTS (πŸ₯ˆ29 Β· ⭐ 3.5K) - - a deep learning toolkit for Text-to-Speech, battle-.. MPL-2.0 +
Coqui TTS (πŸ₯ˆ29 Β· ⭐ 3.9K) - - a deep learning toolkit for Text-to-Speech, battle-.. MPL-2.0 -- [GitHub](https://github.com/coqui-ai/TTS) (πŸ‘¨β€πŸ’» 82 Β· πŸ”€ 290 Β· πŸ“₯ 63K Β· πŸ“‹ 200 - 10% open Β· ⏱️ 03.01.2022): +- [GitHub](https://github.com/coqui-ai/TTS) (πŸ‘¨β€πŸ’» 82 Β· πŸ”€ 340 Β· πŸ“₯ 69K Β· πŸ“‹ 220 - 13% open Β· ⏱️ 03.01.2022): ``` git clone https://github.com/coqui-ai/TTS ``` -- [PyPi](https://pypi.org/project/tts) (πŸ“₯ 3.8K / month Β· ⏱️ 14.07.2017): +- [PyPi](https://pypi.org/project/tts) (πŸ“₯ 4.6K / month Β· ⏱️ 14.07.2017): ``` pip install tts ``` +- [Conda](https://anaconda.org/conda-forge/tts) (πŸ“₯ 1.1K Β· ⏱️ 15.12.2021): + ``` + conda install -c conda-forge tts + ```
audioread (πŸ₯ˆ29 Β· ⭐ 390) - cross-library (GStreamer + Core Audio + MAD + FFmpeg) audio decoding.. MIT -- [GitHub](https://github.com/beetbox/audioread) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 89 Β· πŸ“¦ 7.1K Β· πŸ“‹ 77 - 40% open Β· ⏱️ 03.12.2021): +- [GitHub](https://github.com/beetbox/audioread) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 89 Β· πŸ“¦ 7.3K Β· πŸ“‹ 77 - 40% open Β· ⏱️ 03.12.2021): ``` git clone https://github.com/beetbox/audioread ``` -- [PyPi](https://pypi.org/project/audioread) (πŸ“₯ 470K / month Β· πŸ“¦ 320 Β· ⏱️ 20.10.2020): +- [PyPi](https://pypi.org/project/audioread) (πŸ“₯ 510K / month Β· πŸ“¦ 320 Β· ⏱️ 20.10.2020): ``` pip install audioread ``` @@ -3198,9 +3475,9 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as conda install -c conda-forge audioread ```
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spleeter (πŸ₯‰28 Β· ⭐ 18K) - Deezer source separation library including pretrained models. MIT +
spleeter (πŸ₯‰28 Β· ⭐ 19K) - Deezer source separation library including pretrained models. MIT -- [GitHub](https://github.com/deezer/spleeter) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 2K Β· πŸ“₯ 1.4M Β· πŸ“‹ 620 - 16% open Β· ⏱️ 08.12.2021): +- [GitHub](https://github.com/deezer/spleeter) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 2K Β· πŸ“₯ 1.4M Β· πŸ“‹ 640 - 17% open Β· ⏱️ 08.12.2021): ``` git clone https://github.com/deezer/spleeter @@ -3216,128 +3493,125 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as
Porcupine (πŸ₯‰28 Β· ⭐ 2.6K) - On-device wake word detection powered by deep learning. Apache-2 -- [GitHub](https://github.com/Picovoice/porcupine) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 380 Β· πŸ“¦ 7 Β· πŸ“‹ 360 - 1% open Β· ⏱️ 11.01.2022): +- [GitHub](https://github.com/Picovoice/porcupine) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 390 Β· πŸ“¦ 8 Β· πŸ“‹ 360 - 1% open Β· ⏱️ 06.02.2022): ``` git clone https://github.com/Picovoice/Porcupine ``` -- [PyPi](https://pypi.org/project/pvporcupine) (πŸ“₯ 1.7K / month Β· πŸ“¦ 8 Β· ⏱️ 21.12.2021): +- [PyPi](https://pypi.org/project/pvporcupine) (πŸ“₯ 2.2K / month Β· πŸ“¦ 8 Β· ⏱️ 04.02.2022): ``` pip install pvporcupine ```
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Madmom (πŸ₯‰28 Β· ⭐ 850) - Python audio and music signal processing library. BSD-3 +
Madmom (πŸ₯‰27 Β· ⭐ 860) - Python audio and music signal processing library. BSD-3 -- [GitHub](https://github.com/CPJKU/madmom) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 150 Β· πŸ“¦ 180 Β· πŸ“‹ 250 - 21% open Β· ⏱️ 06.01.2022): +- [GitHub](https://github.com/CPJKU/madmom) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 150 Β· πŸ“¦ 180 Β· πŸ“‹ 260 - 21% open Β· ⏱️ 06.01.2022): ``` git clone https://github.com/CPJKU/madmom ``` -- [PyPi](https://pypi.org/project/madmom) (πŸ“₯ 8.8K / month Β· πŸ“¦ 27 Β· ⏱️ 14.11.2018): +- [PyPi](https://pypi.org/project/madmom) (πŸ“₯ 7.6K / month Β· πŸ“¦ 27 Β· ⏱️ 14.11.2018): ``` pip install madmom ```
tinytag (πŸ₯‰27 Β· ⭐ 500) - Read audio and music meta data and duration of MP3, OGG, OPUS, MP4, M4A,.. MIT -- [GitHub](https://github.com/devsnd/tinytag) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 87 Β· πŸ“¦ 460 Β· πŸ“‹ 87 - 13% open Β· ⏱️ 17.12.2021): +- [GitHub](https://github.com/devsnd/tinytag) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 87 Β· πŸ“¦ 480 Β· πŸ“‹ 87 - 13% open Β· ⏱️ 17.12.2021): ``` git clone https://github.com/devsnd/tinytag ``` -- [PyPi](https://pypi.org/project/tinytag) (πŸ“₯ 14K / month Β· πŸ“¦ 67 Β· ⏱️ 14.12.2021): +- [PyPi](https://pypi.org/project/tinytag) (πŸ“₯ 26K / month Β· πŸ“¦ 67 Β· ⏱️ 14.12.2021): ``` pip install tinytag ```
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DDSP (πŸ₯‰26 Β· ⭐ 2K) - DDSP: Differentiable Digital Signal Processing. Apache-2 +
DDSP (πŸ₯‰26 Β· ⭐ 2.1K) - DDSP: Differentiable Digital Signal Processing. Apache-2 -- [GitHub](https://github.com/magenta/ddsp) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 210 Β· πŸ“¦ 19 Β· πŸ“‹ 130 - 17% open Β· ⏱️ 21.12.2021): +- [GitHub](https://github.com/magenta/ddsp) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 220 Β· πŸ“¦ 19 Β· πŸ“‹ 130 - 17% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/magenta/ddsp ``` -- [PyPi](https://pypi.org/project/ddsp) (πŸ“₯ 2.6K / month Β· πŸ“¦ 1 Β· ⏱️ 24.12.2021): +- [PyPi](https://pypi.org/project/ddsp) (πŸ“₯ 2K / month Β· πŸ“¦ 1 Β· ⏱️ 24.12.2021): ``` pip install ddsp ``` -
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kapre (πŸ₯‰25 Β· ⭐ 800) - kapre: Keras Audio Preprocessors. MIT - -- [GitHub](https://github.com/keunwoochoi/kapre) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 140 Β· πŸ“₯ 19 Β· πŸ“¦ 1.3K Β· πŸ“‹ 93 - 11% open Β· ⏱️ 14.11.2021): - - ``` - git clone https://github.com/keunwoochoi/kapre +- [Conda](https://anaconda.org/conda-forge/ddsp) (πŸ“₯ 10K Β· ⏱️ 08.06.2020): ``` -- [PyPi](https://pypi.org/project/kapre) (πŸ“₯ 1.5K / month Β· πŸ“¦ 14 Β· ⏱️ 14.11.2021): - ``` - pip install kapre + conda install -c conda-forge ddsp ```
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python-soundfile (πŸ₯‰25 Β· ⭐ 430) - SoundFile is an audio library based on libsndfile, CFFI, and.. BSD-3 +
audiomentations (πŸ₯‰25 Β· ⭐ 860) - A Python library for audio data augmentation. Inspired by.. MIT -- [GitHub](https://github.com/bastibe/python-soundfile) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 59 Β· πŸ“₯ 2.8K Β· πŸ“‹ 160 - 38% open Β· ⏱️ 07.12.2021): +- [GitHub](https://github.com/iver56/audiomentations) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 110 Β· πŸ“¦ 110 Β· πŸ“‹ 98 - 27% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/bastibe/python-soundfile + git clone https://github.com/iver56/audiomentations ``` -- [PyPi](https://pypi.org/project/soundfile) (πŸ“₯ 730K / month Β· πŸ“¦ 540 Β· ⏱️ 27.11.2019): +- [PyPi](https://pypi.org/project/audiomentations) (πŸ“₯ 2.8K / month Β· ⏱️ 10.02.2022): ``` - pip install soundfile + pip install audiomentations ```
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audiomentations (πŸ₯‰24 Β· ⭐ 830) - A Python library for audio data augmentation. Inspired by.. MIT +
kapre (πŸ₯‰24 Β· ⭐ 800) - kapre: Keras Audio Preprocessors. MIT -- [GitHub](https://github.com/iver56/audiomentations) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 100 Β· πŸ“¦ 100 Β· πŸ“‹ 91 - 27% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/keunwoochoi/kapre) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 140 Β· πŸ“₯ 19 Β· πŸ“¦ 1.4K Β· πŸ“‹ 94 - 12% open Β· ⏱️ 21.01.2022): ``` - git clone https://github.com/iver56/audiomentations + git clone https://github.com/keunwoochoi/kapre ``` -- [PyPi](https://pypi.org/project/audiomentations) (πŸ“₯ 2.5K / month Β· ⏱️ 18.11.2021): +- [PyPi](https://pypi.org/project/kapre) (πŸ“₯ 2.2K / month Β· πŸ“¦ 14 Β· ⏱️ 21.01.2022): ``` - pip install audiomentations + pip install kapre ```
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DeepSpeech (πŸ₯‰22 Β· ⭐ 18K) - DeepSpeech is an open source embedded (offline, on-device).. MPL-2.0 +
python-soundfile (πŸ₯‰24 Β· ⭐ 430) - SoundFile is an audio library based on libsndfile, CFFI, and.. BSD-3 -- [GitHub](https://github.com/mozilla/DeepSpeech) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 3.3K): +- [GitHub](https://github.com/bastibe/python-soundfile) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 59 Β· πŸ“₯ 2.9K Β· πŸ“‹ 160 - 38% open Β· ⏱️ 28.01.2022): ``` - git clone https://github.com/mozilla/DeepSpeech + git clone https://github.com/bastibe/python-soundfile ``` -- [PyPi](https://pypi.org/project/deepspeech) (πŸ“₯ 8.6K / month Β· πŸ“¦ 35 Β· ⏱️ 19.12.2020): +- [PyPi](https://pypi.org/project/soundfile) (πŸ“₯ 880K / month Β· πŸ“¦ 540 Β· ⏱️ 27.11.2019): ``` - pip install deepspeech + pip install soundfile + ``` +- [Conda](https://anaconda.org/anaconda/pysoundfile): + ``` + conda install -c anaconda pysoundfile ```
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TTS (πŸ₯‰22 Β· ⭐ 5.5K Β· πŸ’€) - Deep learning for Text to Speech (Discussion forum:.. MPL-2.0 +
TTS (πŸ₯‰22 Β· ⭐ 5.6K Β· πŸ’€) - Deep learning for Text to Speech (Discussion forum:.. MPL-2.0 -- [GitHub](https://github.com/mozilla/TTS) (πŸ‘¨β€πŸ’» 56 Β· πŸ”€ 860 Β· πŸ“₯ 1.6K Β· πŸ“‹ 520 - 2% open Β· ⏱️ 12.02.2021): +- [GitHub](https://github.com/mozilla/TTS) (πŸ‘¨β€πŸ’» 56 Β· πŸ”€ 870 Β· πŸ“₯ 1.8K Β· πŸ“‹ 530 - 3% open Β· ⏱️ 12.02.2021): ``` git clone https://github.com/mozilla/TTS ```
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nnAudio (πŸ₯‰21 Β· ⭐ 640) - Audio processing by using pytorch 1D convolution network. MIT +
nnAudio (πŸ₯‰21 Β· ⭐ 650) - Audio processing by using pytorch 1D convolution network. MIT -- [GitHub](https://github.com/KinWaiCheuk/nnAudio) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 61 Β· πŸ“¦ 39 Β· πŸ“‹ 48 - 22% open Β· ⏱️ 24.12.2021): +- [GitHub](https://github.com/KinWaiCheuk/nnAudio) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 62 Β· πŸ“¦ 41 Β· πŸ“‹ 49 - 24% open Β· ⏱️ 24.12.2021): ``` git clone https://github.com/KinWaiCheuk/nnAudio ``` -- [PyPi](https://pypi.org/project/nnAudio) (πŸ“₯ 850 / month Β· πŸ“¦ 1 Β· ⏱️ 24.12.2021): +- [PyPi](https://pypi.org/project/nnAudio) (πŸ“₯ 1.5K / month Β· πŸ“¦ 1 Β· ⏱️ 24.12.2021): ``` pip install nnAudio ```
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Show 6 hidden projects... +
Show 7 hidden projects... - aubio (πŸ₯ˆ29 Β· ⭐ 2.6K) - a library for audio and music analysis. ❗️GPL-3.0 - Essentia (πŸ₯‰28 Β· ⭐ 2K) - C++ library for audio and music analysis, description and.. ❗️AGPL-3.0 - python_speech_features (πŸ₯‰24 Β· ⭐ 2K Β· πŸ’€) - This library provides common speech features for ASR.. MIT - Dejavu (πŸ₯‰22 Β· ⭐ 5.6K Β· πŸ’€) - Audio fingerprinting and recognition in Python. MIT +- TimeSide (πŸ₯‰21 Β· ⭐ 310 Β· πŸ’€) - Scalable audio processing framework written in Python with a.. ❗️AGPL-3.0 - Muda (πŸ₯‰19 Β· ⭐ 200 Β· πŸ’€) - A library for augmenting annotated audio data. ISC -- Julius (πŸ₯‰16 Β· ⭐ 250) - Fast PyTorch based DSP for audio and 1D signals. MIT +- Julius (πŸ₯‰18 Β· ⭐ 250) - Fast PyTorch based DSP for audio and 1D signals. MIT

@@ -3349,80 +3623,64 @@ _Libraries to load, process, analyze, and write geographic data as well as libra
pydeck (πŸ₯‡42 Β· ⭐ 9.4K) - WebGL2 powered visualization framework. MIT -- [GitHub](https://github.com/visgl/deck.gl) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 1.7K Β· πŸ“¦ 3.4K Β· πŸ“‹ 2.3K - 5% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/visgl/deck.gl) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 1.7K Β· πŸ“¦ 3.6K Β· πŸ“‹ 2.4K - 5% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/visgl/deck.gl ``` -- [PyPi](https://pypi.org/project/pydeck) (πŸ“₯ 620K / month Β· πŸ“¦ 15 Β· ⏱️ 25.10.2021): +- [PyPi](https://pypi.org/project/pydeck) (πŸ“₯ 830K / month Β· πŸ“¦ 16 Β· ⏱️ 25.10.2021): ``` pip install pydeck ``` -- [Conda](https://anaconda.org/conda-forge/pydeck) (πŸ“₯ 65K Β· ⏱️ 26.10.2021): +- [Conda](https://anaconda.org/conda-forge/pydeck) (πŸ“₯ 68K Β· ⏱️ 26.10.2021): ``` conda install -c conda-forge pydeck ``` -- [npm](https://www.npmjs.com/package/deck.gl) (πŸ“₯ 200K / month Β· πŸ“¦ 380 Β· ⏱️ 30.12.2021): +- [npm](https://www.npmjs.com/package/deck.gl) (πŸ“₯ 290K / month Β· πŸ“¦ 380 Β· ⏱️ 10.02.2022): ``` - npm install deck.gl - ``` -
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Shapely (πŸ₯‡38 Β· ⭐ 2.6K) - Manipulation and analysis of geometric objects. BSD-3 - -- [GitHub](https://github.com/shapely/shapely) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 440 Β· πŸ“¦ 25K Β· πŸ“‹ 820 - 17% open Β· ⏱️ 13.01.2022): - - ``` - git clone https://github.com/Toblerity/Shapely - ``` -- [PyPi](https://pypi.org/project/shapely) (πŸ“₯ 5.5M / month Β· πŸ“¦ 3.6K Β· ⏱️ 25.10.2021): - ``` - pip install shapely - ``` -- [Conda](https://anaconda.org/conda-forge/shapely) (πŸ“₯ 3.1M Β· ⏱️ 20.11.2021): - ``` - conda install -c conda-forge shapely + npm install deck.gl ```
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Rasterio (πŸ₯‡37 Β· ⭐ 1.7K) - Rasterio reads and writes geospatial raster datasets. BSD-3 +
Shapely (πŸ₯‡37 Β· ⭐ 2.6K) - Manipulation and analysis of geometric objects. BSD-3 -- [GitHub](https://github.com/rasterio/rasterio) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 460 Β· πŸ“₯ 740 Β· πŸ“¦ 4.2K Β· πŸ“‹ 1.5K - 9% open Β· ⏱️ 06.01.2022): +- [GitHub](https://github.com/shapely/shapely) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 440 Β· πŸ“¦ 26K Β· πŸ“‹ 820 - 18% open Β· ⏱️ 07.02.2022): ``` - git clone https://github.com/mapbox/rasterio + git clone https://github.com/shapely/shapely ``` -- [PyPi](https://pypi.org/project/rasterio) (πŸ“₯ 620K / month Β· πŸ“¦ 730 Β· ⏱️ 15.10.2021): +- [PyPi](https://pypi.org/project/shapely) (πŸ“₯ 6.6M / month Β· πŸ“¦ 3.6K Β· ⏱️ 25.10.2021): ``` - pip install rasterio + pip install shapely ``` -- [Conda](https://anaconda.org/conda-forge/rasterio) (πŸ“₯ 1.4M Β· ⏱️ 04.01.2022): +- [Conda](https://anaconda.org/conda-forge/shapely) (πŸ“₯ 3.2M Β· ⏱️ 19.01.2022): ``` - conda install -c conda-forge rasterio + conda install -c conda-forge shapely ```
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folium (πŸ₯ˆ36 Β· ⭐ 5.6K) - Python Data. Leaflet.js Maps. MIT +
folium (πŸ₯‡36 Β· ⭐ 5.6K) - Python Data. Leaflet.js Maps. MIT - [GitHub](https://github.com/python-visualization/folium) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 2K Β· πŸ“¦ 14K Β· πŸ“‹ 920 - 22% open Β· ⏱️ 08.01.2022): ``` git clone https://github.com/python-visualization/folium ``` -- [PyPi](https://pypi.org/project/folium) (πŸ“₯ 680K / month Β· πŸ“¦ 630 Β· ⏱️ 19.11.2021): +- [PyPi](https://pypi.org/project/folium) (πŸ“₯ 720K / month Β· πŸ“¦ 630 Β· ⏱️ 19.11.2021): ``` pip install folium ``` -- [Conda](https://anaconda.org/conda-forge/folium) (πŸ“₯ 500K Β· ⏱️ 03.12.2021): +- [Conda](https://anaconda.org/conda-forge/folium) (πŸ“₯ 550K Β· ⏱️ 03.12.2021): ``` conda install -c conda-forge folium ```
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GeoPandas (πŸ₯ˆ36 Β· ⭐ 2.9K) - Python tools for geographic data. BSD-3 +
GeoPandas (πŸ₯‡36 Β· ⭐ 3K) - Python tools for geographic data. BSD-3 -- [GitHub](https://github.com/geopandas/geopandas) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 660 Β· πŸ“₯ 1.4K Β· πŸ“¦ 12K Β· πŸ“‹ 1.3K - 32% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/geopandas/geopandas) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 670 Β· πŸ“₯ 1.4K Β· πŸ“¦ 12K Β· πŸ“‹ 1.3K - 32% open Β· ⏱️ 08.02.2022): ``` git clone https://github.com/geopandas/geopandas ``` -- [PyPi](https://pypi.org/project/geopandas) (πŸ“₯ 1.8M / month Β· πŸ“¦ 1.1K Β· ⏱️ 16.10.2021): +- [PyPi](https://pypi.org/project/geopandas) (πŸ“₯ 2.3M / month Β· πŸ“¦ 1.1K Β· ⏱️ 16.10.2021): ``` pip install geopandas ``` @@ -3431,46 +3689,78 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge geopandas ```
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pyproj (πŸ₯ˆ35 Β· ⭐ 700) - Python interface to PROJ (cartographic projections and coordinate.. MIT +
Rasterio (πŸ₯‡36 Β· ⭐ 1.7K) - Rasterio reads and writes geospatial raster datasets. BSD-3 + +- [GitHub](https://github.com/rasterio/rasterio) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 460 Β· πŸ“₯ 740 Β· πŸ“¦ 4.3K Β· πŸ“‹ 1.5K - 10% open Β· ⏱️ 04.02.2022): + + ``` + git clone https://github.com/rasterio/rasterio + ``` +- [PyPi](https://pypi.org/project/rasterio) (πŸ“₯ 790K / month Β· πŸ“¦ 740 Β· ⏱️ 04.02.2022): + ``` + pip install rasterio + ``` +- [Conda](https://anaconda.org/conda-forge/rasterio) (πŸ“₯ 1.4M Β· ⏱️ 04.01.2022): + ``` + conda install -c conda-forge rasterio + ``` +
+
pyproj (πŸ₯ˆ35 Β· ⭐ 710) - Python interface to PROJ (cartographic projections and coordinate.. MIT -- [GitHub](https://github.com/pyproj4/pyproj) (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 170 Β· πŸ“¦ 12K Β· πŸ“‹ 460 - 1% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/pyproj4/pyproj) (πŸ‘¨β€πŸ’» 46 Β· πŸ”€ 170 Β· πŸ“¦ 13K Β· πŸ“‹ 460 - 1% open Β· ⏱️ 28.01.2022): ``` git clone https://github.com/pyproj4/pyproj ``` -- [PyPi](https://pypi.org/project/pyproj) (πŸ“₯ 3.5M / month Β· πŸ“¦ 1.6K Β· ⏱️ 18.11.2021): +- [PyPi](https://pypi.org/project/pyproj) (πŸ“₯ 4.2M / month Β· πŸ“¦ 1.6K Β· ⏱️ 18.11.2021): ``` pip install pyproj ``` -- [Conda](https://anaconda.org/conda-forge/pyproj) (πŸ“₯ 2.8M Β· ⏱️ 03.01.2022): +- [Conda](https://anaconda.org/conda-forge/pyproj) (πŸ“₯ 2.9M Β· ⏱️ 03.01.2022): ``` conda install -c conda-forge pyproj ```
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geopy (πŸ₯ˆ33 Β· ⭐ 3.5K) - Geocoding library for Python. MIT +
Fiona (πŸ₯ˆ34 Β· ⭐ 880) - Fiona reads and writes geographic data files. BSD-3 + +- [GitHub](https://github.com/Toblerity/Fiona) (πŸ‘¨β€πŸ’» 66 Β· πŸ”€ 180 Β· πŸ“¦ 7.7K Β· πŸ“‹ 660 - 11% open Β· ⏱️ 07.02.2022): + + ``` + git clone https://github.com/Toblerity/Fiona + ``` +- [PyPi](https://pypi.org/project/fiona) (πŸ“₯ 2.6M / month Β· πŸ“¦ 770 Β· ⏱️ 07.02.2022): + ``` + pip install fiona + ``` +- [Conda](https://anaconda.org/conda-forge/fiona) (πŸ“₯ 2.5M Β· ⏱️ 08.02.2022): + ``` + conda install -c conda-forge fiona + ``` +
+
geopy (πŸ₯ˆ33 Β· ⭐ 3.6K) - Geocoding library for Python. MIT -- [GitHub](https://github.com/geopy/geopy) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 560 Β· πŸ“¦ 32K Β· πŸ“‹ 250 - 9% open Β· ⏱️ 26.09.2021): +- [GitHub](https://github.com/geopy/geopy) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 560 Β· πŸ“¦ 33K Β· πŸ“‹ 250 - 9% open Β· ⏱️ 26.09.2021): ``` git clone https://github.com/geopy/geopy ``` -- [PyPi](https://pypi.org/project/geopy) (πŸ“₯ 2.8M / month Β· πŸ“¦ 3.9K Β· ⏱️ 11.07.2021): +- [PyPi](https://pypi.org/project/geopy) (πŸ“₯ 3.1M / month Β· πŸ“¦ 3.9K Β· ⏱️ 11.07.2021): ``` pip install geopy ``` -- [Conda](https://anaconda.org/conda-forge/geopy) (πŸ“₯ 640K Β· ⏱️ 12.07.2021): +- [Conda](https://anaconda.org/conda-forge/geopy) (πŸ“₯ 650K Β· ⏱️ 12.07.2021): ``` conda install -c conda-forge geopy ```
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ipyleaflet (πŸ₯ˆ32 Β· ⭐ 1.2K) - A Jupyter - Leaflet.js bridge. MIT +
ipyleaflet (πŸ₯‰32 Β· ⭐ 1.2K) - A Jupyter - Leaflet.js bridge. MIT -- [GitHub](https://github.com/jupyter-widgets/ipyleaflet) (πŸ‘¨β€πŸ’» 73 Β· πŸ”€ 320 Β· πŸ“¦ 1.4K Β· πŸ“‹ 470 - 38% open Β· ⏱️ 22.12.2021): +- [GitHub](https://github.com/jupyter-widgets/ipyleaflet) (πŸ‘¨β€πŸ’» 74 Β· πŸ”€ 320 Β· πŸ“¦ 1.4K Β· πŸ“‹ 470 - 38% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/jupyter-widgets/ipyleaflet ``` -- [PyPi](https://pypi.org/project/ipyleaflet) (πŸ“₯ 43K / month Β· πŸ“¦ 100 Β· ⏱️ 06.12.2021): +- [PyPi](https://pypi.org/project/ipyleaflet) (πŸ“₯ 56K / month Β· πŸ“¦ 100 Β· ⏱️ 06.12.2021): ``` pip install ipyleaflet ``` @@ -3478,51 +3768,51 @@ _Libraries to load, process, analyze, and write geographic data as well as libra ``` conda install -c conda-forge ipyleaflet ``` -- [npm](https://www.npmjs.com/package/jupyter-leaflet) (πŸ“₯ 36K / month Β· πŸ“¦ 2 Β· ⏱️ 06.12.2021): +- [npm](https://www.npmjs.com/package/jupyter-leaflet) (πŸ“₯ 45K / month Β· πŸ“¦ 2 Β· ⏱️ 06.12.2021): ``` npm install jupyter-leaflet ```
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Fiona (πŸ₯ˆ32 Β· ⭐ 880) - Fiona reads and writes geographic data files. BSD-3 +
ArcGIS API (πŸ₯‰30 Β· ⭐ 1.2K) - Documentation and samples for ArcGIS API for Python. Apache-2 -- [GitHub](https://github.com/Toblerity/Fiona) (πŸ‘¨β€πŸ’» 65 Β· πŸ”€ 180 Β· πŸ“¦ 7.5K Β· πŸ“‹ 650 - 12% open Β· ⏱️ 28.12.2021): +- [GitHub](https://github.com/Esri/arcgis-python-api) (πŸ‘¨β€πŸ’» 77 Β· πŸ”€ 870 Β· πŸ“₯ 1.7K Β· πŸ“‹ 420 - 29% open Β· ⏱️ 01.02.2022): ``` - git clone https://github.com/Toblerity/Fiona + git clone https://github.com/Esri/arcgis-python-api ``` -- [PyPi](https://pypi.org/project/fiona) (πŸ“₯ 2M / month Β· πŸ“¦ 770 Β· ⏱️ 31.05.2021): +- [PyPi](https://pypi.org/project/arcgis) (πŸ“₯ 48K / month Β· πŸ“¦ 22 Β· ⏱️ 03.02.2022): ``` - pip install fiona + pip install arcgis ``` -- [Conda](https://anaconda.org/conda-forge/fiona) (πŸ“₯ 2.5M Β· ⏱️ 01.12.2021): +- [Docker Hub](https://hub.docker.com/r/esridocker/arcgis-api-python-notebook) (πŸ“₯ 5.9K Β· ⭐ 33 Β· ⏱️ 04.02.2022): ``` - conda install -c conda-forge fiona + docker pull esridocker/arcgis-api-python-notebook ```
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ArcGIS API (πŸ₯‰29 Β· ⭐ 1.2K) - Documentation and samples for ArcGIS API for Python. Apache-2 +
PySAL (πŸ₯‰28 Β· ⭐ 970) - PySAL: Python Spatial Analysis Library Meta-Package. BSD-3 -- [GitHub](https://github.com/Esri/arcgis-python-api) (πŸ‘¨β€πŸ’» 74 Β· πŸ”€ 830 Β· πŸ“₯ 1.4K Β· πŸ“‹ 400 - 27% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/pysal/pysal) (πŸ‘¨β€πŸ’» 75 Β· πŸ”€ 270 Β· πŸ“‹ 610 - 1% open Β· ⏱️ 30.01.2022): ``` - git clone https://github.com/Esri/arcgis-python-api + git clone https://github.com/pysal/pysal ``` -- [PyPi](https://pypi.org/project/arcgis) (πŸ“₯ 48K / month Β· πŸ“¦ 18 Β· ⏱️ 04.10.2021): +- [PyPi](https://pypi.org/project/pysal) (πŸ“₯ 17K / month Β· πŸ“¦ 30 Β· ⏱️ 30.01.2022): ``` - pip install arcgis + pip install pysal ``` -- [Docker Hub](https://hub.docker.com/r/esridocker/arcgis-api-python-notebook) (πŸ“₯ 5.5K Β· ⭐ 33 Β· ⏱️ 05.10.2021): +- [Conda](https://anaconda.org/conda-forge/pysal) (πŸ“₯ 430K Β· ⏱️ 31.01.2022): ``` - docker pull esridocker/arcgis-api-python-notebook + conda install -c conda-forge pysal ```
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geojson (πŸ₯‰29 Β· ⭐ 680) - Python bindings and utilities for GeoJSON. BSD-3 +
geojson (πŸ₯‰28 Β· ⭐ 690) - Python bindings and utilities for GeoJSON. BSD-3 -- [GitHub](https://github.com/jazzband/geojson) (πŸ‘¨β€πŸ’» 46 Β· πŸ”€ 89 Β· πŸ“¦ 8.4K Β· πŸ“‹ 79 - 26% open Β· ⏱️ 03.01.2022): +- [GitHub](https://github.com/jazzband/geojson) (πŸ‘¨β€πŸ’» 46 Β· πŸ”€ 90 Β· πŸ“¦ 8.5K Β· πŸ“‹ 80 - 27% open Β· ⏱️ 03.01.2022): ``` git clone https://github.com/jazzband/geojson ``` -- [PyPi](https://pypi.org/project/geojson) (πŸ“₯ 520K / month Β· πŸ“¦ 1.1K Β· ⏱️ 09.08.2019): +- [PyPi](https://pypi.org/project/geojson) (πŸ“₯ 760K / month Β· πŸ“¦ 1.1K Β· ⏱️ 09.08.2019): ``` pip install geojson ``` @@ -3538,67 +3828,52 @@ _Libraries to load, process, analyze, and write geographic data as well as libra ``` git clone https://github.com/holoviz/geoviews ``` -- [PyPi](https://pypi.org/project/geoviews) (πŸ“₯ 8.8K / month Β· πŸ“¦ 25 Β· ⏱️ 25.12.2021): +- [PyPi](https://pypi.org/project/geoviews) (πŸ“₯ 13K / month Β· πŸ“¦ 25 Β· ⏱️ 25.12.2021): ``` pip install geoviews ``` -- [Conda](https://anaconda.org/conda-forge/geoviews) (πŸ“₯ 90K Β· ⏱️ 13.01.2022): +- [Conda](https://anaconda.org/conda-forge/geoviews) (πŸ“₯ 93K Β· ⏱️ 13.01.2022): ``` conda install -c conda-forge geoviews ```
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EarthPy (πŸ₯‰26 Β· ⭐ 320) - A package built to support working with spatial data using open source.. BSD-3 +
EarthPy (πŸ₯‰26 Β· ⭐ 330) - A package built to support working with spatial data using open source.. BSD-3 -- [GitHub](https://github.com/earthlab/earthpy) (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 120 Β· πŸ“¦ 120 Β· πŸ“‹ 220 - 7% open Β· ⏱️ 20.12.2021): +- [GitHub](https://github.com/earthlab/earthpy) (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 120 Β· πŸ“¦ 130 Β· πŸ“‹ 220 - 8% open Β· ⏱️ 20.12.2021): ``` git clone https://github.com/earthlab/earthpy ``` -- [PyPi](https://pypi.org/project/earthpy) (πŸ“₯ 5.7K / month Β· πŸ“¦ 7 Β· ⏱️ 01.10.2021): +- [PyPi](https://pypi.org/project/earthpy) (πŸ“₯ 4.8K / month Β· πŸ“¦ 7 Β· ⏱️ 01.10.2021): ``` pip install earthpy ``` -- [Conda](https://anaconda.org/conda-forge/earthpy) (πŸ“₯ 40K Β· ⏱️ 04.10.2021): +- [Conda](https://anaconda.org/conda-forge/earthpy) (πŸ“₯ 41K Β· ⏱️ 04.10.2021): ``` conda install -c conda-forge earthpy ```
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PySAL (πŸ₯‰25 Β· ⭐ 950) - PySAL: Python Spatial Analysis Library Meta-Package. BSD-3 - -- [GitHub](https://github.com/pysal/pysal) (πŸ‘¨β€πŸ’» 74 Β· πŸ”€ 270 Β· πŸ“‹ 600 - 1% open Β· ⏱️ 18.10.2021): - - ``` - git clone https://github.com/pysal/pysal - ``` -- [PyPi](https://pypi.org/project/pysal) (πŸ“₯ 23K / month Β· πŸ“¦ 30 Β· ⏱️ 01.08.2021): - ``` - pip install pysal - ``` -- [Conda](https://anaconda.org/conda-forge/pysal) (πŸ“₯ 430K Β· ⏱️ 02.08.2021): - ``` - conda install -c conda-forge pysal - ``` -
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Mapbox GL (πŸ₯‰24 Β· ⭐ 590 Β· πŸ’€) - Use Mapbox GL JS to visualize data in a Python Jupyter notebook. MIT +
Mapbox GL (πŸ₯‰24 Β· ⭐ 600 Β· πŸ’€) - Use Mapbox GL JS to visualize data in a Python Jupyter notebook. MIT - [GitHub](https://github.com/mapbox/mapboxgl-jupyter) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 130 Β· πŸ“¦ 120 Β· πŸ“‹ 100 - 34% open Β· ⏱️ 19.04.2021): ``` git clone https://github.com/mapbox/mapboxgl-jupyter ``` -- [PyPi](https://pypi.org/project/mapboxgl) (πŸ“₯ 13K / month Β· πŸ“¦ 14 Β· ⏱️ 02.06.2019): +- [PyPi](https://pypi.org/project/mapboxgl) (πŸ“₯ 17K / month Β· πŸ“¦ 14 Β· ⏱️ 02.06.2019): ``` pip install mapboxgl ```
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Show 6 hidden projects... +
Show 7 hidden projects... - Geocoder (πŸ₯ˆ33 Β· ⭐ 1.4K Β· πŸ’€) - Python Geocoder. MIT -- Satpy (πŸ₯‰30 Β· ⭐ 790) - Python package for earth-observing satellite data processing. ❗️GPL-3.0 -- Sentinelsat (πŸ₯‰29 Β· ⭐ 700) - Search and download Copernicus Sentinel satellite images. ❗️GPL-3.0 +- Satpy (πŸ₯‰30 Β· ⭐ 800) - Python package for earth-observing satellite data processing. ❗️GPL-3.0 +- Sentinelsat (πŸ₯‰29 Β· ⭐ 710) - Search and download Copernicus Sentinel satellite images. ❗️GPL-3.0 - gmaps (πŸ₯‰24 Β· ⭐ 730 Β· πŸ’€) - Google maps for Jupyter notebooks. BSD-3 -- pymap3d (πŸ₯‰23 Β· ⭐ 220) - pure-Python (Numpy optional) 3D coordinate conversions for geospace ecef.. BSD-2 - geoplotlib (πŸ₯‰21 Β· ⭐ 950 Β· πŸ’€) - python toolbox for visualizing geographical data and making maps. MIT +- pymap3d (πŸ₯‰21 Β· ⭐ 230) - pure-Python (Numpy optional) 3D coordinate conversions for geospace ecef.. BSD-2 +- prettymaps (πŸ₯‰18 Β· ⭐ 7.7K Β· βž•) - A small set of Python functions to draw pretty maps from.. ❗️AGPL-3.0

@@ -3608,54 +3883,58 @@ _Libraries to load, process, analyze, and write geographic data as well as libra _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, technical analysis, and other tasks on financial data._ -
yfinance (πŸ₯‡36 Β· ⭐ 6.3K) - Download market data from Yahoo! Finances API. Apache-2 +
yfinance (πŸ₯‡35 Β· ⭐ 6.6K) - Download market data from Yahoo! Finances API. Apache-2 -- [GitHub](https://github.com/ranaroussi/yfinance) (πŸ‘¨β€πŸ’» 51 Β· πŸ”€ 1.5K Β· πŸ“¦ 8.9K Β· πŸ“‹ 720 - 55% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/ranaroussi/yfinance) (πŸ‘¨β€πŸ’» 53 Β· πŸ”€ 1.5K Β· πŸ“¦ 9.4K Β· πŸ“‹ 740 - 55% open Β· ⏱️ 30.01.2022): ``` git clone https://github.com/ranaroussi/yfinance ``` -- [PyPi](https://pypi.org/project/yfinance) (πŸ“₯ 280K / month Β· πŸ“¦ 120 Β· ⏱️ 12.01.2022): +- [PyPi](https://pypi.org/project/yfinance) (πŸ“₯ 290K / month Β· πŸ“¦ 120 Β· ⏱️ 30.01.2022): ``` pip install yfinance ``` -- [Conda](https://anaconda.org/ranaroussi/yfinance) (πŸ“₯ 24K Β· ⏱️ 10.07.2021): +- [Conda](https://anaconda.org/ranaroussi/yfinance) (πŸ“₯ 29K Β· ⏱️ 10.07.2021): ``` conda install -c ranaroussi yfinance ```
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Qlib (πŸ₯‡30 Β· ⭐ 7.8K) - Qlib is an AI-oriented quantitative investment platform, which aims to.. MIT +
Qlib (πŸ₯‡31 Β· ⭐ 8K) - Qlib is an AI-oriented quantitative investment platform, which aims to.. MIT -- [GitHub](https://github.com/microsoft/qlib) (πŸ‘¨β€πŸ’» 78 Β· πŸ”€ 1.3K Β· πŸ“₯ 270 Β· πŸ“¦ 9 Β· πŸ“‹ 420 - 32% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/microsoft/qlib) (πŸ‘¨β€πŸ’» 81 Β· πŸ”€ 1.3K Β· πŸ“₯ 270 Β· πŸ“¦ 11 Β· πŸ“‹ 460 - 33% open Β· ⏱️ 07.02.2022): ``` git clone https://github.com/microsoft/qlib ``` -- [PyPi](https://pypi.org/project/pyqlib) (πŸ“₯ 3K / month Β· ⏱️ 07.12.2021): +- [PyPi](https://pypi.org/project/pyqlib) (πŸ“₯ 4.4K / month Β· ⏱️ 19.01.2022): ``` pip install pyqlib ```
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ta (πŸ₯‡30 Β· ⭐ 2.7K) - Technical Analysis Library using Pandas and Numpy. MIT +
ta (πŸ₯‡31 Β· ⭐ 2.8K) - Technical Analysis Library using Pandas and Numpy. MIT -- [GitHub](https://github.com/bukosabino/ta) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 650 Β· πŸ“¦ 940 Β· πŸ“‹ 200 - 53% open Β· ⏱️ 09.01.2022): +- [GitHub](https://github.com/bukosabino/ta) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 650 Β· πŸ“¦ 980 Β· πŸ“‹ 200 - 53% open Β· ⏱️ 27.01.2022): ``` git clone https://github.com/bukosabino/ta ``` -- [PyPi](https://pypi.org/project/ta) (πŸ“₯ 52K / month Β· πŸ“¦ 27 Β· ⏱️ 09.01.2022): +- [PyPi](https://pypi.org/project/ta) (πŸ“₯ 89K / month Β· πŸ“¦ 27 Β· ⏱️ 09.01.2022): ``` pip install ta ``` +- [Conda](https://anaconda.org/conda-forge/ta) (πŸ“₯ 2.2K Β· ⏱️ 12.01.2022): + ``` + conda install -c conda-forge ta + ```
IB-insync (πŸ₯ˆ29 Β· ⭐ 1.7K) - Python sync/async framework for Interactive Brokers API. BSD-2 -- [GitHub](https://github.com/erdewit/ib_insync) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 460 Β· πŸ“‹ 360 - 1% open Β· ⏱️ 06.01.2022): +- [GitHub](https://github.com/erdewit/ib_insync) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 470 Β· πŸ“‹ 370 - 1% open Β· ⏱️ 06.02.2022): ``` git clone https://github.com/erdewit/ib_insync ``` -- [PyPi](https://pypi.org/project/ib_insync) (πŸ“₯ 8.9K / month Β· πŸ“¦ 19 Β· ⏱️ 28.11.2021): +- [PyPi](https://pypi.org/project/ib_insync) (πŸ“₯ 9.8K / month Β· πŸ“¦ 19 Β· ⏱️ 28.11.2021): ``` pip install ib_insync ``` @@ -3671,72 +3950,88 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te ``` git clone https://github.com/RomelTorres/alpha_vantage ``` -- [PyPi](https://pypi.org/project/alpha_vantage) (πŸ“₯ 31K / month Β· πŸ“¦ 100 Β· ⏱️ 26.08.2018): +- [PyPi](https://pypi.org/project/alpha_vantage) (πŸ“₯ 22K / month Β· πŸ“¦ 100 Β· ⏱️ 26.08.2018): ``` pip install alpha_vantage ``` +- [Conda](https://anaconda.org/conda-forge/alpha_vantage) (πŸ“₯ 910 Β· ⏱️ 14.01.2021): + ``` + conda install -c conda-forge alpha_vantage + ```
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TensorTrade (πŸ₯‰26 Β· ⭐ 3.7K) - An open source reinforcement learning framework for training,.. Apache-2 +
TensorTrade (πŸ₯ˆ27 Β· ⭐ 3.7K) - An open source reinforcement learning framework for training,.. Apache-2 -- [GitHub](https://github.com/tensortrade-org/tensortrade) (πŸ‘¨β€πŸ’» 58 Β· πŸ”€ 830 Β· πŸ“¦ 29 Β· πŸ“‹ 200 - 12% open Β· ⏱️ 04.01.2022): +- [GitHub](https://github.com/tensortrade-org/tensortrade) (πŸ‘¨β€πŸ’» 60 Β· πŸ”€ 840 Β· πŸ“¦ 30 Β· πŸ“‹ 210 - 11% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/tensortrade-org/tensortrade ``` -- [PyPi](https://pypi.org/project/tensortrade) (πŸ“₯ 950 / month Β· πŸ“¦ 1 Β· ⏱️ 10.05.2021): +- [PyPi](https://pypi.org/project/tensortrade) (πŸ“₯ 990 / month Β· πŸ“¦ 1 Β· ⏱️ 10.05.2021): ``` pip install tensortrade ``` +- [Conda](https://anaconda.org/conda-forge/tensortrade) (πŸ“₯ 940 Β· ⏱️ 10.05.2021): + ``` + conda install -c conda-forge tensortrade + ```
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Enigma Catalyst (πŸ₯‰26 Β· ⭐ 2.3K) - An Algorithmic Trading Library for Crypto-Assets in Python. Apache-2 +
bt (πŸ₯ˆ27 Β· ⭐ 1.3K) - bt - flexible backtesting for Python. MIT -- [GitHub](https://github.com/scrtlabs/catalyst) (πŸ‘¨β€πŸ’» 150 Β· πŸ”€ 680 Β· πŸ“¦ 23 Β· πŸ“‹ 480 - 25% open Β· ⏱️ 22.09.2021): +- [GitHub](https://github.com/pmorissette/bt) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 300 Β· πŸ“¦ 93 Β· πŸ“‹ 280 - 18% open Β· ⏱️ 09.02.2022): ``` - git clone https://github.com/enigmampc/catalyst + git clone https://github.com/pmorissette/bt ``` -- [PyPi](https://pypi.org/project/enigma-catalyst) (πŸ“₯ 1.3K / month Β· πŸ“¦ 2 Β· ⏱️ 11.11.2018): +- [PyPi](https://pypi.org/project/bt) (πŸ“₯ 5.8K / month Β· πŸ“¦ 21 Β· ⏱️ 21.04.2021): ``` - pip install enigma-catalyst + pip install bt + ``` +- [Conda](https://anaconda.org/conda-forge/bt) (πŸ“₯ 2.9K Β· ⏱️ 18.01.2022): + ``` + conda install -c conda-forge bt ```
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stockstats (πŸ₯‰26 Β· ⭐ 930) - Supply a wrapper ``StockDataFrame`` based on the.. BSD-3 +
stockstats (πŸ₯‰26 Β· ⭐ 950) - Supply a wrapper ``StockDataFrame`` based on the.. BSD-3 -- [GitHub](https://github.com/jealous/stockstats) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 250 Β· πŸ“¦ 380 Β· πŸ“‹ 79 - 3% open Β· ⏱️ 07.01.2022): +- [GitHub](https://github.com/jealous/stockstats) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 250 Β· πŸ“¦ 400 Β· πŸ“‹ 79 - 3% open Β· ⏱️ 07.01.2022): ``` git clone https://github.com/jealous/stockstats ``` -- [PyPi](https://pypi.org/project/stockstats) (πŸ“₯ 11K / month Β· πŸ“¦ 29 Β· ⏱️ 07.01.2022): +- [PyPi](https://pypi.org/project/stockstats) (πŸ“₯ 9.2K / month Β· πŸ“¦ 29 Β· ⏱️ 07.01.2022): ``` pip install stockstats ```
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bt (πŸ₯‰25 Β· ⭐ 1.3K Β· πŸ’€) - bt - flexible backtesting for Python. MIT +
Enigma Catalyst (πŸ₯‰25 Β· ⭐ 2.3K) - An Algorithmic Trading Library for Crypto-Assets in Python. Apache-2 -- [GitHub](https://github.com/pmorissette/bt) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 290 Β· πŸ“¦ 91 Β· πŸ“‹ 270 - 17% open Β· ⏱️ 15.05.2021): +- [GitHub](https://github.com/scrtlabs/catalyst) (πŸ‘¨β€πŸ’» 150 Β· πŸ”€ 680 Β· πŸ“¦ 23 Β· πŸ“‹ 490 - 27% open Β· ⏱️ 22.09.2021): ``` - git clone https://github.com/pmorissette/bt + git clone https://github.com/scrtlabs/catalyst ``` -- [PyPi](https://pypi.org/project/bt) (πŸ“₯ 6.2K / month Β· πŸ“¦ 21 Β· ⏱️ 21.04.2021): +- [PyPi](https://pypi.org/project/enigma-catalyst) (πŸ“₯ 460 / month Β· πŸ“¦ 2 Β· ⏱️ 11.11.2018): ``` - pip install bt + pip install enigma-catalyst ```
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ffn (πŸ₯‰24 Β· ⭐ 1.1K Β· πŸ’€) - ffn - a financial function library for Python. MIT +
ffn (πŸ₯‰25 Β· ⭐ 1.1K) - ffn - a financial function library for Python. MIT -- [GitHub](https://github.com/pmorissette/ffn) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 200 Β· πŸ“¦ 160 Β· πŸ“‹ 96 - 16% open Β· ⏱️ 24.04.2021): +- [GitHub](https://github.com/pmorissette/ffn) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 200 Β· πŸ“¦ 160 Β· πŸ“‹ 96 - 16% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/pmorissette/ffn ``` -- [PyPi](https://pypi.org/project/ffn) (πŸ“₯ 27K / month Β· πŸ“¦ 25 Β· ⏱️ 21.04.2021): +- [PyPi](https://pypi.org/project/ffn) (πŸ“₯ 28K / month Β· πŸ“¦ 25 Β· ⏱️ 21.04.2021): ``` pip install ffn ``` +- [Conda](https://anaconda.org/conda-forge/ffn) (πŸ“₯ 640 Β· ⏱️ 22.04.2021): + ``` + conda install -c conda-forge ffn + ```
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Crypto Signals (πŸ₯‰21 Β· ⭐ 3.7K Β· πŸ’€) - Github.com/CryptoSignal - #1 Quant Trading & Technical.. MIT +
Crypto Signals (πŸ₯‰21 Β· ⭐ 3.8K Β· πŸ’€) - Github.com/CryptoSignal - #1 Quant Trading & Technical.. MIT - [GitHub](https://github.com/CryptoSignal/Crypto-Signal) (πŸ‘¨β€πŸ’» 28 Β· πŸ”€ 990 Β· πŸ“‹ 250 - 21% open Β· ⏱️ 28.06.2021): @@ -3748,19 +4043,19 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te docker pull shadowreaver/crypto-signal ```
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tf-quant-finance (πŸ₯‰21 Β· ⭐ 2.9K) - High-performance TensorFlow library for quantitative.. Apache-2 +
tf-quant-finance (πŸ₯‰21 Β· ⭐ 3K) - High-performance TensorFlow library for quantitative.. Apache-2 -- [GitHub](https://github.com/google/tf-quant-finance) (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 400 Β· πŸ“‹ 38 - 50% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/google/tf-quant-finance) (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 400 Β· πŸ“‹ 38 - 50% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/google/tf-quant-finance ``` -- [PyPi](https://pypi.org/project/tf-quant-finance) (πŸ“₯ 590 / month Β· πŸ“¦ 2 Β· ⏱️ 07.01.2022): +- [PyPi](https://pypi.org/project/tf-quant-finance) (πŸ“₯ 1K / month Β· πŸ“¦ 2 Β· ⏱️ 07.01.2022): ``` pip install tf-quant-finance ```
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finmarketpy (πŸ₯‰20 Β· ⭐ 2.8K) - Python library for backtesting trading strategies & analyzing.. Apache-2 +
finmarketpy (πŸ₯‰20 Β· ⭐ 2.9K) - Python library for backtesting trading strategies & analyzing.. Apache-2 - [GitHub](https://github.com/cuemacro/finmarketpy) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 450 Β· πŸ“₯ 40 Β· πŸ“¦ 4 Β· πŸ“‹ 26 - 88% open Β· ⏱️ 07.10.2021): @@ -3772,18 +4067,20 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install finmarketpy ```
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Show 10 hidden projects... +
Show 12 hidden projects... - zipline (πŸ₯‡33 Β· ⭐ 15K Β· πŸ’€) - Zipline, a Pythonic Algorithmic Trading Library. Apache-2 -- pyfolio (πŸ₯‡30 Β· ⭐ 4.2K Β· πŸ’€) - Portfolio and risk analytics in Python. Apache-2 -- arch (πŸ₯ˆ29 Β· ⭐ 850) - ARCH models in Python. ❗️NCSA -- backtrader (πŸ₯ˆ28 Β· ⭐ 8K) - Python Backtesting library for trading strategies. ❗️GPL-3.0 -- Alphalens (πŸ₯‰27 Β· ⭐ 2.2K Β· πŸ’€) - Performance analysis of predictive (alpha) stock factors. Apache-2 -- empyrical (πŸ₯‰26 Β· ⭐ 880 Β· πŸ’€) - Common financial risk and performance metrics. Used by zipline.. Apache-2 +- pyfolio (πŸ₯ˆ30 Β· ⭐ 4.3K Β· πŸ’€) - Portfolio and risk analytics in Python. Apache-2 +- backtrader (πŸ₯ˆ29 Β· ⭐ 8.2K Β· πŸ’€) - Python Backtesting library for trading strategies. ❗️GPL-3.0 +- arch (πŸ₯ˆ29 Β· ⭐ 860) - ARCH models in Python. ❗️NCSA +- Alphalens (πŸ₯ˆ27 Β· ⭐ 2.2K Β· πŸ’€) - Performance analysis of predictive (alpha) stock factors. Apache-2 +- empyrical (πŸ₯‰26 Β· ⭐ 890 Β· πŸ’€) - Common financial risk and performance metrics. Used by zipline.. Apache-2 - PyAlgoTrade (πŸ₯‰25 Β· ⭐ 3.6K Β· πŸ’€) - Python Algorithmic Trading Library. Apache-2 - FinTA (πŸ₯‰22 Β· ⭐ 1.4K) - Common financial technical indicators implemented in Pandas. ❗️LGPL-3.0 -- Backtesting.py (πŸ₯‰20 Β· ⭐ 2K) - Backtest trading strategies in Python. ❗️AGPL-3.0 +- Backtesting.py (πŸ₯‰20 Β· ⭐ 2.1K) - Backtest trading strategies in Python. ❗️AGPL-3.0 +- FinQuant (πŸ₯‰18 Β· ⭐ 720 Β· πŸ’€) - A program for financial portfolio management, analysis and.. MIT - surpriver (πŸ₯‰12 Β· ⭐ 1.4K Β· πŸ’€) - Find big moving stocks before they move using machine.. ❗️GPL-3.0 +- pyrtfolio (πŸ₯‰7 Β· ⭐ 100 Β· πŸ’€) - Python package to generate stock portfolios. ❗️GPL-3.0

@@ -3793,218 +4090,242 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te _Libraries for forecasting, anomaly detection, feature extraction, and machine learning on time-series and sequential data._ -
sktime (πŸ₯‡33 Β· ⭐ 4.8K) - A unified framework for machine learning with time series. BSD-3 +
sktime (πŸ₯‡33 Β· ⭐ 4.9K) - A unified framework for machine learning with time series. BSD-3 -- [GitHub](https://github.com/alan-turing-institute/sktime) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 720 Β· πŸ“₯ 64 Β· πŸ“¦ 320 Β· πŸ“‹ 870 - 34% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/alan-turing-institute/sktime) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 740 Β· πŸ“₯ 64 Β· πŸ“¦ 350 Β· πŸ“‹ 910 - 33% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/alan-turing-institute/sktime ``` -- [PyPi](https://pypi.org/project/sktime) (πŸ“₯ 120K / month Β· πŸ“¦ 19 Β· ⏱️ 08.12.2021): +- [PyPi](https://pypi.org/project/sktime) (πŸ“₯ 140K / month Β· πŸ“¦ 19 Β· ⏱️ 08.12.2021): ``` pip install sktime ``` +- [Conda](https://anaconda.org/conda-forge/sktime-all-extras) (πŸ“₯ 1.8K Β· ⏱️ 03.02.2022): + ``` + conda install -c conda-forge sktime-all-extras + ```
Prophet (πŸ₯‡32 Β· ⭐ 14K) - Tool for producing high quality forecasts for time series data that has.. MIT -- [GitHub](https://github.com/facebook/prophet) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 3.9K Β· πŸ“₯ 640 Β· πŸ“‹ 1.7K - 9% open Β· ⏱️ 07.01.2022): +- [GitHub](https://github.com/facebook/prophet) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 4K Β· πŸ“₯ 640 Β· πŸ“‹ 1.8K - 10% open Β· ⏱️ 31.01.2022): ``` git clone https://github.com/facebook/prophet ``` -- [PyPi](https://pypi.org/project/fbprophet) (πŸ“₯ 1.1M / month Β· πŸ“¦ 120 Β· ⏱️ 05.09.2020): +- [PyPi](https://pypi.org/project/fbprophet) (πŸ“₯ 1.3M / month Β· πŸ“¦ 120 Β· ⏱️ 05.09.2020): ``` pip install fbprophet ``` +- [Conda](https://anaconda.org/conda-forge/prophet) (πŸ“₯ 28K Β· ⏱️ 23.08.2021): + ``` + conda install -c conda-forge prophet + ```
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tsfresh (πŸ₯‡31 Β· ⭐ 6.1K) - Automatic extraction of relevant features from time series:. MIT +
tsfresh (πŸ₯‡31 Β· ⭐ 6.2K) - Automatic extraction of relevant features from time series:. MIT - [GitHub](https://github.com/blue-yonder/tsfresh) (πŸ‘¨β€πŸ’» 82 Β· πŸ”€ 960 Β· πŸ“‹ 480 - 8% open Β· ⏱️ 21.12.2021): ``` git clone https://github.com/blue-yonder/tsfresh ``` -- [PyPi](https://pypi.org/project/tsfresh) (πŸ“₯ 260K / month Β· πŸ“¦ 55 Β· ⏱️ 21.12.2021): +- [PyPi](https://pypi.org/project/tsfresh) (πŸ“₯ 400K / month Β· πŸ“¦ 55 Β· ⏱️ 21.12.2021): ``` pip install tsfresh ``` -- [Conda](https://anaconda.org/conda-forge/tsfresh) (πŸ“₯ 81K Β· ⏱️ 21.12.2021): +- [Conda](https://anaconda.org/conda-forge/tsfresh) (πŸ“₯ 94K Β· ⏱️ 21.12.2021): ``` conda install -c conda-forge tsfresh ```
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tslearn (πŸ₯‡31 Β· ⭐ 2K) - A machine learning toolkit dedicated to time-series data. BSD-2 +
pmdarima (πŸ₯‡31 Β· ⭐ 1.1K) - A statistical library designed to fill the void in Pythons time series.. MIT + +- [GitHub](https://github.com/alkaline-ml/pmdarima) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 190 Β· πŸ“¦ 1.7K Β· πŸ“‹ 270 - 9% open Β· ⏱️ 04.01.2022): + + ``` + git clone https://github.com/alkaline-ml/pmdarima + ``` +- [PyPi](https://pypi.org/project/pmdarima) (πŸ“₯ 1M / month Β· πŸ“¦ 44 Β· ⏱️ 05.11.2021): + ``` + pip install pmdarima + ``` +- [Conda](https://anaconda.org/conda-forge/pmdarima) (πŸ“₯ 29K Β· ⏱️ 15.11.2021): + ``` + conda install -c conda-forge pmdarima + ``` +
+
tslearn (πŸ₯ˆ30 Β· ⭐ 2K) - A machine learning toolkit dedicated to time-series data. BSD-2 -- [GitHub](https://github.com/tslearn-team/tslearn) (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 250 Β· πŸ“¦ 380 Β· πŸ“‹ 250 - 28% open Β· ⏱️ 06.12.2021): +- [GitHub](https://github.com/tslearn-team/tslearn) (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 260 Β· πŸ“¦ 400 Β· πŸ“‹ 250 - 29% open Β· ⏱️ 06.12.2021): ``` git clone https://github.com/tslearn-team/tslearn ``` -- [PyPi](https://pypi.org/project/tslearn) (πŸ“₯ 71K / month Β· πŸ“¦ 19 Β· ⏱️ 16.08.2021): +- [PyPi](https://pypi.org/project/tslearn) (πŸ“₯ 100K / month Β· πŸ“¦ 19 Β· ⏱️ 16.08.2021): ``` pip install tslearn ``` -- [Conda](https://anaconda.org/conda-forge/tslearn) (πŸ“₯ 250K Β· ⏱️ 16.08.2021): +- [Conda](https://anaconda.org/conda-forge/tslearn) (πŸ“₯ 250K Β· ⏱️ 15.01.2022): ``` conda install -c conda-forge tslearn ```
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pmdarima (πŸ₯‡31 Β· ⭐ 1.1K) - A statistical library designed to fill the void in Pythons time series.. MIT +
STUMPY (πŸ₯ˆ29 Β· ⭐ 2.1K) - STUMPY is a powerful and scalable Python library for modern time series.. BSD-3 -- [GitHub](https://github.com/alkaline-ml/pmdarima) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 190 Β· πŸ“¦ 1.7K Β· πŸ“‹ 260 - 8% open Β· ⏱️ 04.01.2022): +- [GitHub](https://github.com/TDAmeritrade/stumpy) (πŸ‘¨β€πŸ’» 28 Β· πŸ”€ 200 Β· πŸ“‹ 290 - 10% open Β· ⏱️ 08.02.2022): ``` - git clone https://github.com/alkaline-ml/pmdarima + git clone https://github.com/TDAmeritrade/stumpy ``` -- [PyPi](https://pypi.org/project/pmdarima) (πŸ“₯ 930K / month Β· πŸ“¦ 44 Β· ⏱️ 05.11.2021): +- [PyPi](https://pypi.org/project/stumpy) (πŸ“₯ 300K / month Β· πŸ“¦ 4 Β· ⏱️ 24.12.2021): ``` - pip install pmdarima + pip install stumpy + ``` +- [Conda](https://anaconda.org/conda-forge/stumpy) (πŸ“₯ 35K Β· ⏱️ 24.12.2021): + ``` + conda install -c conda-forge stumpy ```
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pytorch-forecasting (πŸ₯ˆ29 Β· ⭐ 1.6K) - Time series forecasting with PyTorch. MIT +
pytorch-forecasting (πŸ₯ˆ29 Β· ⭐ 1.7K) - Time series forecasting with PyTorch. MIT -- [GitHub](https://github.com/jdb78/pytorch-forecasting) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 240 Β· πŸ“‹ 370 - 37% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/jdb78/pytorch-forecasting) (πŸ‘¨β€πŸ’» 28 Β· πŸ”€ 260 Β· πŸ“‹ 390 - 39% open Β· ⏱️ 21.01.2022): ``` git clone https://github.com/jdb78/pytorch-forecasting ``` -- [PyPi](https://pypi.org/project/pytorch-forecasting) (πŸ“₯ 18K / month Β· πŸ“¦ 4 Β· ⏱️ 29.11.2021): +- [PyPi](https://pypi.org/project/pytorch-forecasting) (πŸ“₯ 25K / month Β· πŸ“¦ 4 Β· ⏱️ 29.11.2021): ``` pip install pytorch-forecasting ``` +- [Conda](https://anaconda.org/conda-forge/pytorch-forecasting) (πŸ“₯ 16K Β· ⏱️ 29.11.2021): + ``` + conda install -c conda-forge pytorch-forecasting + ```
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Darts (πŸ₯ˆ28 Β· ⭐ 3.3K) - A python library for easy manipulation and forecasting of time series. Apache-2 +
Darts (πŸ₯ˆ28 Β· ⭐ 3.7K) - A python library for easy manipulation and forecasting of time series. Apache-2 -- [GitHub](https://github.com/unit8co/darts) (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 300 Β· πŸ“¦ 24 Β· πŸ“‹ 310 - 37% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/unit8co/darts) (πŸ‘¨β€πŸ’» 43 Β· πŸ”€ 340 Β· πŸ“¦ 28 Β· πŸ“‹ 330 - 35% open Β· ⏱️ 08.02.2022): ``` git clone https://github.com/unit8co/darts ``` -- [PyPi](https://pypi.org/project/u8darts) (πŸ“₯ 2.7K / month Β· πŸ“¦ 2 Β· ⏱️ 24.12.2021): +- [PyPi](https://pypi.org/project/u8darts) (πŸ“₯ 5.1K / month Β· πŸ“¦ 2 Β· ⏱️ 24.01.2022): ``` pip install u8darts ``` -- [Docker Hub](https://hub.docker.com/r/unit8/darts) (πŸ“₯ 240 Β· ⏱️ 24.12.2021): +- [Conda](https://anaconda.org/conda-forge/u8darts-all) (πŸ“₯ 2K Β· ⏱️ 25.01.2022): + ``` + conda install -c conda-forge u8darts-all + ``` +- [Docker Hub](https://hub.docker.com/r/unit8/darts) (πŸ“₯ 260 Β· ⏱️ 24.01.2022): ``` docker pull unit8/darts ```
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GluonTS (πŸ₯ˆ28 Β· ⭐ 2.4K) - Probabilistic time series modeling in Python. Apache-2 +
GluonTS (πŸ₯ˆ28 Β· ⭐ 2.5K) - Probabilistic time series modeling in Python. Apache-2 -- [GitHub](https://github.com/awslabs/gluon-ts) (πŸ‘¨β€πŸ’» 82 Β· πŸ”€ 500 Β· πŸ“‹ 700 - 39% open Β· ⏱️ 06.01.2022): +- [GitHub](https://github.com/awslabs/gluon-ts) (πŸ‘¨β€πŸ’» 84 Β· πŸ”€ 500 Β· πŸ“‹ 700 - 39% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/awslabs/gluon-ts ``` -- [PyPi](https://pypi.org/project/gluonts) (πŸ“₯ 60K / month Β· πŸ“¦ 3 Β· ⏱️ 11.11.2021): +- [PyPi](https://pypi.org/project/gluonts) (πŸ“₯ 77K / month Β· πŸ“¦ 3 Β· ⏱️ 11.11.2021): ``` pip install gluonts ``` -
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STUMPY (πŸ₯ˆ28 Β· ⭐ 2K) - STUMPY is a powerful and scalable Python library for modern time series.. BSD-3 - -- [GitHub](https://github.com/TDAmeritrade/stumpy) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 190 Β· πŸ“‹ 280 - 11% open Β· ⏱️ 09.01.2022): - - ``` - git clone https://github.com/TDAmeritrade/stumpy - ``` -- [PyPi](https://pypi.org/project/stumpy) (πŸ“₯ 260K / month Β· πŸ“¦ 4 Β· ⏱️ 24.12.2021): - ``` - pip install stumpy - ``` -- [Conda](https://anaconda.org/conda-forge/stumpy) (πŸ“₯ 35K Β· ⏱️ 24.12.2021): +- [Conda](https://anaconda.org/anaconda/gluonts) (πŸ“₯ 2 Β· ⏱️ 14.10.2021): ``` - conda install -c conda-forge stumpy + conda install -c anaconda gluonts ```
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Streamz (πŸ₯‰27 Β· ⭐ 1K) - Real-time stream processing for python. BSD-3 +
Streamz (πŸ₯‰26 Β· ⭐ 1K) - Real-time stream processing for python. BSD-3 - [GitHub](https://github.com/python-streamz/streamz) (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 130 Β· πŸ“¦ 260 Β· πŸ“‹ 250 - 41% open Β· ⏱️ 24.12.2021): ``` git clone https://github.com/python-streamz/streamz ``` -- [PyPi](https://pypi.org/project/streamz) (πŸ“₯ 8.5K / month Β· πŸ“¦ 29 Β· ⏱️ 04.10.2021): +- [PyPi](https://pypi.org/project/streamz) (πŸ“₯ 11K / month Β· πŸ“¦ 29 Β· ⏱️ 04.10.2021): ``` pip install streamz ``` -- [Conda](https://anaconda.org/conda-forge/streamz) (πŸ“₯ 230K Β· ⏱️ 04.10.2021): +- [Conda](https://anaconda.org/conda-forge/streamz) (πŸ“₯ 240K Β· ⏱️ 04.10.2021): ``` conda install -c conda-forge streamz ```
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pyts (πŸ₯‰25 Β· ⭐ 1.1K) - A Python package for time series classification. BSD-3 +
pyts (πŸ₯‰25 Β· ⭐ 1.2K) - A Python package for time series classification. BSD-3 -- [GitHub](https://github.com/johannfaouzi/pyts) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 120 Β· πŸ“¦ 160 Β· πŸ“‹ 57 - 57% open Β· ⏱️ 09.12.2021): +- [GitHub](https://github.com/johannfaouzi/pyts) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 120 Β· πŸ“¦ 170 Β· πŸ“‹ 57 - 57% open Β· ⏱️ 09.12.2021): ``` git clone https://github.com/johannfaouzi/pyts ``` -- [PyPi](https://pypi.org/project/pyts) (πŸ“₯ 84K / month Β· πŸ“¦ 11 Β· ⏱️ 31.10.2021): +- [PyPi](https://pypi.org/project/pyts) (πŸ“₯ 110K / month Β· πŸ“¦ 11 Β· ⏱️ 31.10.2021): ``` pip install pyts ``` -- [Conda](https://anaconda.org/conda-forge/pyts) (πŸ“₯ 9.8K Β· ⏱️ 31.10.2021): +- [Conda](https://anaconda.org/conda-forge/pyts) (πŸ“₯ 10K Β· ⏱️ 31.10.2021): ``` conda install -c conda-forge pyts ```
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greykite (πŸ₯‰20 Β· ⭐ 1.4K) - A flexible, intuitive and fast forecasting library. BSD-2 +
greykite (πŸ₯‰21 Β· ⭐ 1.5K) - A flexible, intuitive and fast forecasting library. BSD-2 -- [GitHub](https://github.com/linkedin/greykite) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 63 Β· πŸ“¦ 8 Β· πŸ“‹ 57 - 12% open Β· ⏱️ 15.12.2021): +- [GitHub](https://github.com/linkedin/greykite) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 64 Β· πŸ“¦ 8 Β· πŸ“‹ 58 - 12% open Β· ⏱️ 15.12.2021): ``` git clone https://github.com/linkedin/greykite ``` -- [PyPi](https://pypi.org/project/greykite) (πŸ“₯ 6.9K / month Β· ⏱️ 15.12.2021): +- [PyPi](https://pypi.org/project/greykite) (πŸ“₯ 20K / month Β· ⏱️ 15.12.2021): ``` pip install greykite ```
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TSFEL (πŸ₯‰20 Β· ⭐ 360) - An intuitive library to extract features from time series. BSD-3 +
seglearn (πŸ₯‰20 Β· ⭐ 490 Β· πŸ’€) - Python module for machine learning time series:. BSD-3 -- [GitHub](https://github.com/fraunhoferportugal/tsfel) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 49 Β· πŸ“¦ 25 Β· πŸ“‹ 48 - 10% open Β· ⏱️ 23.12.2021): +- [GitHub](https://github.com/dmbee/seglearn) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 52 Β· πŸ“¦ 11 Β· πŸ“‹ 28 - 17% open Β· ⏱️ 12.03.2021): ``` - git clone https://github.com/fraunhoferportugal/tsfel + git clone https://github.com/dmbee/seglearn ``` -- [PyPi](https://pypi.org/project/tsfel) (πŸ“₯ 3.3K / month Β· ⏱️ 14.02.2021): +- [PyPi](https://pypi.org/project/seglearn) (πŸ“₯ 1.1K / month Β· πŸ“¦ 1 Β· ⏱️ 13.03.2021): ``` - pip install tsfel + pip install seglearn ```
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seglearn (πŸ₯‰19 Β· ⭐ 480 Β· πŸ’€) - Python module for machine learning time series:. BSD-3 +
Auto TS (πŸ₯‰20 Β· ⭐ 390) - Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost.. Apache-2 -- [GitHub](https://github.com/dmbee/seglearn) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 52 Β· πŸ“¦ 11 Β· πŸ“‹ 28 - 17% open Β· ⏱️ 12.03.2021): +- [GitHub](https://github.com/AutoViML/Auto_TS) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 69 Β· πŸ“‹ 62 - 9% open Β· ⏱️ 31.01.2022): ``` - git clone https://github.com/dmbee/seglearn + git clone https://github.com/AutoViML/Auto_TS ``` -- [PyPi](https://pypi.org/project/seglearn) (πŸ“₯ 1K / month Β· πŸ“¦ 1 Β· ⏱️ 13.03.2021): +- [PyPi](https://pypi.org/project/auto-ts) (πŸ“₯ 2.5K / month Β· ⏱️ 31.01.2022): ``` - pip install seglearn + pip install auto-ts ```
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Auto TS (πŸ₯‰19 Β· ⭐ 370) - Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost.. Apache-2 +
TSFEL (πŸ₯‰20 Β· ⭐ 380) - An intuitive library to extract features from time series. BSD-3 -- [GitHub](https://github.com/AutoViML/Auto_TS) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 67 Β· πŸ“‹ 61 - 14% open Β· ⏱️ 27.12.2021): +- [GitHub](https://github.com/fraunhoferportugal/tsfel) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 56 Β· πŸ“¦ 25 Β· πŸ“‹ 48 - 10% open Β· ⏱️ 23.12.2021): ``` - git clone https://github.com/AutoViML/Auto_TS + git clone https://github.com/fraunhoferportugal/tsfel ``` -- [PyPi](https://pypi.org/project/auto-ts) (πŸ“₯ 2.2K / month Β· ⏱️ 27.12.2021): +- [PyPi](https://pypi.org/project/tsfel) (πŸ“₯ 5.7K / month Β· ⏱️ 14.02.2021): ``` - pip install auto-ts + pip install tsfel ```
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atspy (πŸ₯‰14 Β· ⭐ 400) - AtsPy: Automated Time Series Models in Python (by @firmai). MIT +
atspy (πŸ₯‰14 Β· ⭐ 410) - AtsPy: Automated Time Series Models in Python (by @firmai). MIT - [GitHub](https://github.com/firmai/atspy) (πŸ‘¨β€πŸ’» 5 Β· πŸ”€ 80 Β· πŸ“¦ 5 Β· πŸ“‹ 20 - 90% open Β· ⏱️ 18.12.2021): ``` git clone https://github.com/firmai/atspy ``` -- [PyPi](https://pypi.org/project/atspy) (πŸ“₯ 1.1K / month Β· ⏱️ 24.04.2020): +- [PyPi](https://pypi.org/project/atspy) (πŸ“₯ 690 / month Β· ⏱️ 24.04.2020): ``` pip install atspy ``` @@ -4012,11 +4333,11 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l
Show 7 hidden projects... - PyFlux (πŸ₯‰24 Β· ⭐ 1.9K Β· πŸ’€) - Open source time series library for Python. BSD-3 -- luminol (πŸ₯‰21 Β· ⭐ 990 Β· πŸ’€) - Anomaly Detection and Correlation library. Apache-2 -- pydlm (πŸ₯‰20 Β· ⭐ 400 Β· πŸ’€) - A python library for Bayesian time series modeling. BSD-3 -- tick (πŸ₯‰20 Β· ⭐ 370 Β· πŸ’€) - Module for statistical learning, with a particular emphasis on time-.. BSD-3 +- luminol (πŸ₯‰21 Β· ⭐ 1K Β· πŸ’€) - Anomaly Detection and Correlation library. Apache-2 +- tick (πŸ₯‰21 Β· ⭐ 370 Β· πŸ’€) - Module for statistical learning, with a particular emphasis on time-.. BSD-3 +- pydlm (πŸ₯‰20 Β· ⭐ 410 Β· πŸ’€) - A python library for Bayesian time series modeling. BSD-3 +- ADTK (πŸ₯‰19 Β· ⭐ 770 Β· πŸ’€) - A Python toolkit for rule-based/unsupervised anomaly detection in time.. MPL-2.0 - matrixprofile-ts (πŸ₯‰19 Β· ⭐ 670 Β· πŸ’€) - A Python library for detecting patterns and anomalies.. Apache-2 -- ADTK (πŸ₯‰18 Β· ⭐ 770 Β· πŸ’€) - A Python toolkit for rule-based/unsupervised anomaly detection in time.. MPL-2.0 - tsaug (πŸ₯‰14 Β· ⭐ 220 Β· πŸ’€) - A Python package for time series augmentation. Apache-2

@@ -4029,12 +4350,12 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic
MNE (πŸ₯‡37 Β· ⭐ 1.8K) - MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python. BSD-3 -- [GitHub](https://github.com/mne-tools/mne-python) (πŸ‘¨β€πŸ’» 280 Β· πŸ”€ 970 Β· πŸ“¦ 1.3K Β· πŸ“‹ 3.9K - 9% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/mne-tools/mne-python) (πŸ‘¨β€πŸ’» 280 Β· πŸ”€ 970 Β· πŸ“¦ 1.4K Β· πŸ“‹ 3.9K - 9% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/mne-tools/mne-python ``` -- [PyPi](https://pypi.org/project/mne) (πŸ“₯ 24K / month Β· πŸ“¦ 190 Β· ⏱️ 01.12.2021): +- [PyPi](https://pypi.org/project/mne) (πŸ“₯ 30K / month Β· πŸ“¦ 190 Β· ⏱️ 01.12.2021): ``` pip install mne ``` @@ -4043,113 +4364,117 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic conda install -c conda-forge mne ```
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Nilearn (πŸ₯‡35 Β· ⭐ 800) - Machine learning for NeuroImaging in Python. BSD-3 +
Nilearn (πŸ₯‡35 Β· ⭐ 810) - Machine learning for NeuroImaging in Python. BSD-3 -- [GitHub](https://github.com/nilearn/nilearn) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 440 Β· πŸ“₯ 14 Β· πŸ“¦ 1.3K Β· πŸ“‹ 1.6K - 17% open Β· ⏱️ 10.01.2022): +- [GitHub](https://github.com/nilearn/nilearn) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 440 Β· πŸ“₯ 19 Β· πŸ“¦ 1.4K Β· πŸ“‹ 1.6K - 17% open Β· ⏱️ 07.02.2022): ``` git clone https://github.com/nilearn/nilearn ``` -- [PyPi](https://pypi.org/project/nilearn) (πŸ“₯ 16K / month Β· πŸ“¦ 230 Β· ⏱️ 16.09.2021): +- [PyPi](https://pypi.org/project/nilearn) (πŸ“₯ 19K / month Β· πŸ“¦ 230 Β· ⏱️ 28.01.2022): ``` pip install nilearn ``` -- [Conda](https://anaconda.org/conda-forge/nilearn) (πŸ“₯ 130K Β· ⏱️ 16.09.2021): +- [Conda](https://anaconda.org/conda-forge/nilearn) (πŸ“₯ 140K Β· ⏱️ 31.01.2022): ``` conda install -c conda-forge nilearn ```
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NIPYPE (πŸ₯ˆ34 Β· ⭐ 610) - Workflows and interfaces for neuroimaging packages. Apache-2 +
Hail (πŸ₯ˆ34 Β· ⭐ 780) - Scalable genomic data analysis. MIT -- [GitHub](https://github.com/nipy/nipype) (πŸ‘¨β€πŸ’» 230 Β· πŸ”€ 480 Β· πŸ“¦ 820 Β· πŸ“‹ 1.3K - 28% open Β· ⏱️ 15.12.2021): +- [GitHub](https://github.com/hail-is/hail) (πŸ‘¨β€πŸ’» 77 Β· πŸ”€ 200 Β· πŸ“¦ 47 Β· πŸ“‹ 2K - 2% open Β· ⏱️ 09.02.2022): ``` - git clone https://github.com/nipy/nipype - ``` -- [PyPi](https://pypi.org/project/nipype) (πŸ“₯ 29K / month Β· πŸ“¦ 150 Β· ⏱️ 20.10.2021): - ``` - pip install nipype + git clone https://github.com/hail-is/hail ``` -- [Conda](https://anaconda.org/conda-forge/nipype) (πŸ“₯ 460K Β· ⏱️ 20.10.2021): +- [PyPi](https://pypi.org/project/hail) (πŸ“₯ 180K / month Β· πŸ“¦ 6 Β· ⏱️ 01.02.2022): ``` - conda install -c conda-forge nipype + pip install hail ```
MONAI (πŸ₯ˆ33 Β· ⭐ 2.7K) - AI Toolkit for Healthcare Imaging. Apache-2 -- [GitHub](https://github.com/Project-MONAI/MONAI) (πŸ‘¨β€πŸ’» 84 Β· πŸ”€ 510 Β· πŸ“¦ 180 Β· πŸ“‹ 1.4K - 10% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/Project-MONAI/MONAI) (πŸ‘¨β€πŸ’» 85 Β· πŸ”€ 520 Β· πŸ“¦ 200 Β· πŸ“‹ 1.5K - 10% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/Project-MONAI/MONAI ``` -- [PyPi](https://pypi.org/project/monai) (πŸ“₯ 20K / month Β· πŸ“¦ 11 Β· ⏱️ 10.01.2022): +- [PyPi](https://pypi.org/project/monai) (πŸ“₯ 44K / month Β· πŸ“¦ 11 Β· ⏱️ 09.02.2022): ``` pip install monai ``` +- [Conda](https://anaconda.org/conda-forge/monai) (πŸ“₯ 90 Β· ⏱️ 09.01.2022): + ``` + conda install -c conda-forge monai + ```
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Hail (πŸ₯ˆ33 Β· ⭐ 770) - Scalable genomic data analysis. MIT +
NIPYPE (πŸ₯ˆ33 Β· ⭐ 620) - Workflows and interfaces for neuroimaging packages. Apache-2 -- [GitHub](https://github.com/hail-is/hail) (πŸ‘¨β€πŸ’» 77 Β· πŸ”€ 200 Β· πŸ“¦ 47 Β· πŸ“‹ 2K - 2% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/nipy/nipype) (πŸ‘¨β€πŸ’» 230 Β· πŸ”€ 480 Β· πŸ“¦ 840 Β· πŸ“‹ 1.3K - 28% open Β· ⏱️ 15.12.2021): ``` - git clone https://github.com/hail-is/hail + git clone https://github.com/nipy/nipype ``` -- [PyPi](https://pypi.org/project/hail) (πŸ“₯ 15K / month Β· πŸ“¦ 5 Β· ⏱️ 21.12.2021): +- [PyPi](https://pypi.org/project/nipype) (πŸ“₯ 43K / month Β· πŸ“¦ 150 Β· ⏱️ 20.10.2021): ``` - pip install hail + pip install nipype + ``` +- [Conda](https://anaconda.org/conda-forge/nipype) (πŸ“₯ 460K Β· ⏱️ 20.10.2021): + ``` + conda install -c conda-forge nipype ```
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Lifelines (πŸ₯ˆ31 Β· ⭐ 1.8K) - Survival analysis in Python. MIT +
NiBabel (πŸ₯ˆ33 Β· ⭐ 460) - Python package to access a cacophony of neuro-imaging file formats. MIT -- [GitHub](https://github.com/CamDavidsonPilon/lifelines) (πŸ‘¨β€πŸ’» 98 Β· πŸ”€ 450 Β· πŸ“¦ 750 Β· πŸ“‹ 840 - 25% open Β· ⏱️ 30.11.2021): +- [GitHub](https://github.com/nipy/nibabel) (πŸ‘¨β€πŸ’» 93 Β· πŸ”€ 230 Β· πŸ“¦ 6.3K Β· πŸ“‹ 450 - 30% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/CamDavidsonPilon/lifelines + git clone https://github.com/nipy/nibabel ``` -- [PyPi](https://pypi.org/project/lifelines) (πŸ“₯ 310K / month Β· πŸ“¦ 98 Β· ⏱️ 30.11.2021): +- [PyPi](https://pypi.org/project/nibabel) (πŸ“₯ 200K / month Β· πŸ“¦ 970 Β· ⏱️ 07.02.2022): ``` - pip install lifelines + pip install nibabel ``` -- [Conda](https://anaconda.org/conda-forge/lifelines) (πŸ“₯ 180K Β· ⏱️ 01.12.2021): +- [Conda](https://anaconda.org/conda-forge/nibabel) (πŸ“₯ 410K Β· ⏱️ 07.02.2022): ``` - conda install -c conda-forge lifelines + conda install -c conda-forge nibabel ```
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DIPY (πŸ₯ˆ31 Β· ⭐ 480) - DIPY is the paragon 3D/4D+ imaging library in Python. Contains generic.. BSD-3 +
Lifelines (πŸ₯ˆ32 Β· ⭐ 1.8K) - Survival analysis in Python. MIT -- [GitHub](https://github.com/dipy/dipy) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 330 Β· πŸ“¦ 490 Β· πŸ“‹ 760 - 16% open Β· ⏱️ 03.12.2021): +- [GitHub](https://github.com/CamDavidsonPilon/lifelines) (πŸ‘¨β€πŸ’» 99 Β· πŸ”€ 460 Β· πŸ“¦ 770 Β· πŸ“‹ 850 - 26% open Β· ⏱️ 19.01.2022): ``` - git clone https://github.com/dipy/dipy + git clone https://github.com/CamDavidsonPilon/lifelines ``` -- [PyPi](https://pypi.org/project/dipy) (πŸ“₯ 7.3K / month Β· πŸ“¦ 80 Β· ⏱️ 06.05.2021): +- [PyPi](https://pypi.org/project/lifelines) (πŸ“₯ 360K / month Β· πŸ“¦ 100 Β· ⏱️ 30.11.2021): ``` - pip install dipy + pip install lifelines ``` -- [Conda](https://anaconda.org/conda-forge/dipy) (πŸ“₯ 280K Β· ⏱️ 06.05.2021): +- [Conda](https://anaconda.org/conda-forge/lifelines) (πŸ“₯ 180K Β· ⏱️ 04.02.2022): ``` - conda install -c conda-forge dipy + conda install -c conda-forge lifelines ```
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NiBabel (πŸ₯ˆ31 Β· ⭐ 460) - Python package to access a cacophony of neuro-imaging file formats. MIT +
DIPY (πŸ₯ˆ30 Β· ⭐ 490) - DIPY is the paragon 3D/4D+ imaging library in Python. Contains generic.. BSD-3 -- [GitHub](https://github.com/nipy/nibabel) (πŸ‘¨β€πŸ’» 93 Β· πŸ”€ 220 Β· πŸ“¦ 6.1K Β· πŸ“‹ 440 - 29% open Β· ⏱️ 30.09.2021): +- [GitHub](https://github.com/dipy/dipy) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 330 Β· πŸ“¦ 490 Β· πŸ“‹ 760 - 16% open Β· ⏱️ 09.02.2022): ``` - git clone https://github.com/nipy/nibabel + git clone https://github.com/dipy/dipy ``` -- [PyPi](https://pypi.org/project/nibabel) (πŸ“₯ 140K / month Β· πŸ“¦ 960 Β· ⏱️ 28.11.2020): +- [PyPi](https://pypi.org/project/dipy) (πŸ“₯ 11K / month Β· πŸ“¦ 80 Β· ⏱️ 06.05.2021): ``` - pip install nibabel + pip install dipy ``` -- [Conda](https://anaconda.org/conda-forge/nibabel) (πŸ“₯ 400K Β· ⏱️ 29.11.2020): +- [Conda](https://anaconda.org/conda-forge/dipy) (πŸ“₯ 280K Β· ⏱️ 06.05.2021): ``` - conda install -c conda-forge nibabel + conda install -c conda-forge dipy ```
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DeepVariant (πŸ₯‰27 Β· ⭐ 2.4K) - DeepVariant is an analysis pipeline that uses a deep neural.. BSD-3 +
DeepVariant (πŸ₯‰26 Β· ⭐ 2.4K) - DeepVariant is an analysis pipeline that uses a deep neural.. BSD-3 -- [GitHub](https://github.com/google/deepvariant) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 580 Β· πŸ“₯ 3.8K Β· πŸ“‹ 450 - 1% open Β· ⏱️ 10.12.2021): +- [GitHub](https://github.com/google/deepvariant) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 580 Β· πŸ“₯ 3.8K Β· πŸ“‹ 460 - 1% open Β· ⏱️ 28.01.2022): ``` git clone https://github.com/google/deepvariant @@ -4159,14 +4484,14 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic conda install -c bioconda deepvariant ```
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NIPY (πŸ₯‰24 Β· ⭐ 310 Β· πŸ’€) - Neuroimaging in Python FMRI analysis package. BSD-3 +
NIPY (πŸ₯‰24 Β· ⭐ 320 Β· πŸ’€) - Neuroimaging in Python FMRI analysis package. BSD-3 - [GitHub](https://github.com/nipy/nipy) (πŸ‘¨β€πŸ’» 63 Β· πŸ”€ 130 Β· πŸ“‹ 160 - 28% open Β· ⏱️ 29.03.2021): ``` git clone https://github.com/nipy/nipy ``` -- [PyPi](https://pypi.org/project/nipy) (πŸ“₯ 1.1K / month Β· πŸ“¦ 47 Β· ⏱️ 19.02.2018): +- [PyPi](https://pypi.org/project/nipy) (πŸ“₯ 2.9K / month Β· πŸ“¦ 47 Β· ⏱️ 19.02.2018): ``` pip install nipy ``` @@ -4182,7 +4507,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic ``` git clone https://github.com/perone/medicaltorch ``` -- [PyPi](https://pypi.org/project/medicaltorch) (πŸ“₯ 130 / month Β· ⏱️ 24.11.2018): +- [PyPi](https://pypi.org/project/medicaltorch) (πŸ“₯ 120 / month Β· ⏱️ 24.11.2018): ``` pip install medicaltorch ``` @@ -4198,10 +4523,10 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic
Show 7 hidden projects... - NiftyNet (πŸ₯‰23 Β· ⭐ 1.3K Β· πŸ’€) - [unmaintained] An open-source convolutional neural.. Apache-2 -- DLTK (πŸ₯‰21 Β· ⭐ 1.3K Β· πŸ’€) - Deep Learning Toolkit for Medical Image Analysis. Apache-2 -- MedPy (πŸ₯‰21 Β· ⭐ 380 Β· πŸ’€) - Medical image processing in Python. ❗️GPL-3.0 +- DLTK (πŸ₯‰22 Β· ⭐ 1.3K Β· πŸ’€) - Deep Learning Toolkit for Medical Image Analysis. Apache-2 +- MedPy (πŸ₯‰21 Β· ⭐ 390 Β· πŸ’€) - Medical image processing in Python. ❗️GPL-3.0 - Brainiak (πŸ₯‰21 Β· ⭐ 260 Β· πŸ’€) - Brain Imaging Analysis Kit. Apache-2 -- Glow (πŸ₯‰21 Β· ⭐ 180) - An open-source toolkit for large-scale genomic analysis. Apache-2 +- Glow (πŸ₯‰21 Β· ⭐ 190) - An open-source toolkit for large-scale genomic analysis. Apache-2 - DeepNeuro (πŸ₯‰13 Β· ⭐ 110 Β· πŸ’€) - A deep learning python package for neuroimaging data. Made by:. MIT - MedicalNet (πŸ₯‰12 Β· ⭐ 1.3K Β· πŸ’€) - Many studies have shown that the performance on deep learning is.. MIT
@@ -4213,26 +4538,26 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic _Libraries for processing tabular and structured data._ -
pytorch_tabular (πŸ₯‡21 Β· ⭐ 510) - A standard framework for modelling Deep Learning Models.. MIT +
pytorch_tabular (πŸ₯‡21 Β· ⭐ 530) - A standard framework for modelling Deep Learning Models.. MIT -- [GitHub](https://github.com/manujosephv/pytorch_tabular) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 47 Β· πŸ“‹ 48 - 33% open Β· ⏱️ 03.01.2022): +- [GitHub](https://github.com/manujosephv/pytorch_tabular) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 52 Β· πŸ“‹ 51 - 31% open Β· ⏱️ 05.02.2022): ``` git clone https://github.com/manujosephv/pytorch_tabular ``` -- [PyPi](https://pypi.org/project/pytorch_tabular) (πŸ“₯ 1.4K / month Β· ⏱️ 01.09.2021): +- [PyPi](https://pypi.org/project/pytorch_tabular) (πŸ“₯ 1.3K / month Β· ⏱️ 01.09.2021): ``` pip install pytorch_tabular ```
-
carefree-learn (πŸ₯‰19 Β· ⭐ 360) - Deep Learning PyTorch. MIT +
carefree-learn (πŸ₯ˆ19 Β· ⭐ 360) - Deep Learning PyTorch. MIT -- [GitHub](https://github.com/carefree0910/carefree-learn) (πŸ‘¨β€πŸ’» 1 Β· πŸ”€ 30 Β· πŸ“¦ 2 Β· ⏱️ 04.01.2022): +- [GitHub](https://github.com/carefree0910/carefree-learn) (πŸ‘¨β€πŸ’» 1 Β· πŸ”€ 30 Β· πŸ“¦ 2 Β· ⏱️ 03.02.2022): ``` git clone https://github.com/carefree0910/carefree-learn ``` -- [PyPi](https://pypi.org/project/carefree-learn) (πŸ“₯ 52 / month Β· ⏱️ 29.10.2021): +- [PyPi](https://pypi.org/project/carefree-learn) (πŸ“₯ 160 / month Β· ⏱️ 29.10.2021): ``` pip install carefree-learn ``` @@ -4244,11 +4569,15 @@ _Libraries for processing tabular and structured data._ ``` git clone https://github.com/firmai/deltapy ``` -- [PyPi](https://pypi.org/project/deltapy) (πŸ“₯ 52 / month Β· ⏱️ 09.04.2020): +- [PyPi](https://pypi.org/project/deltapy) (πŸ“₯ 47 / month Β· ⏱️ 09.04.2020): ``` pip install deltapy ```
+
Show 1 hidden projects... + +- upgini (πŸ₯‰15 Β· ⭐ 21 Β· 🐣) - Automated feature discovery & enrichment library automatically find.. BSD-3 +

## Optical Character Recognition @@ -4259,19 +4588,19 @@ _Libraries for optical character recognition (OCR) and text extraction from imag
PaddleOCR (πŸ₯‡36 Β· ⭐ 19K) - Awesome multilingual OCR toolkits based on PaddlePaddle.. Apache-2 -- [GitHub](https://github.com/PaddlePaddle/PaddleOCR) (πŸ‘¨β€πŸ’» 85 Β· πŸ”€ 3.8K Β· πŸ“¦ 490 Β· πŸ“‹ 3.8K - 26% open Β· ⏱️ 10.01.2022): +- [GitHub](https://github.com/PaddlePaddle/PaddleOCR) (πŸ‘¨β€πŸ’» 85 Β· πŸ”€ 3.9K Β· πŸ“¦ 540 Β· πŸ“‹ 3.9K - 25% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/PaddlePaddle/PaddleOCR ``` -- [PyPi](https://pypi.org/project/paddleocr) (πŸ“₯ 28K / month Β· πŸ“¦ 4 Β· ⏱️ 10.01.2022): +- [PyPi](https://pypi.org/project/paddleocr) (πŸ“₯ 39K / month Β· πŸ“¦ 4 Β· ⏱️ 10.01.2022): ``` pip install paddleocr ```
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EasyOCR (πŸ₯‡33 Β· ⭐ 14K Β· πŸ“ˆ) - Ready-to-use OCR with 80+ supported languages and all popular.. Apache-2 +
EasyOCR (πŸ₯‡33 Β· ⭐ 14K) - Ready-to-use OCR with 80+ supported languages and all popular writing.. Apache-2 -- [GitHub](https://github.com/JaidedAI/EasyOCR) (πŸ‘¨β€πŸ’» 90 Β· πŸ”€ 1.8K Β· πŸ“₯ 980K Β· πŸ“¦ 810 Β· πŸ“‹ 480 - 31% open Β· ⏱️ 15.10.2021): +- [GitHub](https://github.com/JaidedAI/EasyOCR) (πŸ‘¨β€πŸ’» 91 Β· πŸ”€ 1.8K Β· πŸ“₯ 1.1M Β· πŸ“¦ 870 Β· πŸ“‹ 500 - 32% open Β· ⏱️ 14.01.2022): ``` git clone https://github.com/JaidedAI/EasyOCR @@ -4281,37 +4610,41 @@ _Libraries for optical character recognition (OCR) and text extraction from imag pip install easyocr ```
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Tesseract (πŸ₯ˆ32 Β· ⭐ 4K) - Python-tesseract is an optical character recognition (OCR) tool for.. Apache-2 +
Tesseract (πŸ₯‡33 Β· ⭐ 4K) - Python-tesseract is an optical character recognition (OCR) tool for.. Apache-2 -- [GitHub](https://github.com/madmaze/pytesseract) (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 560 Β· πŸ“‹ 280 - 3% open Β· ⏱️ 05.01.2022): +- [GitHub](https://github.com/madmaze/pytesseract) (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 570 Β· πŸ“‹ 290 - 4% open Β· ⏱️ 02.02.2022): ``` git clone https://github.com/madmaze/pytesseract ``` -- [PyPi](https://pypi.org/project/pytesseract) (πŸ“₯ 490K / month Β· πŸ“¦ 920 Β· ⏱️ 28.06.2021): +- [PyPi](https://pypi.org/project/pytesseract) (πŸ“₯ 520K / month Β· πŸ“¦ 920 Β· ⏱️ 28.06.2021): ``` pip install pytesseract ``` -- [Conda](https://anaconda.org/conda-forge/pytesseract) (πŸ“₯ 480K Β· ⏱️ 05.06.2021): +- [Conda](https://anaconda.org/conda-forge/pytesseract) (πŸ“₯ 490K Β· ⏱️ 26.01.2022): ``` conda install -c conda-forge pytesseract ```
-
OCRmyPDF (πŸ₯ˆ30 Β· ⭐ 5.8K) - OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them.. MPL-2.0 +
OCRmyPDF (πŸ₯ˆ30 Β· ⭐ 5.9K) - OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them.. MPL-2.0 -- [GitHub](https://github.com/ocrmypdf/OCRmyPDF) (πŸ‘¨β€πŸ’» 60 Β· πŸ”€ 520 Β· πŸ“‹ 790 - 11% open Β· ⏱️ 04.01.2022): +- [GitHub](https://github.com/ocrmypdf/OCRmyPDF) (πŸ‘¨β€πŸ’» 61 Β· πŸ”€ 540 Β· πŸ“‹ 810 - 10% open Β· ⏱️ 08.02.2022): ``` - git clone https://github.com/jbarlow83/OCRmyPDF + git clone https://github.com/ocrmypdf/OCRmyPDF ``` -- [PyPi](https://pypi.org/project/ocrmypdf) (πŸ“₯ 20K / month Β· πŸ“¦ 12 Β· ⏱️ 19.12.2021): +- [PyPi](https://pypi.org/project/ocrmypdf) (πŸ“₯ 23K / month Β· πŸ“¦ 12 Β· ⏱️ 26.01.2022): ``` pip install ocrmypdf ``` +- [Conda](https://anaconda.org/conda-forge/ocrmypdf) (πŸ“₯ 8.3K Β· ⏱️ 26.01.2022): + ``` + conda install -c conda-forge ocrmypdf + ```
tesserocr (πŸ₯ˆ27 Β· ⭐ 1.6K) - A Python wrapper for the tesseract-ocr API. MIT -- [GitHub](https://github.com/sirfz/tesserocr) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 200 Β· πŸ“¦ 600 Β· πŸ“‹ 240 - 32% open Β· ⏱️ 09.11.2021): +- [GitHub](https://github.com/sirfz/tesserocr) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 210 Β· πŸ“¦ 610 Β· πŸ“‹ 240 - 32% open Β· ⏱️ 09.11.2021): ``` git clone https://github.com/sirfz/tesserocr @@ -4320,50 +4653,54 @@ _Libraries for optical character recognition (OCR) and text extraction from imag ``` pip install tesserocr ``` -- [Conda](https://anaconda.org/conda-forge/tesserocr) (πŸ“₯ 63K Β· ⏱️ 13.01.2021): +- [Conda](https://anaconda.org/conda-forge/tesserocr) (πŸ“₯ 64K Β· ⏱️ 13.01.2021): ``` conda install -c conda-forge tesserocr ```
-
keras-ocr (πŸ₯‰21 Β· ⭐ 960) - A packaged and flexible version of the CRAFT text detector and.. MIT +
calamari (πŸ₯‰22 Β· ⭐ 900) - Line based ATR Engine based on OCRopy. Apache-2 -- [GitHub](https://github.com/faustomorales/keras-ocr) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 240 Β· πŸ“₯ 220K Β· πŸ“‹ 160 - 32% open Β· ⏱️ 24.11.2021): +- [GitHub](https://github.com/Calamari-OCR/calamari) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 190 Β· πŸ“‹ 230 - 16% open Β· ⏱️ 09.02.2022): ``` - git clone https://github.com/faustomorales/keras-ocr + git clone https://github.com/Calamari-OCR/calamari ``` -- [PyPi](https://pypi.org/project/keras-ocr) (πŸ“₯ 4.3K / month Β· πŸ“¦ 2 Β· ⏱️ 24.11.2021): +- [PyPi](https://pypi.org/project/calamari_ocr) (πŸ“₯ 650 / month Β· πŸ“¦ 2 Β· ⏱️ 13.11.2018): ``` - pip install keras-ocr + pip install calamari_ocr ```
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calamari (πŸ₯‰21 Β· ⭐ 890) - Line based ATR Engine based on OCRopy. Apache-2 +
keras-ocr (πŸ₯‰21 Β· ⭐ 970) - A packaged and flexible version of the CRAFT text detector and.. MIT -- [GitHub](https://github.com/Calamari-OCR/calamari) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 180 Β· πŸ“‹ 230 - 17% open Β· ⏱️ 20.12.2021): +- [GitHub](https://github.com/faustomorales/keras-ocr) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 240 Β· πŸ“₯ 220K Β· πŸ“‹ 160 - 33% open Β· ⏱️ 24.11.2021): ``` - git clone https://github.com/Calamari-OCR/calamari + git clone https://github.com/faustomorales/keras-ocr ``` -- [PyPi](https://pypi.org/project/calamari_ocr) (πŸ“₯ 550 / month Β· πŸ“¦ 2 Β· ⏱️ 13.11.2018): +- [PyPi](https://pypi.org/project/keras-ocr) (πŸ“₯ 6K / month Β· πŸ“¦ 2 Β· ⏱️ 24.11.2021): ``` - pip install calamari_ocr + pip install keras-ocr + ``` +- [Conda](https://anaconda.org/anaconda/keras-ocr) (πŸ“₯ 19 Β· ⏱️ 14.01.2022): + ``` + conda install -c anaconda keras-ocr ```
attention-ocr (πŸ₯‰21 Β· ⭐ 890) - A Tensorflow model for text recognition (CNN + seq2seq with.. MIT -- [GitHub](https://github.com/emedvedev/attention-ocr) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 240 Β· πŸ“¦ 18 Β· πŸ“‹ 150 - 14% open Β· ⏱️ 29.10.2021): +- [GitHub](https://github.com/emedvedev/attention-ocr) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 240 Β· πŸ“¦ 18 Β· πŸ“‹ 150 - 15% open Β· ⏱️ 29.10.2021): ``` git clone https://github.com/emedvedev/attention-ocr ``` -- [PyPi](https://pypi.org/project/aocr) (πŸ“₯ 190 / month Β· ⏱️ 19.04.2019): +- [PyPi](https://pypi.org/project/aocr) (πŸ“₯ 250 / month Β· ⏱️ 19.04.2019): ``` pip install aocr ```
Mozart (πŸ₯‰10 Β· ⭐ 350 Β· πŸ’€) - An optical music recognition (OMR) system. Converts sheet.. Apache-2 -- [GitHub](https://github.com/aashrafh/Mozart) (πŸ‘¨β€πŸ’» 5 Β· πŸ”€ 49 Β· πŸ“‹ 9 - 33% open Β· ⏱️ 05.05.2021): +- [GitHub](https://github.com/aashrafh/Mozart) (πŸ‘¨β€πŸ’» 5 Β· πŸ”€ 52 Β· πŸ“‹ 10 - 30% open Β· ⏱️ 05.05.2021): ``` git clone https://github.com/aashrafh/Mozart @@ -4372,7 +4709,7 @@ _Libraries for optical character recognition (OCR) and text extraction from imag
Show 2 hidden projects... - pdftabextract (πŸ₯‰19 Β· ⭐ 2K Β· πŸ’€) - A set of tools for extracting tables from PDF files.. Apache-2 -- doc2text (πŸ₯‰19 Β· ⭐ 1.3K Β· πŸ’€) - Detect text blocks and OCR poorly scanned PDFs in bulk. Python.. MIT +- doc2text (πŸ₯‰19 Β· ⭐ 1.2K Β· πŸ’€) - Detect text blocks and OCR poorly scanned PDFs in bulk. Python.. MIT

@@ -4382,162 +4719,178 @@ _Libraries for optical character recognition (OCR) and text extraction from imag _General-purpose data containers & structures as well as utilities & extensions for pandas._ -
pandas (πŸ₯‡52 Β· ⭐ 32K) - Flexible and powerful data analysis / manipulation library for.. BSD-3 +
pandas (πŸ₯‡52 Β· ⭐ 33K) - Flexible and powerful data analysis / manipulation library for.. BSD-3 -- [GitHub](https://github.com/pandas-dev/pandas) (πŸ‘¨β€πŸ’» 2.9K Β· πŸ”€ 14K Β· πŸ“₯ 130K Β· πŸ“¦ 610K Β· πŸ“‹ 22K - 15% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/pandas-dev/pandas) (πŸ‘¨β€πŸ’» 2.9K Β· πŸ”€ 14K Β· πŸ“₯ 140K Β· πŸ“¦ 630K Β· πŸ“‹ 22K - 15% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/pandas-dev/pandas ``` -- [PyPi](https://pypi.org/project/pandas) (πŸ“₯ 68M / month Β· πŸ“¦ 57K Β· ⏱️ 06.01.2022): +- [PyPi](https://pypi.org/project/pandas) (πŸ“₯ 76M / month Β· πŸ“¦ 57K Β· ⏱️ 22.01.2022): ``` pip install pandas ``` -- [Conda](https://anaconda.org/conda-forge/pandas) (πŸ“₯ 22M Β· ⏱️ 07.01.2022): +- [Conda](https://anaconda.org/conda-forge/pandas) (πŸ“₯ 23M Β· ⏱️ 22.01.2022): ``` conda install -c conda-forge pandas ```
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numpy (πŸ₯‡50 Β· ⭐ 19K) - The fundamental package for scientific computing with Python. BSD-3 +
numpy (πŸ₯‡50 Β· ⭐ 20K) - The fundamental package for scientific computing with Python. BSD-3 -- [GitHub](https://github.com/numpy/numpy) (πŸ‘¨β€πŸ’» 1.4K Β· πŸ”€ 6.3K Β· πŸ“₯ 440K Β· πŸ“¦ 940K Β· πŸ“‹ 10K - 22% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/numpy/numpy) (πŸ‘¨β€πŸ’» 1.4K Β· πŸ”€ 6.5K Β· πŸ“₯ 460K Β· πŸ“¦ 960K Β· πŸ“‹ 11K - 22% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/numpy/numpy ``` -- [PyPi](https://pypi.org/project/numpy) (πŸ“₯ 83M / month Β· πŸ“¦ 120K Β· ⏱️ 31.12.2021): +- [PyPi](https://pypi.org/project/numpy) (πŸ“₯ 96M / month Β· πŸ“¦ 120K Β· ⏱️ 04.02.2022): ``` pip install numpy ``` -- [Conda](https://anaconda.org/conda-forge/numpy) (πŸ“₯ 28M Β· ⏱️ 03.01.2022): +- [Conda](https://anaconda.org/conda-forge/numpy) (πŸ“₯ 28M Β· ⏱️ 04.02.2022): ``` conda install -c conda-forge numpy ```
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Arrow (πŸ₯‡43 Β· ⭐ 8.9K) - Apache Arrow is a multi-language toolbox for accelerated data.. Apache-2 +
Arrow (πŸ₯‡43 Β· ⭐ 9.1K) - Apache Arrow is a multi-language toolbox for accelerated data.. Apache-2 -- [GitHub](https://github.com/apache/arrow) (πŸ‘¨β€πŸ’» 790 Β· πŸ”€ 2.2K Β· πŸ“¦ 61 Β· πŸ“‹ 890 - 22% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/apache/arrow) (πŸ‘¨β€πŸ’» 800 Β· πŸ”€ 2.2K Β· πŸ“¦ 64 Β· πŸ“‹ 900 - 22% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/apache/arrow ``` -- [PyPi](https://pypi.org/project/pyarrow) (πŸ“₯ 33M / month Β· πŸ“¦ 1.3K Β· ⏱️ 18.11.2021): +- [PyPi](https://pypi.org/project/pyarrow) (πŸ“₯ 51M / month Β· πŸ“¦ 1.4K Β· ⏱️ 03.02.2022): ``` pip install pyarrow ``` -- [Conda](https://anaconda.org/conda-forge/arrow) (πŸ“₯ 860K Β· ⏱️ 26.10.2021): +- [Conda](https://anaconda.org/conda-forge/arrow) (πŸ“₯ 870K Β· ⏱️ 27.01.2022): ``` conda install -c conda-forge arrow ```
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h5py (πŸ₯ˆ40 Β· ⭐ 1.7K) - HDF5 for Python -- The h5py package is a Pythonic interface to the HDF5.. BSD-3 +
h5py (πŸ₯‡40 Β· ⭐ 1.7K) - HDF5 for Python -- The h5py package is a Pythonic interface to the HDF5.. BSD-3 -- [GitHub](https://github.com/h5py/h5py) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 430 Β· πŸ“₯ 1.7K Β· πŸ“¦ 150K Β· πŸ“‹ 1.3K - 17% open Β· ⏱️ 08.01.2022): +- [GitHub](https://github.com/h5py/h5py) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 430 Β· πŸ“₯ 1.7K Β· πŸ“¦ 150K Β· πŸ“‹ 1.3K - 17% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/h5py/h5py ``` -- [PyPi](https://pypi.org/project/h5py) (πŸ“₯ 11M / month Β· πŸ“¦ 14K Β· ⏱️ 16.11.2021): +- [PyPi](https://pypi.org/project/h5py) (πŸ“₯ 12M / month Β· πŸ“¦ 14K Β· ⏱️ 16.11.2021): ``` pip install h5py ``` -- [Conda](https://anaconda.org/conda-forge/h5py) (πŸ“₯ 6.9M Β· ⏱️ 26.11.2021): +- [Conda](https://anaconda.org/conda-forge/h5py) (πŸ“₯ 7M Β· ⏱️ 26.11.2021): ``` conda install -c conda-forge h5py ```
xarray (πŸ₯ˆ38 Β· ⭐ 2.4K) - N-D labeled arrays and datasets in Python. Apache-2 -- [GitHub](https://github.com/pydata/xarray) (πŸ‘¨β€πŸ’» 360 Β· πŸ”€ 750 Β· πŸ“¦ 8.7K Β· πŸ“‹ 3.2K - 29% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/pydata/xarray) (πŸ‘¨β€πŸ’» 360 Β· πŸ”€ 760 Β· πŸ“¦ 9K Β· πŸ“‹ 3.2K - 29% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/pydata/xarray ``` -- [PyPi](https://pypi.org/project/xarray) (πŸ“₯ 870K / month Β· πŸ“¦ 1.3K Β· ⏱️ 10.12.2021): +- [PyPi](https://pypi.org/project/xarray) (πŸ“₯ 1M / month Β· πŸ“¦ 1.3K Β· ⏱️ 01.02.2022): ``` pip install xarray ``` -- [Conda](https://anaconda.org/conda-forge/xarray) (πŸ“₯ 4.4M Β· ⏱️ 10.12.2021): +- [Conda](https://anaconda.org/conda-forge/xarray) (πŸ“₯ 4.6M Β· ⏱️ 01.02.2022): ``` conda install -c conda-forge xarray ```
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Modin (πŸ₯ˆ34 Β· ⭐ 6.7K) - Modin: Speed up your Pandas workflows by changing a single line of.. Apache-2 +
PyTables (πŸ₯ˆ35 Β· ⭐ 1.1K) - A Python package to manage extremely large amounts of data. BSD-3 -- [GitHub](https://github.com/modin-project/modin) (πŸ‘¨β€πŸ’» 87 Β· πŸ”€ 470 Β· πŸ“₯ 200K Β· πŸ“¦ 540 Β· πŸ“‹ 2.3K - 29% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/PyTables/PyTables) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 220 Β· πŸ“₯ 160 Β· πŸ“‹ 680 - 26% open Β· ⏱️ 28.01.2022): ``` - git clone https://github.com/modin-project/modin + git clone https://github.com/PyTables/PyTables ``` -- [PyPi](https://pypi.org/project/modin) (πŸ“₯ 170K / month Β· πŸ“¦ 20 Β· ⏱️ 19.12.2021): +- [PyPi](https://pypi.org/project/tables) (πŸ“₯ 800K / month Β· πŸ“¦ 2.3K Β· ⏱️ 28.12.2021): ``` - pip install modin + pip install tables + ``` +- [Conda](https://anaconda.org/conda-forge/pytables) (πŸ“₯ 3.8M Β· ⏱️ 25.01.2022): + ``` + conda install -c conda-forge pytables ```
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PyTables (πŸ₯ˆ34 Β· ⭐ 1.1K) - A Python package to manage extremely large amounts of data. BSD-3 +
Modin (πŸ₯ˆ34 Β· ⭐ 6.8K) - Modin: Speed up your Pandas workflows by changing a single line of.. Apache-2 -- [GitHub](https://github.com/PyTables/PyTables) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 220 Β· πŸ“₯ 160 Β· πŸ“‹ 680 - 26% open Β· ⏱️ 07.01.2022): +- [GitHub](https://github.com/modin-project/modin) (πŸ‘¨β€πŸ’» 88 Β· πŸ”€ 480 Β· πŸ“₯ 200K Β· πŸ“¦ 560 Β· πŸ“‹ 2.5K - 33% open Β· ⏱️ 09.02.2022): ``` - git clone https://github.com/PyTables/PyTables + git clone https://github.com/modin-project/modin ``` -- [PyPi](https://pypi.org/project/tables) (πŸ“₯ 630K / month Β· πŸ“¦ 2.3K Β· ⏱️ 28.12.2021): +- [PyPi](https://pypi.org/project/modin) (πŸ“₯ 190K / month Β· πŸ“¦ 21 Β· ⏱️ 04.02.2022): ``` - pip install tables + pip install modin ``` -- [Conda](https://anaconda.org/conda-forge/pytables) (πŸ“₯ 3.7M Β· ⏱️ 29.11.2021): +- [Conda](https://anaconda.org/conda-forge/modin-core) (πŸ“₯ 17K Β· ⏱️ 06.02.2022): ``` - conda install -c conda-forge pytables + conda install -c conda-forge modin-core ```
numexpr (πŸ₯ˆ33 Β· ⭐ 1.7K) - Fast numerical array expression evaluator for Python, NumPy, PyTables,.. MIT -- [GitHub](https://github.com/pydata/numexpr) (πŸ‘¨β€πŸ’» 58 Β· πŸ”€ 170 Β· πŸ“‹ 320 - 18% open Β· ⏱️ 07.01.2022): +- [GitHub](https://github.com/pydata/numexpr) (πŸ‘¨β€πŸ’» 59 Β· πŸ”€ 170 Β· πŸ“‹ 320 - 18% open Β· ⏱️ 06.02.2022): ``` git clone https://github.com/pydata/numexpr ``` -- [PyPi](https://pypi.org/project/numexpr) (πŸ“₯ 1.4M / month Β· πŸ“¦ 3K Β· ⏱️ 15.12.2021): +- [PyPi](https://pypi.org/project/numexpr) (πŸ“₯ 2.1M / month Β· πŸ“¦ 3K Β· ⏱️ 15.12.2021): ``` pip install numexpr ``` -- [Conda](https://anaconda.org/conda-forge/numexpr) (πŸ“₯ 3.5M Β· ⏱️ 09.12.2021): +- [Conda](https://anaconda.org/conda-forge/numexpr) (πŸ“₯ 3.6M Β· ⏱️ 26.01.2022): ``` conda install -c conda-forge numexpr ```
zarr (πŸ₯ˆ32 Β· ⭐ 840) - An implementation of chunked, compressed, N-dimensional arrays for Python. MIT -- [GitHub](https://github.com/zarr-developers/zarr-python) (πŸ‘¨β€πŸ’» 55 Β· πŸ”€ 130 Β· πŸ“¦ 990 Β· πŸ“‹ 480 - 41% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/zarr-developers/zarr-python) (πŸ‘¨β€πŸ’» 55 Β· πŸ”€ 140 Β· πŸ“¦ 1K Β· πŸ“‹ 490 - 42% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/zarr-developers/zarr-python ``` -- [PyPi](https://pypi.org/project/zarr) (πŸ“₯ 52K / month Β· πŸ“¦ 180 Β· ⏱️ 19.11.2021): +- [PyPi](https://pypi.org/project/zarr) (πŸ“₯ 83K / month Β· πŸ“¦ 190 Β· ⏱️ 07.02.2022): ``` pip install zarr ``` -- [Conda](https://anaconda.org/conda-forge/zarr) (πŸ“₯ 1.2M Β· ⏱️ 19.11.2021): +- [Conda](https://anaconda.org/conda-forge/zarr) (πŸ“₯ 1.2M Β· ⏱️ 07.02.2022): ``` conda install -c conda-forge zarr ```
TinyDB (πŸ₯ˆ31 Β· ⭐ 4.8K) - TinyDB is a lightweight document oriented database optimized for your.. MIT -- [GitHub](https://github.com/msiemens/tinydb) (πŸ‘¨β€πŸ’» 72 Β· πŸ”€ 420 Β· πŸ“‹ 280 - 3% open Β· ⏱️ 10.01.2022): +- [GitHub](https://github.com/msiemens/tinydb) (πŸ‘¨β€πŸ’» 73 Β· πŸ”€ 420 Β· πŸ“‹ 280 - 2% open Β· ⏱️ 18.01.2022): ``` git clone https://github.com/msiemens/tinydb ``` -- [PyPi](https://pypi.org/project/tinydb) (πŸ“₯ 290K / month Β· πŸ“¦ 780 Β· ⏱️ 23.09.2021): +- [PyPi](https://pypi.org/project/tinydb) (πŸ“₯ 320K / month Β· πŸ“¦ 790 Β· ⏱️ 18.01.2022): ``` pip install tinydb ``` -- [Conda](https://anaconda.org/conda-forge/tinydb) (πŸ“₯ 150K Β· ⏱️ 23.09.2021): +- [Conda](https://anaconda.org/conda-forge/tinydb) (πŸ“₯ 160K Β· ⏱️ 18.01.2022): ``` conda install -c conda-forge tinydb ```
+
polars (πŸ₯ˆ31 Β· ⭐ 4.5K) - Fast multi-threaded DataFrame library in Rust | Python | Node.js. MIT + +- [GitHub](https://github.com/pola-rs/polars) (πŸ‘¨β€πŸ’» 69 Β· πŸ”€ 250 Β· πŸ“¦ 2 Β· πŸ“‹ 960 - 8% open Β· ⏱️ 10.02.2022): + + ``` + git clone https://github.com/pola-rs/polars + ``` +- [PyPi](https://pypi.org/project/polars) (πŸ“₯ 33K / month Β· πŸ“¦ 11 Β· ⏱️ 09.02.2022): + ``` + pip install polars + ``` +
Koalas (πŸ₯ˆ31 Β· ⭐ 3.1K) - Koalas: pandas API on Apache Spark. Apache-2 - [GitHub](https://github.com/databricks/koalas) (πŸ‘¨β€πŸ’» 51 Β· πŸ”€ 320 Β· πŸ“₯ 1K Β· πŸ“¦ 170 Β· πŸ“‹ 580 - 16% open Β· ⏱️ 21.10.2021): @@ -4545,7 +4898,7 @@ _General-purpose data containers & structures as well as utilities & extensions ``` git clone https://github.com/databricks/koalas ``` -- [PyPi](https://pypi.org/project/koalas) (πŸ“₯ 2M / month Β· πŸ“¦ 7 Β· ⏱️ 19.10.2021): +- [PyPi](https://pypi.org/project/koalas) (πŸ“₯ 2.2M / month Β· πŸ“¦ 7 Β· ⏱️ 19.10.2021): ``` pip install koalas ``` @@ -4554,150 +4907,178 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge koalas ```
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Bottleneck (πŸ₯ˆ31 Β· ⭐ 690 Β· πŸ’€) - Fast NumPy array functions written in C. BSD-2 +
Vaex (πŸ₯‰30 Β· ⭐ 6.9K) - Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization.. MIT -- [GitHub](https://github.com/pydata/bottleneck) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 75 Β· πŸ“¦ 30K Β· πŸ“‹ 220 - 17% open Β· ⏱️ 24.01.2021): +- [GitHub](https://github.com/vaexio/vaex) (πŸ‘¨β€πŸ’» 63 Β· πŸ”€ 530 Β· πŸ“₯ 230 Β· πŸ“‹ 1K - 36% open Β· ⏱️ 09.02.2022): ``` - git clone https://github.com/pydata/bottleneck + git clone https://github.com/vaexio/vaex ``` -- [PyPi](https://pypi.org/project/Bottleneck) (πŸ“₯ 410K / month Β· πŸ“¦ 1.6K Β· ⏱️ 21.02.2020): +- [PyPi](https://pypi.org/project/vaex) (πŸ“₯ 26K / month Β· πŸ“¦ 16 Β· ⏱️ 07.02.2022): ``` - pip install Bottleneck + pip install vaex ``` -- [Conda](https://anaconda.org/conda-forge/bottleneck) (πŸ“₯ 1.8M Β· ⏱️ 04.11.2021): +- [Conda](https://anaconda.org/conda-forge/vaex) (πŸ“₯ 120K Β· ⏱️ 30.12.2021): ``` - conda install -c conda-forge bottleneck + conda install -c conda-forge vaex ```
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Vaex (πŸ₯‰30 Β· ⭐ 6.8K) - Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization.. MIT +
Arctic (πŸ₯‰30 Β· ⭐ 2.6K) - Arctic is a high performance datastore for numeric data. ❗️LGPL-2.1 -- [GitHub](https://github.com/vaexio/vaex) (πŸ‘¨β€πŸ’» 62 Β· πŸ”€ 530 Β· πŸ“₯ 220 Β· πŸ“‹ 970 - 36% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/man-group/arctic) (πŸ‘¨β€πŸ’» 75 Β· πŸ”€ 520 Β· πŸ“₯ 180 Β· πŸ“¦ 150 Β· πŸ“‹ 540 - 17% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/vaexio/vaex + git clone https://github.com/man-group/arctic ``` -- [PyPi](https://pypi.org/project/vaex) (πŸ“₯ 16K / month Β· πŸ“¦ 16 Β· ⏱️ 18.12.2021): +- [PyPi](https://pypi.org/project/arctic) (πŸ“₯ 9.2K / month Β· πŸ“¦ 34 Β· ⏱️ 24.01.2022): ``` - pip install vaex + pip install arctic ``` -- [Conda](https://anaconda.org/conda-forge/vaex) (πŸ“₯ 120K Β· ⏱️ 30.12.2021): +- [Conda](https://anaconda.org/conda-forge/arctic) (πŸ“₯ 17K Β· ⏱️ 16.12.2019): ``` - conda install -c conda-forge vaex + conda install -c conda-forge arctic ```
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polars (πŸ₯‰30 Β· ⭐ 4.2K) - Fast multi-threaded DataFrame library in Rust | Python | Node.js. MIT +
datasketch (πŸ₯‰30 Β· ⭐ 1.7K) - MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog,.. MIT -- [GitHub](https://github.com/pola-rs/polars) (πŸ‘¨β€πŸ’» 65 Β· πŸ”€ 230 Β· πŸ“‹ 870 - 9% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/ekzhu/datasketch) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 230 Β· πŸ“₯ 19 Β· πŸ“¦ 350 Β· πŸ“‹ 130 - 22% open Β· ⏱️ 04.02.2022): ``` - git clone https://github.com/pola-rs/polars + git clone https://github.com/ekzhu/datasketch ``` -- [PyPi](https://pypi.org/project/polars) (πŸ“₯ 34K / month Β· πŸ“¦ 8 Β· ⏱️ 10.01.2022): +- [PyPi](https://pypi.org/project/datasketch) (πŸ“₯ 420K / month Β· πŸ“¦ 54 Β· ⏱️ 04.02.2022): ``` - pip install polars + pip install datasketch ```
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Arctic (πŸ₯‰29 Β· ⭐ 2.6K) - Arctic is a high performance datastore for numeric data. ❗️LGPL-2.1 +
Bottleneck (πŸ₯‰30 Β· ⭐ 700) - Fast NumPy array functions written in C. BSD-2 -- [GitHub](https://github.com/man-group/arctic) (πŸ‘¨β€πŸ’» 72 Β· πŸ”€ 520 Β· πŸ“₯ 180 Β· πŸ“¦ 150 Β· πŸ“‹ 540 - 17% open Β· ⏱️ 10.01.2022): +- [GitHub](https://github.com/pydata/bottleneck) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 74 Β· πŸ“¦ 30K Β· πŸ“‹ 220 - 17% open Β· ⏱️ 07.02.2022): ``` - git clone https://github.com/man-group/arctic + git clone https://github.com/pydata/bottleneck ``` -- [PyPi](https://pypi.org/project/arctic) (πŸ“₯ 5.4K / month Β· πŸ“¦ 34 Β· ⏱️ 10.01.2022): +- [PyPi](https://pypi.org/project/Bottleneck) (πŸ“₯ 410K / month Β· πŸ“¦ 1.6K Β· ⏱️ 21.02.2020): ``` - pip install arctic + pip install Bottleneck ``` -- [Conda](https://anaconda.org/conda-forge/arctic) (πŸ“₯ 17K Β· ⏱️ 16.12.2019): +- [Conda](https://anaconda.org/conda-forge/bottleneck) (πŸ“₯ 1.9M Β· ⏱️ 04.11.2021): ``` - conda install -c conda-forge arctic + conda install -c conda-forge bottleneck ```
datatable (πŸ₯‰29 Β· ⭐ 1.4K) - A Python package for manipulating 2-dimensional tabular data.. MPL-2.0 -- [GitHub](https://github.com/h2oai/datatable) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 120 Β· πŸ“₯ 1.2K Β· πŸ“‹ 1.4K - 9% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/h2oai/datatable) (πŸ‘¨β€πŸ’» 33 Β· πŸ”€ 130 Β· πŸ“₯ 1.2K Β· πŸ“‹ 1.4K - 9% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/h2oai/datatable ``` -- [PyPi](https://pypi.org/project/datatable) (πŸ“₯ 68K / month Β· πŸ“¦ 12 Β· ⏱️ 01.07.2021): +- [PyPi](https://pypi.org/project/datatable) (πŸ“₯ 79K / month Β· πŸ“¦ 12 Β· ⏱️ 01.07.2021): ``` pip install datatable ``` +- [Conda](https://anaconda.org/conda-forge/datatable) (πŸ“₯ 12K Β· ⏱️ 23.12.2020): + ``` + conda install -c conda-forge datatable + ```
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datasketch (πŸ₯‰28 Β· ⭐ 1.6K) - MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog,.. MIT +
swifter (πŸ₯‰28 Β· ⭐ 1.9K) - A package which efficiently applies any function to a pandas.. MIT -- [GitHub](https://github.com/ekzhu/datasketch) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 230 Β· πŸ“₯ 18 Β· πŸ“¦ 340 Β· πŸ“‹ 130 - 23% open Β· ⏱️ 27.12.2021): +- [GitHub](https://github.com/jmcarpenter2/swifter) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 87 Β· πŸ“¦ 480 Β· πŸ“‹ 110 - 21% open Β· ⏱️ 07.02.2022): ``` - git clone https://github.com/ekzhu/datasketch + git clone https://github.com/jmcarpenter2/swifter ``` -- [PyPi](https://pypi.org/project/datasketch) (πŸ“₯ 380K / month Β· πŸ“¦ 54 Β· ⏱️ 27.12.2021): +- [PyPi](https://pypi.org/project/swifter) (πŸ“₯ 140K / month Β· πŸ“¦ 28 Β· ⏱️ 07.02.2022): ``` - pip install datasketch + pip install swifter + ``` +- [Conda](https://anaconda.org/conda-forge/swifter) (πŸ“₯ 130K Β· ⏱️ 26.06.2021): + ``` + conda install -c conda-forge swifter ```
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swifter (πŸ₯‰26 Β· ⭐ 1.9K Β· πŸ’€) - A package which efficiently applies any function to a pandas.. MIT +
pandera (πŸ₯‰27 Β· ⭐ 1K Β· βž•) - A light-weight, flexible, and expressive data validation library.. MIT -- [GitHub](https://github.com/jmcarpenter2/swifter) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 86 Β· πŸ“¦ 450 Β· πŸ“‹ 110 - 21% open Β· ⏱️ 25.06.2021): +- [GitHub](https://github.com/pandera-dev/pandera) (πŸ‘¨β€πŸ’» 48 Β· πŸ”€ 82 Β· πŸ“¦ 150 Β· πŸ“‹ 360 - 22% open Β· ⏱️ 08.02.2022): ``` - git clone https://github.com/jmcarpenter2/swifter + git clone https://github.com/pandera-dev/pandera ``` -- [PyPi](https://pypi.org/project/swifter) (πŸ“₯ 91K / month Β· πŸ“¦ 27 Β· ⏱️ 25.06.2021): +- [PyPi](https://pypi.org/project/pandera) (πŸ“₯ 160K / month Β· πŸ“¦ 18 Β· ⏱️ 09.02.2022): ``` - pip install swifter + pip install pandera ``` -- [Conda](https://anaconda.org/conda-forge/swifter) (πŸ“₯ 130K Β· ⏱️ 26.06.2021): +- [Conda](https://anaconda.org/conda-forge/pandera-core) (πŸ“₯ 5.8K Β· ⏱️ 31.12.2021): ``` - conda install -c conda-forge swifter + conda install -c conda-forge pandera-core + ``` +
+
PandaralΒ·lel (πŸ₯‰26 Β· ⭐ 2K) - A simple and efficient tool to parallelize Pandas.. BSD-3 + +- [GitHub](https://github.com/nalepae/pandarallel) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 130 Β· πŸ“¦ 400 Β· πŸ“‹ 150 - 54% open Β· ⏱️ 06.02.2022): + + ``` + git clone https://github.com/nalepae/pandarallel + ``` +- [PyPi](https://pypi.org/project/pandarallel) (πŸ“₯ 220K / month Β· πŸ“¦ 19 Β· ⏱️ 06.02.2022): + ``` + pip install pandarallel + ``` +- [Conda](https://anaconda.org/conda-forge/pandarallel) (πŸ“₯ 1.5K Β· ⏱️ 06.02.2022): + ``` + conda install -c conda-forge pandarallel ```
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PandaralΒ·lel (πŸ₯‰24 Β· ⭐ 1.9K) - A simple and efficient tool to parallelize Pandas.. BSD-3 +
docarray (πŸ₯‰23 Β· ⭐ 520 Β· 🐣) - The data structure for unstructured data. Apache-2 -- [GitHub](https://github.com/nalepae/pandarallel) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 120 Β· πŸ“¦ 370 Β· πŸ“‹ 140 - 54% open Β· ⏱️ 17.10.2021): +- [GitHub](https://github.com/jina-ai/docarray) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 30 Β· πŸ“¦ 7 Β· πŸ“‹ 27 - 29% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/nalepae/pandarallel + git clone https://github.com/jina-ai/docarray + ``` +- [PyPi](https://pypi.org/project/docarray) (πŸ“₯ 52K / month Β· ⏱️ 10.02.2022): + ``` + pip install docarray ``` -- [PyPi](https://pypi.org/project/pandarallel) (πŸ“₯ 180K / month Β· πŸ“¦ 13 Β· ⏱️ 17.10.2021): +- [Conda](https://anaconda.org/conda-forge/docarray) (πŸ“₯ 41 Β· ⏱️ 10.01.2022): ``` - pip install pandarallel + conda install -c conda-forge docarray ```
Pandas Summary (πŸ₯‰21 Β· ⭐ 380) - A library for managing, validating, summarizing, and.. Apache-2 -- [GitHub](https://github.com/polyaxon/datatile) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 37 Β· πŸ“¦ 3 Β· πŸ“‹ 14 - 50% open Β· ⏱️ 06.01.2022): +- [GitHub](https://github.com/polyaxon/datatile) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 37 Β· πŸ“‹ 15 - 53% open Β· ⏱️ 08.02.2022): ``` - git clone https://github.com/mouradmourafiq/pandas-summary + git clone https://github.com/polyaxon/datatile ``` -- [PyPi](https://pypi.org/project/pandas-summary) (πŸ“₯ 38K / month Β· πŸ“¦ 57 Β· ⏱️ 25.11.2021): +- [PyPi](https://pypi.org/project/pandas-summary) (πŸ“₯ 43K / month Β· πŸ“¦ 57 Β· ⏱️ 25.11.2021): ``` pip install pandas-summary ```
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Bounter (πŸ₯‰18 Β· ⭐ 930 Β· πŸ’€) - Efficient Counter that uses a limited (bounded) amount of memory.. MIT +
Bounter (πŸ₯‰17 Β· ⭐ 930 Β· πŸ’€) - Efficient Counter that uses a limited (bounded) amount of memory.. MIT - [GitHub](https://github.com/RaRe-Technologies/bounter) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 48 Β· πŸ“¦ 25 Β· πŸ“‹ 24 - 62% open Β· ⏱️ 24.05.2021): ``` git clone https://github.com/RaRe-Technologies/bounter ``` -- [PyPi](https://pypi.org/project/bounter) (πŸ“₯ 190 / month Β· πŸ“¦ 8 Β· ⏱️ 17.08.2020): +- [PyPi](https://pypi.org/project/bounter) (πŸ“₯ 110 / month Β· πŸ“¦ 8 Β· ⏱️ 17.08.2020): ``` pip install bounter ```
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PandaPy (πŸ₯‰10 Β· ⭐ 490) - PandaPy has the speed of NumPy and the usability of Pandas 10x to 50x.. MIT +
PandaPy (πŸ₯‰11 Β· ⭐ 490) - PandaPy has the speed of NumPy and the usability of Pandas 10x to 50x.. MIT - [GitHub](https://github.com/firmai/pandapy) (πŸ‘¨β€πŸ’» 3 Β· πŸ”€ 56 Β· πŸ“¦ 1 Β· πŸ“‹ 3 - 66% open Β· ⏱️ 20.10.2021): ``` git clone https://github.com/firmai/pandapy ``` -- [PyPi](https://pypi.org/project/pandapy) (πŸ“₯ 70 / month Β· ⏱️ 25.01.2020): +- [PyPi](https://pypi.org/project/pandapy) (πŸ“₯ 96 / month Β· ⏱️ 25.01.2020): ``` pip install pandapy ``` @@ -4705,11 +5086,11 @@ _General-purpose data containers & structures as well as utilities & extensions
Show 7 hidden projects... - Blaze (πŸ₯ˆ31 Β· ⭐ 3K Β· πŸ’€) - NumPy and Pandas interface to Big Data. BSD-3 -- sklearn-pandas (πŸ₯‰27 Β· ⭐ 2.5K Β· πŸ’€) - Pandas integration with sklearn. ❗️Zlib +- sklearn-pandas (πŸ₯‰27 Β· ⭐ 2.6K Β· πŸ’€) - Pandas integration with sklearn. ❗️Zlib - bcolz (πŸ₯‰26 Β· ⭐ 940 Β· πŸ’€) - A columnar data container that can be compressed. BSD-3 - StaticFrame (πŸ₯‰26 Β· ⭐ 260) - Immutable and grow-only Pandas-like DataFrames with a more explicit.. MIT - pandasql (πŸ₯‰25 Β· ⭐ 1.1K Β· πŸ’€) - sqldf for pandas. MIT -- pickleDB (πŸ₯‰23 Β· ⭐ 630 Β· πŸ’€) - pickleDB is an open source key-value store using Pythons json module. BSD-3 +- pickleDB (πŸ₯‰23 Β· ⭐ 640 Β· πŸ’€) - pickleDB is an open source key-value store using Pythons json module. BSD-3 - fletcher (πŸ₯‰19 Β· ⭐ 220 Β· πŸ’€) - Pandas ExtensionDType/Array backed by Apache Arrow. MIT

@@ -4720,7 +5101,7 @@ _General-purpose data containers & structures as well as utilities & extensions _Libraries for loading, collecting, and extracting data from a variety of data sources and formats._ -πŸ”— best-of-python - Data Extraction ( ⭐ 1.9K) - Collection of data-loading and -extraction libraries. +πŸ”— best-of-python - Data Extraction ( ⭐ 2K) - Collection of data-loading and -extraction libraries.
@@ -4742,140 +5123,144 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched
Celery (πŸ₯‡46 Β· ⭐ 19K) - Asynchronous task queue/job queue based on distributed message passing. BSD-3 -- [GitHub](https://github.com/celery/celery) (πŸ‘¨β€πŸ’» 1.2K Β· πŸ”€ 4.2K Β· πŸ“¦ 63K Β· πŸ“‹ 4.7K - 10% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/celery/celery) (πŸ‘¨β€πŸ’» 1.2K Β· πŸ”€ 4.2K Β· πŸ“¦ 64K Β· πŸ“‹ 4.7K - 11% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/celery/celery ``` -- [PyPi](https://pypi.org/project/celery) (πŸ“₯ 4.2M / month Β· πŸ“¦ 15K Β· ⏱️ 29.12.2021): +- [PyPi](https://pypi.org/project/celery) (πŸ“₯ 5.2M / month Β· πŸ“¦ 15K Β· ⏱️ 29.12.2021): ``` pip install celery ``` -- [Conda](https://anaconda.org/conda-forge/celery) (πŸ“₯ 770K Β· ⏱️ 09.01.2022): +- [Conda](https://anaconda.org/conda-forge/celery) (πŸ“₯ 780K Β· ⏱️ 07.02.2022): ``` conda install -c conda-forge celery ```
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Airflow (πŸ₯‡44 Β· ⭐ 25K Β· πŸ“‰) - Platform to programmatically author, schedule, and monitor.. Apache-2 +
Airflow (πŸ₯‡44 Β· ⭐ 25K) - Platform to programmatically author, schedule, and monitor workflows. Apache-2 -- [GitHub](https://github.com/apache/airflow) (πŸ‘¨β€πŸ’» 2.2K Β· πŸ”€ 9.8K Β· πŸ“₯ 230K Β· πŸ“‹ 4.9K - 18% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/apache/airflow) (πŸ‘¨β€πŸ’» 2.3K Β· πŸ”€ 10K Β· πŸ“₯ 250K Β· πŸ“‹ 5.1K - 18% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/apache/airflow ``` -- [PyPi](https://pypi.org/project/apache-airflow) (πŸ“₯ 3.5M / month Β· πŸ“¦ 440 Β· ⏱️ 21.12.2021): +- [PyPi](https://pypi.org/project/apache-airflow) (πŸ“₯ 4.2M / month Β· πŸ“¦ 440 Β· ⏱️ 21.12.2021): ``` pip install apache-airflow ``` -- [Conda](https://anaconda.org/conda-forge/airflow) (πŸ“₯ 520K Β· ⏱️ 22.12.2021): +- [Conda](https://anaconda.org/conda-forge/airflow) (πŸ“₯ 540K Β· ⏱️ 22.12.2021): ``` conda install -c conda-forge airflow ``` -- [Docker Hub](https://hub.docker.com/r/apache/airflow) (πŸ“₯ 59M Β· ⭐ 310 Β· ⏱️ 21.12.2021): +- [Docker Hub](https://hub.docker.com/r/apache/airflow) (πŸ“₯ 63M Β· ⭐ 320 Β· ⏱️ 25.01.2022): ``` docker pull apache/airflow ```
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Beam (πŸ₯‡39 Β· ⭐ 5.2K) - Unified programming model to define and execute data processing.. Apache-2 +
Beam (πŸ₯‡39 Β· ⭐ 5.3K) - Unified programming model to define and execute data processing.. Apache-2 -- [GitHub](https://github.com/apache/beam) (πŸ‘¨β€πŸ’» 1.2K Β· πŸ”€ 3.3K Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/apache/beam) (πŸ‘¨β€πŸ’» 1.2K Β· πŸ”€ 3.4K Β· ⏱️ 10.02.2022): ``` git clone https://github.com/apache/beam ``` -- [PyPi](https://pypi.org/project/apache-beam) (πŸ“₯ 22M / month Β· πŸ“¦ 140 Β· ⏱️ 30.12.2021): +- [PyPi](https://pypi.org/project/apache-beam) (πŸ“₯ 15M / month Β· πŸ“¦ 150 Β· ⏱️ 07.02.2022): ``` pip install apache-beam ``` +- [Conda](https://anaconda.org/conda-forge/apache-beam-with-aws) (πŸ“₯ 3.9K Β· ⏱️ 08.02.2022): + ``` + conda install -c conda-forge apache-beam-with-aws + ```
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luigi (πŸ₯‡38 Β· ⭐ 15K) - Luigi is a Python module that helps you build complex pipelines of batch.. Apache-2 +
joblib (πŸ₯‡39 Β· ⭐ 2.7K) - Computing with Python functions. BSD-3 -- [GitHub](https://github.com/spotify/luigi) (πŸ‘¨β€πŸ’» 580 Β· πŸ”€ 2.3K Β· πŸ“¦ 1.6K Β· πŸ“‹ 970 - 10% open Β· ⏱️ 11.01.2022): +- [GitHub](https://github.com/joblib/joblib) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 320 Β· πŸ“¦ 160K Β· πŸ“‹ 720 - 46% open Β· ⏱️ 08.02.2022): ``` - git clone https://github.com/spotify/luigi + git clone https://github.com/joblib/joblib ``` -- [PyPi](https://pypi.org/project/luigi) (πŸ“₯ 570K / month Β· πŸ“¦ 400 Β· ⏱️ 23.09.2020): +- [PyPi](https://pypi.org/project/joblib) (πŸ“₯ 27M / month Β· πŸ“¦ 4.9K Β· ⏱️ 07.10.2021): ``` - pip install luigi + pip install joblib ``` -- [Conda](https://anaconda.org/anaconda/luigi) (πŸ“₯ 8.8K Β· πŸ“¦ 2 Β· ⏱️ 17.04.2021): +- [Conda](https://anaconda.org/conda-forge/joblib) (πŸ“₯ 7.1M Β· ⏱️ 07.10.2021): ``` - conda install -c anaconda luigi + conda install -c conda-forge joblib ```
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Dagster (πŸ₯‡37 Β· ⭐ 4.2K) - An orchestration platform for the development, production, and.. Apache-2 +
luigi (πŸ₯‡38 Β· ⭐ 15K) - Luigi is a Python module that helps you build complex pipelines of batch.. Apache-2 -- [GitHub](https://github.com/dagster-io/dagster) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 510 Β· πŸ“¦ 290 Β· πŸ“‹ 3.6K - 24% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/spotify/luigi) (πŸ‘¨β€πŸ’» 580 Β· πŸ”€ 2.3K Β· πŸ“¦ 1.6K Β· πŸ“‹ 970 - 10% open Β· ⏱️ 16.01.2022): ``` - git clone https://github.com/dagster-io/dagster + git clone https://github.com/spotify/luigi ``` -- [PyPi](https://pypi.org/project/dagster) (πŸ“₯ 150K / month Β· πŸ“¦ 83 Β· ⏱️ 06.01.2022): +- [PyPi](https://pypi.org/project/luigi) (πŸ“₯ 620K / month Β· πŸ“¦ 400 Β· ⏱️ 23.09.2020): ``` - pip install dagster + pip install luigi ``` -- [Conda](https://anaconda.org/conda-forge/dagster) (πŸ“₯ 430K Β· ⏱️ 07.01.2022): +- [Conda](https://anaconda.org/anaconda/luigi) (πŸ“₯ 8.9K Β· πŸ“¦ 2 Β· ⏱️ 20.01.2022): ``` - conda install -c conda-forge dagster + conda install -c anaconda luigi ```
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joblib (πŸ₯‡37 Β· ⭐ 2.6K Β· πŸ“ˆ) - Computing with Python functions. BSD-3 +
rq (πŸ₯‡38 Β· ⭐ 8.1K) - Simple job queues for Python. BSD-3 -- [GitHub](https://github.com/joblib/joblib) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 320 Β· πŸ“¦ 150K Β· πŸ“‹ 710 - 46% open Β· ⏱️ 08.11.2021): +- [GitHub](https://github.com/rq/rq) (πŸ‘¨β€πŸ’» 250 Β· πŸ”€ 1.3K Β· πŸ“¦ 9.6K Β· πŸ“‹ 940 - 17% open Β· ⏱️ 07.02.2022): ``` - git clone https://github.com/joblib/joblib + git clone https://github.com/rq/rq ``` -- [PyPi](https://pypi.org/project/joblib) (πŸ“₯ 24M / month Β· πŸ“¦ 4.9K Β· ⏱️ 07.10.2021): +- [PyPi](https://pypi.org/project/rq) (πŸ“₯ 540K / month Β· πŸ“¦ 1.7K Β· ⏱️ 07.12.2021): ``` - pip install joblib + pip install rq ``` -- [Conda](https://anaconda.org/conda-forge/joblib) (πŸ“₯ 6.7M Β· ⏱️ 07.10.2021): +- [Conda](https://anaconda.org/conda-forge/rq) (πŸ“₯ 68K Β· ⏱️ 30.06.2021): ``` - conda install -c conda-forge joblib + conda install -c conda-forge rq ```
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rq (πŸ₯ˆ36 Β· ⭐ 8.1K) - Simple job queues for Python. BSD-3 +
Prefect (πŸ₯ˆ37 Β· ⭐ 8.3K) - The easiest way to automate your data. Apache-2 -- [GitHub](https://github.com/rq/rq) (πŸ‘¨β€πŸ’» 250 Β· πŸ”€ 1.3K Β· πŸ“¦ 9.4K Β· πŸ“‹ 940 - 17% open Β· ⏱️ 03.01.2022): +- [GitHub](https://github.com/PrefectHQ/prefect) (πŸ‘¨β€πŸ’» 290 Β· πŸ”€ 800 Β· πŸ“¦ 590 Β· πŸ“‹ 2.1K - 20% open Β· ⏱️ 09.02.2022): ``` - git clone https://github.com/rq/rq + git clone https://github.com/PrefectHQ/prefect ``` -- [PyPi](https://pypi.org/project/rq) (πŸ“₯ 410K / month Β· πŸ“¦ 1.7K Β· ⏱️ 07.12.2021): +- [PyPi](https://pypi.org/project/prefect) (πŸ“₯ 170K / month Β· πŸ“¦ 40 Β· ⏱️ 09.02.2022): ``` - pip install rq + pip install prefect ``` -- [Conda](https://anaconda.org/conda-forge/rq) (πŸ“₯ 67K Β· ⏱️ 30.06.2021): +- [Conda](https://anaconda.org/conda-forge/prefect) (πŸ“₯ 240K Β· ⏱️ 25.01.2022): ``` - conda install -c conda-forge rq + conda install -c conda-forge prefect ```
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Prefect (πŸ₯ˆ36 Β· ⭐ 8.1K) - The easiest way to automate your data. Apache-2 +
Dagster (πŸ₯ˆ37 Β· ⭐ 4.3K) - An orchestration platform for the development, production, and.. Apache-2 -- [GitHub](https://github.com/PrefectHQ/prefect) (πŸ‘¨β€πŸ’» 290 Β· πŸ”€ 780 Β· πŸ“¦ 550 Β· πŸ“‹ 2K - 19% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/dagster-io/dagster) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 530 Β· πŸ“¦ 300 Β· πŸ“‹ 3.7K - 24% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/PrefectHQ/prefect + git clone https://github.com/dagster-io/dagster ``` -- [PyPi](https://pypi.org/project/prefect) (πŸ“₯ 140K / month Β· πŸ“¦ 40 Β· ⏱️ 12.01.2022): +- [PyPi](https://pypi.org/project/dagster) (πŸ“₯ 180K / month Β· πŸ“¦ 84 Β· ⏱️ 03.02.2022): ``` - pip install prefect + pip install dagster ``` -- [Conda](https://anaconda.org/conda-forge/prefect) (πŸ“₯ 230K Β· ⏱️ 23.12.2021): +- [Conda](https://anaconda.org/conda-forge/dagster) (πŸ“₯ 450K Β· ⏱️ 04.02.2022): ``` - conda install -c conda-forge prefect + conda install -c conda-forge dagster ```
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dbt (πŸ₯ˆ36 Β· ⭐ 4K Β· πŸ“‰) - dbt enables data analysts and engineers to transform their data using.. Apache-2 +
dbt (πŸ₯ˆ36 Β· ⭐ 4.2K) - dbt enables data analysts and engineers to transform their data using the.. Apache-2 -- [GitHub](https://github.com/dbt-labs/dbt-core) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 720 Β· πŸ“₯ 120 Β· πŸ“¦ 250 Β· πŸ“‹ 2.4K - 10% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/dbt-labs/dbt-core) (πŸ‘¨β€πŸ’» 200 Β· πŸ”€ 760 Β· πŸ“₯ 160 Β· πŸ“¦ 300 Β· πŸ“‹ 2.5K - 11% open Β· ⏱️ 07.02.2022): ``` - git clone https://github.com/fishtown-analytics/dbt + git clone https://github.com/dbt-labs/dbt-core ``` -- [PyPi](https://pypi.org/project/dbt) (πŸ“₯ 570K / month Β· πŸ“¦ 29 Β· ⏱️ 06.12.2021): +- [PyPi](https://pypi.org/project/dbt) (πŸ“₯ 680K / month Β· πŸ“¦ 29 Β· ⏱️ 06.12.2021): ``` pip install dbt ``` @@ -4884,232 +5269,252 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched conda install -c conda-forge dbt ```
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Great Expectations (πŸ₯ˆ35 Β· ⭐ 5.9K Β· πŸ“ˆ) - Always know what to expect from your data. Apache-2 +
Great Expectations (πŸ₯ˆ35 Β· ⭐ 6.1K) - Always know what to expect from your data. Apache-2 -- [GitHub](https://github.com/great-expectations/great_expectations) (πŸ‘¨β€πŸ’» 260 Β· πŸ”€ 800 Β· πŸ“‹ 1.2K - 15% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/great-expectations/great_expectations) (πŸ‘¨β€πŸ’» 260 Β· πŸ”€ 830 Β· πŸ“‹ 1.2K - 15% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/great-expectations/great_expectations ``` -- [PyPi](https://pypi.org/project/great_expectations) (πŸ“₯ 2.3M / month Β· πŸ“¦ 27 Β· ⏱️ 06.01.2022): +- [PyPi](https://pypi.org/project/great_expectations) (πŸ“₯ 2.9M / month Β· πŸ“¦ 27 Β· ⏱️ 03.02.2022): ``` pip install great_expectations ``` +- [Conda](https://anaconda.org/conda-forge/great-expectations) (πŸ“₯ 350K Β· ⏱️ 04.02.2022): + ``` + conda install -c conda-forge great-expectations + ```
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Kedro (πŸ₯ˆ33 Β· ⭐ 4.8K) - A Python framework for creating reproducible, maintainable and modular.. Apache-2 +
Kedro (πŸ₯ˆ33 Β· ⭐ 6.5K) - A Python framework for creating reproducible, maintainable and modular.. Apache-2 -- [GitHub](https://github.com/kedro-org/kedro) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 540 Β· πŸ“¦ 680 Β· πŸ“‹ 610 - 8% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/kedro-org/kedro) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 600 Β· πŸ“¦ 730 Β· πŸ“‹ 600 - 6% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/quantumblacklabs/kedro + git clone https://github.com/kedro-org/kedro ``` -- [PyPi](https://pypi.org/project/kedro) (πŸ“₯ 220K / month Β· πŸ“¦ 35 Β· ⏱️ 09.12.2021): +- [PyPi](https://pypi.org/project/kedro) (πŸ“₯ 300K / month Β· πŸ“¦ 35 Β· ⏱️ 09.12.2021): ``` pip install kedro ```
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Activeloop (πŸ₯ˆ31 Β· ⭐ 4.2K) - Dataset format for AI. Build, manage, & visualize datasets for.. MPL-2.0 +
mleap (πŸ₯ˆ31 Β· ⭐ 1.4K) - MLeap: Deploy ML Pipelines to Production. Apache-2 -- [GitHub](https://github.com/activeloopai/Hub) (πŸ‘¨β€πŸ’» 89 Β· πŸ”€ 340 Β· πŸ“¦ 140 Β· πŸ“‹ 330 - 20% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/combust/mleap) (πŸ‘¨β€πŸ’» 71 Β· πŸ”€ 290 Β· πŸ“¦ 180 Β· πŸ“‹ 440 - 20% open Β· ⏱️ 27.01.2022): ``` - git clone https://github.com/activeloopai/Hub + git clone https://github.com/combust/mleap ``` -- [PyPi](https://pypi.org/project/hub) (πŸ“₯ 2.1K / month Β· πŸ“¦ 52 Β· ⏱️ 22.12.2021): +- [PyPi](https://pypi.org/project/mleap) (πŸ“₯ 200K / month Β· πŸ“¦ 25 Β· ⏱️ 12.01.2022): ``` - pip install hub + pip install mleap + ``` +- [Conda](https://anaconda.org/conda-forge/mleap) (πŸ“₯ 43K Β· ⏱️ 12.01.2022): + ``` + conda install -c conda-forge mleap ```
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huey (πŸ₯ˆ31 Β· ⭐ 3.8K) - a little task queue for python. MIT +
petl (πŸ₯ˆ31 Β· ⭐ 970) - Python Extract Transform and Load Tables of Data. MIT -- [GitHub](https://github.com/coleifer/huey) (πŸ‘¨β€πŸ’» 66 Β· πŸ”€ 330 Β· πŸ“¦ 850 Β· ⏱️ 10.01.2022): +- [GitHub](https://github.com/petl-developers/petl) (πŸ‘¨β€πŸ’» 54 Β· πŸ”€ 170 Β· πŸ“¦ 620 Β· πŸ“‹ 440 - 16% open Β· ⏱️ 08.02.2022): ``` - git clone https://github.com/coleifer/huey + git clone https://github.com/petl-developers/petl ``` -- [PyPi](https://pypi.org/project/huey) (πŸ“₯ 45K / month Β· πŸ“¦ 160 Β· ⏱️ 28.12.2021): +- [PyPi](https://pypi.org/project/petl) (πŸ“₯ 56K / month Β· πŸ“¦ 74 Β· ⏱️ 08.02.2022): ``` - pip install huey + pip install petl ``` -- [Conda](https://anaconda.org/conda-forge/huey) (πŸ“₯ 23K Β· ⏱️ 16.10.2019): +- [Conda](https://anaconda.org/conda-forge/petl) (πŸ“₯ 70K Β· ⏱️ 05.02.2022): ``` - conda install -c conda-forge huey + conda install -c conda-forge petl ```
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mleap (πŸ₯ˆ31 Β· ⭐ 1.3K) - MLeap: Deploy ML Pipelines to Production. Apache-2 +
Activeloop (πŸ₯ˆ30 Β· ⭐ 4.3K) - Dataset format for AI. Build, manage, & visualize datasets for.. MPL-2.0 -- [GitHub](https://github.com/combust/mleap) (πŸ‘¨β€πŸ’» 71 Β· πŸ”€ 290 Β· πŸ“¦ 170 Β· πŸ“‹ 440 - 20% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/activeloopai/Hub) (πŸ‘¨β€πŸ’» 91 Β· πŸ”€ 350 Β· πŸ“‹ 340 - 19% open Β· ⏱️ 09.02.2022): ``` - git clone https://github.com/combust/mleap - ``` -- [PyPi](https://pypi.org/project/mleap) (πŸ“₯ 200K / month Β· πŸ“¦ 25 Β· ⏱️ 12.01.2022): - ``` - pip install mleap + git clone https://github.com/activeloopai/Hub ``` -- [Conda](https://anaconda.org/conda-forge/mleap) (πŸ“₯ 43K Β· ⏱️ 12.01.2022): +- [PyPi](https://pypi.org/project/hub) (πŸ“₯ 3.2K / month Β· πŸ“¦ 52 Β· ⏱️ 01.02.2022): ``` - conda install -c conda-forge mleap + pip install hub ```
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TFX (πŸ₯ˆ30 Β· ⭐ 1.7K) - TFX is an end-to-end platform for deploying production ML pipelines. Apache-2 +
huey (πŸ₯ˆ30 Β· ⭐ 3.8K) - a little task queue for python. MIT -- [GitHub](https://github.com/tensorflow/tfx) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 520 Β· πŸ“‹ 730 - 34% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/coleifer/huey) (πŸ‘¨β€πŸ’» 66 Β· πŸ”€ 330 Β· πŸ“¦ 860 Β· ⏱️ 10.01.2022): ``` - git clone https://github.com/tensorflow/tfx + git clone https://github.com/coleifer/huey ``` -- [PyPi](https://pypi.org/project/tfx) (πŸ“₯ 340K / month Β· πŸ“¦ 5 Β· ⏱️ 14.12.2021): +- [PyPi](https://pypi.org/project/huey) (πŸ“₯ 59K / month Β· πŸ“¦ 160 Β· ⏱️ 28.12.2021): ``` - pip install tfx + pip install huey + ``` +- [Conda](https://anaconda.org/conda-forge/huey) (πŸ“₯ 23K Β· ⏱️ 16.10.2019): + ``` + conda install -c conda-forge huey ```
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streamparse (πŸ₯‰28 Β· ⭐ 1.4K) - Run Python in Apache Storm topologies. Pythonic API, CLI.. Apache-2 +
TFX (πŸ₯ˆ30 Β· ⭐ 1.7K) - TFX is an end-to-end platform for deploying production ML pipelines. Apache-2 -- [GitHub](https://github.com/Parsely/streamparse) (πŸ‘¨β€πŸ’» 42 Β· πŸ”€ 220 Β· πŸ“¦ 53 Β· πŸ“‹ 330 - 21% open Β· ⏱️ 10.01.2022): +- [GitHub](https://github.com/tensorflow/tfx) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 520 Β· πŸ“‹ 740 - 33% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/Parsely/streamparse + git clone https://github.com/tensorflow/tfx ``` -- [PyPi](https://pypi.org/project/streamparse) (πŸ“₯ 2.7K / month Β· πŸ“¦ 27 Β· ⏱️ 10.01.2022): +- [PyPi](https://pypi.org/project/tfx) (πŸ“₯ 310K / month Β· πŸ“¦ 7 Β· ⏱️ 08.02.2022): ``` - pip install streamparse + pip install tfx ```
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petl (πŸ₯‰28 Β· ⭐ 960) - Python Extract Transform and Load Tables of Data. MIT +
ploomber (πŸ₯‰29 Β· ⭐ 1.2K) - The fastest way to build data pipelines. Develop iteratively,.. Apache-2 -- [GitHub](https://github.com/petl-developers/petl) (πŸ‘¨β€πŸ’» 52 Β· πŸ”€ 170 Β· πŸ“¦ 610 Β· πŸ“‹ 420 - 16% open Β· ⏱️ 04.01.2022): +- [GitHub](https://github.com/ploomber/ploomber) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 92 Β· πŸ“¦ 28 Β· πŸ“‹ 510 - 26% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/petl-developers/petl + git clone https://github.com/ploomber/ploomber ``` -- [PyPi](https://pypi.org/project/petl) (πŸ“₯ 39K / month Β· πŸ“¦ 73 Β· ⏱️ 27.03.2021): +- [PyPi](https://pypi.org/project/ploomber) (πŸ“₯ 7.7K / month Β· πŸ“¦ 4 Β· ⏱️ 09.02.2022): ``` - pip install petl + pip install ploomber ``` -- [Conda](https://anaconda.org/conda-forge/petl) (πŸ“₯ 63K Β· ⏱️ 05.04.2021): +- [Conda](https://anaconda.org/conda-forge/ploomber) (πŸ“₯ 3.9K Β· ⏱️ 03.02.2022): ``` - conda install -c conda-forge petl + conda install -c conda-forge ploomber ```
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Optimus (πŸ₯‰27 Β· ⭐ 1.2K) - Agile Data Preparation Workflows madeeasy with Pandas, Dask,.. Apache-2 +
streamparse (πŸ₯‰28 Β· ⭐ 1.5K) - Run Python in Apache Storm topologies. Pythonic API, CLI.. Apache-2 -- [GitHub](https://github.com/hi-primus/optimus) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 200 Β· πŸ“‹ 220 - 13% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/Parsely/streamparse) (πŸ‘¨β€πŸ’» 42 Β· πŸ”€ 220 Β· πŸ“¦ 53 Β· πŸ“‹ 330 - 21% open Β· ⏱️ 10.01.2022): ``` - git clone https://github.com/hi-primus/optimus + git clone https://github.com/Parsely/streamparse ``` -- [PyPi](https://pypi.org/project/optimuspyspark) (πŸ“₯ 12K / month Β· ⏱️ 30.05.2019): +- [PyPi](https://pypi.org/project/streamparse) (πŸ“₯ 2.4K / month Β· πŸ“¦ 27 Β· ⏱️ 10.01.2022): ``` - pip install optimuspyspark + pip install streamparse ```
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PyFunctional (πŸ₯‰26 Β· ⭐ 2K) - Python library for creating data pipelines with chain functional.. MIT +
zenml (πŸ₯‰27 Β· ⭐ 1.6K) - ZenML : MLOps framework to create reproducible pipelines. Apache-2 -- [GitHub](https://github.com/EntilZha/PyFunctional) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 110 Β· πŸ“¦ 380 Β· πŸ“‹ 120 - 4% open Β· ⏱️ 05.11.2021): +- [GitHub](https://github.com/zenml-io/zenml) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 100 Β· πŸ“‹ 58 - 17% open Β· ⏱️ 08.02.2022): ``` - git clone https://github.com/EntilZha/PyFunctional + git clone https://github.com/zenml-io/zenml ``` -- [PyPi](https://pypi.org/project/pyfunctional) (πŸ“₯ 71K / month Β· πŸ“¦ 12 Β· ⏱️ 12.01.2021): +- [PyPi](https://pypi.org/project/zenml) (πŸ“₯ 1.3K / month Β· ⏱️ 07.02.2022): ``` - pip install pyfunctional + pip install zenml ```
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zenml (πŸ₯‰26 Β· ⭐ 1.6K) - ZenML : MLOps framework to create reproducible pipelines. Apache-2 +
Optimus (πŸ₯‰27 Β· ⭐ 1.2K) - Agile Data Preparation Workflows madeeasy with Pandas, Dask,.. Apache-2 -- [GitHub](https://github.com/zenml-io/zenml) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 93 Β· πŸ“‹ 56 - 16% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/hi-primus/optimus) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 200 Β· πŸ“‹ 230 - 14% open Β· ⏱️ 07.02.2022): ``` - git clone https://github.com/maiot-io/zenml + git clone https://github.com/hi-primus/optimus ``` -- [PyPi](https://pypi.org/project/zenml) (πŸ“₯ 570 / month Β· ⏱️ 13.01.2022): +- [PyPi](https://pypi.org/project/optimuspyspark) (πŸ“₯ 21K / month Β· ⏱️ 30.05.2019): ``` - pip install zenml + pip install optimuspyspark ```
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ploomber (πŸ₯‰26 Β· ⭐ 870) - Write maintainable, production-ready pipelines using Jupyter or your.. Apache-2 +
PyFunctional (πŸ₯‰26 Β· ⭐ 2K) - Python library for creating data pipelines with chain functional.. MIT -- [GitHub](https://github.com/ploomber/ploomber) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 66 Β· πŸ“¦ 26 Β· πŸ“‹ 430 - 21% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/EntilZha/PyFunctional) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 110 Β· πŸ“¦ 390 Β· πŸ“‹ 130 - 5% open Β· ⏱️ 05.11.2021): ``` - git clone https://github.com/ploomber/ploomber + git clone https://github.com/EntilZha/PyFunctional ``` -- [PyPi](https://pypi.org/project/ploomber) (πŸ“₯ 4.3K / month Β· πŸ“¦ 4 Β· ⏱️ 08.01.2022): +- [PyPi](https://pypi.org/project/pyfunctional) (πŸ“₯ 86K / month Β· πŸ“¦ 12 Β· ⏱️ 12.01.2021): ``` - pip install ploomber + pip install pyfunctional ```
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bonobo (πŸ₯‰24 Β· ⭐ 1.5K Β· πŸ’€) - Extract Transform Load for Python 3.5+. Apache-2 +
bonobo (πŸ₯‰25 Β· ⭐ 1.5K Β· πŸ’€) - Extract Transform Load for Python 3.5+. Apache-2 - [GitHub](https://github.com/python-bonobo/bonobo) (πŸ‘¨β€πŸ’» 37 Β· πŸ”€ 120 Β· πŸ“¦ 130 Β· πŸ“‹ 200 - 46% open Β· ⏱️ 10.03.2021): ``` git clone https://github.com/python-bonobo/bonobo ``` -- [PyPi](https://pypi.org/project/bonobo) (πŸ“₯ 3.2K / month Β· πŸ“¦ 33 Β· ⏱️ 20.07.2019): +- [PyPi](https://pypi.org/project/bonobo) (πŸ“₯ 8.6K / month Β· πŸ“¦ 33 Β· ⏱️ 20.07.2019): ``` pip install bonobo ```
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arq (πŸ₯‰24 Β· ⭐ 1.1K) - Fast job queuing and RPC in python with asyncio and redis. MIT +
arq (πŸ₯‰25 Β· ⭐ 1.1K) - Fast job queuing and RPC in python with asyncio and redis. MIT -- [GitHub](https://github.com/samuelcolvin/arq) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 84 Β· πŸ“¦ 160 Β· πŸ“‹ 120 - 27% open Β· ⏱️ 15.10.2021): +- [GitHub](https://github.com/samuelcolvin/arq) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 86 Β· πŸ“¦ 180 Β· πŸ“‹ 130 - 26% open Β· ⏱️ 26.01.2022): ``` git clone https://github.com/samuelcolvin/arq ``` -- [PyPi](https://pypi.org/project/arq) (πŸ“₯ 15K / month Β· πŸ“¦ 10 Β· ⏱️ 02.09.2021): +- [PyPi](https://pypi.org/project/arq) (πŸ“₯ 18K / month Β· πŸ“¦ 10 Β· ⏱️ 02.09.2021): ``` pip install arq ``` +- [Conda](https://anaconda.org/conda-forge/arq) (πŸ“₯ 1.7K Β· ⏱️ 03.09.2021): + ``` + conda install -c conda-forge arq + ```
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whylogs (πŸ₯‰23 Β· ⭐ 720) - Open standard for end-to-end data and ML monitoring for any scale in.. Apache-2 +
Pypeline (πŸ₯‰23 Β· ⭐ 1.3K) - Concurrent data pipelines in Python . MIT -- [GitHub](https://github.com/whylabs/whylogs) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 39 Β· πŸ“₯ 47 Β· πŸ“‹ 110 - 44% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/cgarciae/pypeln) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 77 Β· πŸ“‹ 57 - 26% open Β· ⏱️ 06.01.2022): ``` - git clone https://github.com/whylabs/whylogs + git clone https://github.com/cgarciae/pypeln ``` -- [PyPi](https://pypi.org/project/whylogs) (πŸ“₯ 3.3K / month Β· ⏱️ 08.01.2022): +- [PyPi](https://pypi.org/project/pypeln) (πŸ“₯ 10K / month Β· πŸ“¦ 9 Β· ⏱️ 06.01.2022): ``` - pip install whylogs + pip install pypeln + ``` +- [Conda](https://anaconda.org/conda-forge/pypeln) (πŸ“₯ 4.6K Β· ⏱️ 06.01.2022): + ``` + conda install -c conda-forge pypeln ```
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pdpipe (πŸ₯‰23 Β· ⭐ 640) - Easy pipelines for pandas DataFrames. MIT +
TaskTiger (πŸ₯‰23 Β· ⭐ 1.1K) - Python task queue using Redis. MIT -- [GitHub](https://github.com/pdpipe/pdpipe) (πŸ‘¨β€πŸ’» 9 Β· πŸ”€ 30 Β· πŸ“¦ 38 Β· πŸ“‹ 40 - 35% open Β· ⏱️ 26.12.2021): +- [GitHub](https://github.com/closeio/tasktiger) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 62 Β· πŸ“¦ 22 Β· πŸ“‹ 68 - 48% open Β· ⏱️ 07.02.2022): ``` - git clone https://github.com/pdpipe/pdpipe + git clone https://github.com/closeio/tasktiger ``` -- [PyPi](https://pypi.org/project/pdpipe) (πŸ“₯ 2.2K / month Β· πŸ“¦ 5 Β· ⏱️ 26.12.2021): +- [PyPi](https://pypi.org/project/tasktiger) (πŸ“₯ 2.2K / month Β· πŸ“¦ 10 Β· ⏱️ 02.12.2021): ``` - pip install pdpipe + pip install tasktiger ```
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Pypeline (πŸ₯‰22 Β· ⭐ 1.3K) - Concurrent data pipelines in Python . MIT +
whylogs (πŸ₯‰23 Β· ⭐ 750) - Open standard for end-to-end data and ML monitoring for any scale in.. Apache-2 -- [GitHub](https://github.com/cgarciae/pypeln) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 77 Β· πŸ“‹ 57 - 26% open Β· ⏱️ 06.01.2022): +- [GitHub](https://github.com/whylabs/whylogs) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 39 Β· πŸ“₯ 49 Β· πŸ“‹ 110 - 43% open Β· ⏱️ 09.02.2022): ``` - git clone https://github.com/cgarciae/pypeln + git clone https://github.com/whylabs/whylogs ``` -- [PyPi](https://pypi.org/project/pypeln) (πŸ“₯ 4.7K / month Β· πŸ“¦ 9 Β· ⏱️ 06.01.2022): +- [PyPi](https://pypi.org/project/whylogs) (πŸ“₯ 8K / month Β· πŸ“¦ 2 Β· ⏱️ 08.02.2022): ``` - pip install pypeln + pip install whylogs ```
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TaskTiger (πŸ₯‰22 Β· ⭐ 1.1K) - Python task queue using Redis. MIT +
pdpipe (πŸ₯‰23 Β· ⭐ 650) - Easy pipelines for pandas DataFrames. MIT -- [GitHub](https://github.com/closeio/tasktiger) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 62 Β· πŸ“¦ 22 Β· πŸ“‹ 68 - 48% open Β· ⏱️ 02.12.2021): +- [GitHub](https://github.com/pdpipe/pdpipe) (πŸ‘¨β€πŸ’» 9 Β· πŸ”€ 32 Β· πŸ“¦ 40 Β· πŸ“‹ 41 - 34% open Β· ⏱️ 30.01.2022): ``` - git clone https://github.com/closeio/tasktiger + git clone https://github.com/pdpipe/pdpipe ``` -- [PyPi](https://pypi.org/project/tasktiger) (πŸ“₯ 1.6K / month Β· πŸ“¦ 10 Β· ⏱️ 02.12.2021): +- [PyPi](https://pypi.org/project/pdpipe) (πŸ“₯ 2.9K / month Β· πŸ“¦ 5 Β· ⏱️ 30.01.2022): ``` - pip install tasktiger + pip install pdpipe + ``` +- [Conda](https://anaconda.org/conda-forge/pdpipe) (πŸ“₯ 3K Β· ⏱️ 26.12.2021): + ``` + conda install -c conda-forge pdpipe ```
riko (πŸ₯‰20 Β· ⭐ 1.6K) - A Python stream processing engine modeled after Yahoo! Pipes. MIT @@ -5119,7 +5524,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched ``` git clone https://github.com/nerevu/riko ``` -- [PyPi](https://pypi.org/project/riko) (πŸ“₯ 220 / month Β· πŸ“¦ 1 Β· ⏱️ 28.12.2021): +- [PyPi](https://pypi.org/project/riko) (πŸ“₯ 290 / month Β· πŸ“¦ 1 Β· ⏱️ 28.12.2021): ``` pip install riko ``` @@ -5132,54 +5537,55 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched git clone https://github.com/databricks/spark-deep-learning ```
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Databolt Flow (πŸ₯‰19 Β· ⭐ 930) - Python library for building highly effective data science workflows. MIT +
Databolt Flow (πŸ₯‰19 Β· ⭐ 940) - Python library for building highly effective data science workflows. MIT -- [GitHub](https://github.com/d6t/d6tflow) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 69 Β· πŸ“¦ 17 Β· πŸ“‹ 23 - 43% open Β· ⏱️ 28.09.2021): +- [GitHub](https://github.com/d6t/d6tflow) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 69 Β· πŸ“¦ 19 Β· πŸ“‹ 23 - 43% open Β· ⏱️ 28.09.2021): ``` git clone https://github.com/d6t/d6tflow ``` -- [PyPi](https://pypi.org/project/d6tflow) (πŸ“₯ 200 / month Β· ⏱️ 06.10.2021): +- [PyPi](https://pypi.org/project/d6tflow) (πŸ“₯ 210 / month Β· ⏱️ 06.10.2021): ``` pip install d6tflow ```
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Mara Pipelines (πŸ₯‰16 Β· ⭐ 1.8K) - A lightweight opinionated ETL framework, halfway between plain.. MIT +
kale (πŸ₯‰18 Β· ⭐ 480) - Kubeflows superfood for Data Scientists. Apache-2 -- [GitHub](https://github.com/mara/mara-pipelines) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 86 Β· πŸ“¦ 8 Β· πŸ“‹ 24 - 45% open Β· ⏱️ 18.09.2021): +- [GitHub](https://github.com/kubeflow-kale/kale) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 94 Β· πŸ“‹ 160 - 53% open Β· ⏱️ 20.10.2021): ``` - git clone https://github.com/mara/mara-pipelines + git clone https://github.com/kubeflow-kale/kale ``` -- [PyPi](https://pypi.org/project/mara-pipelines) (πŸ“₯ 79 / month Β· ⏱️ 23.01.2021): +- [PyPi](https://pypi.org/project/kubeflow-kale) (πŸ“₯ 1.1K / month Β· ⏱️ 19.05.2021): ``` - pip install mara-pipelines + pip install kubeflow-kale ```
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kale (πŸ₯‰16 Β· ⭐ 470) - Kubeflows superfood for Data Scientists. Apache-2 +
Mara Pipelines (πŸ₯‰17 Β· ⭐ 1.9K) - A lightweight opinionated ETL framework, halfway between plain.. MIT -- [GitHub](https://github.com/kubeflow-kale/kale) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 89 Β· πŸ“‹ 160 - 53% open Β· ⏱️ 20.10.2021): +- [GitHub](https://github.com/mara/mara-pipelines) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 86 Β· πŸ“¦ 8 Β· πŸ“‹ 24 - 45% open Β· ⏱️ 18.09.2021): ``` - git clone https://github.com/kubeflow-kale/kale + git clone https://github.com/mara/mara-pipelines ``` -- [PyPi](https://pypi.org/project/kubeflow-kale) (πŸ“₯ 980 / month Β· ⏱️ 19.05.2021): +- [PyPi](https://pypi.org/project/mara-pipelines) (πŸ“₯ 250 / month Β· ⏱️ 23.01.2021): ``` - pip install kubeflow-kale + pip install mara-pipelines ```
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Show 10 hidden projects... +
Show 11 hidden projects... - mrjob (πŸ₯ˆ32 Β· ⭐ 2.6K Β· πŸ’€) - Run MapReduce jobs on Hadoop or Amazon Web Services. Apache-2 -- faust (πŸ₯ˆ31 Β· ⭐ 5.9K Β· πŸ’€) - Python Stream Processing. BSD-3 -- dbnd (πŸ₯‰25 Β· ⭐ 210) - DBND is an agile pipeline framework that helps data engineering teams.. Apache-2 +- faust (πŸ₯ˆ31 Β· ⭐ 6K Β· πŸ’€) - Python Stream Processing. BSD-3 +- dbnd (πŸ₯‰26 Β· ⭐ 220) - DBND is an agile pipeline framework that helps data engineering teams.. Apache-2 - dpark (πŸ₯‰22 Β· ⭐ 2.7K Β· πŸ’€) - Python clone of Spark, a MapReduce alike framework in Python. BSD-3 - pysparkling (πŸ₯‰22 Β· ⭐ 240 Β· πŸ’€) - A pure Python implementation of Apache Sparks RDD and DStream.. MIT - mrq (πŸ₯‰21 Β· ⭐ 860 Β· πŸ’€) - Mr. Queue - A distributed worker task queue in Python using Redis & gevent. MIT - BatchFlow (πŸ₯‰20 Β· ⭐ 170) - BatchFlow helps you conveniently work with random or sequential.. Apache-2 -- bodywork-core (πŸ₯‰18 Β· ⭐ 320) - ML pipeline orchestration and model deployments on.. ❗️AGPL-3.0 -- flupy (πŸ₯‰17 Β· ⭐ 170 Β· πŸ“‰) - Fluent data pipelines for python and your shell. MIT +- bodywork-core (πŸ₯‰17 Β· ⭐ 320) - ML pipeline orchestration and model deployments on.. ❗️AGPL-3.0 +- flupy (πŸ₯‰17 Β· ⭐ 170) - Fluent data pipelines for python and your shell. MIT - Botflow (πŸ₯‰15 Β· ⭐ 1.2K Β· πŸ’€) - Python Fast Dataflow programming framework for Data pipeline work(.. BSD-3 +- datajob (πŸ₯‰14 Β· ⭐ 83 Β· βž•) - Build and deploy a serverless data pipeline on AWS with no effort. Apache-2

@@ -5191,84 +5597,88 @@ _Libraries that provide capabilities to distribute and parallelize machine learn
Ray (πŸ₯‡43 Β· ⭐ 19K) - An open source framework that provides a simple, universal API for.. Apache-2 -- [GitHub](https://github.com/ray-project/ray) (πŸ‘¨β€πŸ’» 610 Β· πŸ”€ 3.2K Β· πŸ“¦ 3.7K Β· πŸ“‹ 9.2K - 24% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/ray-project/ray) (πŸ‘¨β€πŸ’» 630 Β· πŸ”€ 3.2K Β· πŸ“¦ 3.9K Β· πŸ“‹ 9.5K - 24% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/ray-project/ray ``` -- [PyPi](https://pypi.org/project/ray) (πŸ“₯ 620K / month Β· πŸ“¦ 230 Β· ⏱️ 11.01.2022): +- [PyPi](https://pypi.org/project/ray) (πŸ“₯ 850K / month Β· πŸ“¦ 230 Β· ⏱️ 04.02.2022): ``` pip install ray ``` +- [Conda](https://anaconda.org/conda-forge/ray-tune) (πŸ“₯ 22K Β· ⏱️ 07.02.2022): + ``` + conda install -c conda-forge ray-tune + ```
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dask (πŸ₯‡43 Β· ⭐ 9.4K) - Parallel computing with task scheduling. BSD-3 +
dask (πŸ₯‡43 Β· ⭐ 9.5K) - Parallel computing with task scheduling. BSD-3 -- [GitHub](https://github.com/dask/dask) (πŸ‘¨β€πŸ’» 500 Β· πŸ”€ 1.4K Β· πŸ“¦ 33K Β· πŸ“‹ 4.1K - 18% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/dask/dask) (πŸ‘¨β€πŸ’» 510 Β· πŸ”€ 1.4K Β· πŸ“¦ 34K Β· πŸ“‹ 4.2K - 18% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/dask/dask ``` -- [PyPi](https://pypi.org/project/dask) (πŸ“₯ 4.5M / month Β· πŸ“¦ 2.5K Β· ⏱️ 10.12.2021): +- [PyPi](https://pypi.org/project/dask) (πŸ“₯ 7.6M / month Β· πŸ“¦ 2.6K Β· ⏱️ 28.01.2022): ``` pip install dask ``` -- [Conda](https://anaconda.org/conda-forge/dask) (πŸ“₯ 4.8M Β· ⏱️ 11.12.2021): +- [Conda](https://anaconda.org/conda-forge/dask) (πŸ“₯ 5M Β· ⏱️ 29.01.2022): ``` conda install -c conda-forge dask ```
dask.distributed (πŸ₯‡40 Β· ⭐ 1.3K) - A distributed task scheduler for Dask. BSD-3 -- [GitHub](https://github.com/dask/distributed) (πŸ‘¨β€πŸ’» 260 Β· πŸ”€ 580 Β· πŸ“¦ 22K Β· πŸ“‹ 2.5K - 34% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/dask/distributed) (πŸ‘¨β€πŸ’» 260 Β· πŸ”€ 590 Β· πŸ“¦ 22K Β· πŸ“‹ 2.6K - 35% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/dask/distributed ``` -- [PyPi](https://pypi.org/project/distributed) (πŸ“₯ 4.4M / month Β· πŸ“¦ 1.1K Β· ⏱️ 10.12.2021): +- [PyPi](https://pypi.org/project/distributed) (πŸ“₯ 6.6M / month Β· πŸ“¦ 1.2K Β· ⏱️ 28.01.2022): ``` pip install distributed ``` -- [Conda](https://anaconda.org/conda-forge/distributed) (πŸ“₯ 6.1M Β· ⏱️ 11.12.2021): +- [Conda](https://anaconda.org/conda-forge/distributed) (πŸ“₯ 6.2M Β· ⏱️ 29.01.2022): ``` conda install -c conda-forge distributed ```
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horovod (πŸ₯ˆ36 Β· ⭐ 12K) - Distributed training framework for TensorFlow, Keras, PyTorch, and.. Apache-2 +
horovod (πŸ₯‡36 Β· ⭐ 12K) - Distributed training framework for TensorFlow, Keras, PyTorch, and.. Apache-2 -- [GitHub](https://github.com/horovod/horovod) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 1.9K Β· πŸ“¦ 480 Β· πŸ“‹ 1.9K - 13% open Β· ⏱️ 10.01.2022): +- [GitHub](https://github.com/horovod/horovod) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 2K Β· πŸ“¦ 500 Β· πŸ“‹ 1.9K - 14% open Β· ⏱️ 04.02.2022): ``` git clone https://github.com/horovod/horovod ``` -- [PyPi](https://pypi.org/project/horovod) (πŸ“₯ 38K / month Β· πŸ“¦ 29 Β· ⏱️ 06.10.2021): +- [PyPi](https://pypi.org/project/horovod) (πŸ“₯ 48K / month Β· πŸ“¦ 29 Β· ⏱️ 06.10.2021): ``` pip install horovod ```
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ipyparallel (πŸ₯ˆ33 Β· ⭐ 2.1K) - IPython Parallel: Interactive Parallel Computing in Python. BSD-3 +
ipyparallel (πŸ₯ˆ34 Β· ⭐ 2.2K) - IPython Parallel: Interactive Parallel Computing in Python. BSD-3 -- [GitHub](https://github.com/ipython/ipyparallel) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 850 Β· πŸ“¦ 1.8K Β· πŸ“‹ 320 - 15% open Β· ⏱️ 10.01.2022): +- [GitHub](https://github.com/ipython/ipyparallel) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 860 Β· πŸ“¦ 1.8K Β· πŸ“‹ 320 - 15% open Β· ⏱️ 07.02.2022): ``` git clone https://github.com/ipython/ipyparallel ``` -- [PyPi](https://pypi.org/project/ipyparallel) (πŸ“₯ 44K / month Β· πŸ“¦ 280 Β· ⏱️ 22.12.2021): +- [PyPi](https://pypi.org/project/ipyparallel) (πŸ“₯ 54K / month Β· πŸ“¦ 280 Β· ⏱️ 07.02.2022): ``` pip install ipyparallel ``` -- [Conda](https://anaconda.org/conda-forge/ipyparallel) (πŸ“₯ 550K Β· ⏱️ 23.12.2021): +- [Conda](https://anaconda.org/conda-forge/ipyparallel) (πŸ“₯ 560K Β· ⏱️ 07.02.2022): ``` conda install -c conda-forge ipyparallel ```
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BigDL (πŸ₯ˆ31 Β· ⭐ 3.8K) - Building Large-Scale AI Applications for Distributed Big Data. Apache-2 +
BigDL (πŸ₯ˆ32 Β· ⭐ 3.8K) - Building Large-Scale AI Applications for Distributed Big Data. Apache-2 -- [GitHub](https://github.com/intel-analytics/BigDL) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 960 Β· πŸ“¦ 32 Β· πŸ“‹ 1.1K - 30% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/intel-analytics/BigDL) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 970 Β· πŸ“¦ 33 Β· πŸ“‹ 1.2K - 31% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/intel-analytics/BigDL ``` -- [PyPi](https://pypi.org/project/bigdl) (πŸ“₯ 5.7K / month Β· πŸ“¦ 1 Β· ⏱️ 13.01.2022): +- [PyPi](https://pypi.org/project/bigdl) (πŸ“₯ 14K / month Β· πŸ“¦ 1 Β· ⏱️ 10.02.2022): ``` pip install bigdl ``` @@ -5281,14 +5691,14 @@ _Libraries that provide capabilities to distribute and parallelize machine learn ```
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DeepSpeed (πŸ₯ˆ30 Β· ⭐ 6.1K) - DeepSpeed is a deep learning optimization library that makes.. MIT +
DeepSpeed (πŸ₯ˆ31 Β· ⭐ 6.3K) - DeepSpeed is a deep learning optimization library that makes.. MIT -- [GitHub](https://github.com/microsoft/DeepSpeed) (πŸ‘¨β€πŸ’» 87 Β· πŸ”€ 660 Β· πŸ“¦ 140 Β· πŸ“‹ 760 - 49% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/microsoft/DeepSpeed) (πŸ‘¨β€πŸ’» 89 Β· πŸ”€ 680 Β· πŸ“¦ 160 Β· πŸ“‹ 770 - 48% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/microsoft/DeepSpeed ``` -- [PyPi](https://pypi.org/project/deepspeed) (πŸ“₯ 43K / month Β· πŸ“¦ 9 Β· ⏱️ 04.01.2022): +- [PyPi](https://pypi.org/project/deepspeed) (πŸ“₯ 72K / month Β· πŸ“¦ 9 Β· ⏱️ 19.01.2022): ``` pip install deepspeed ``` @@ -5297,215 +5707,263 @@ _Libraries that provide capabilities to distribute and parallelize machine learn docker pull deepspeed/deepspeed ```
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FairScale (πŸ₯ˆ29 Β· ⭐ 1.6K) - PyTorch extensions for high performance and large scale training. BSD-3 +
metrics (πŸ₯ˆ31 Β· ⭐ 670) - Machine learning metrics for distributed, scalable PyTorch.. Apache-2 + +- [GitHub](https://github.com/PyTorchLightning/metrics) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 150 Β· πŸ“₯ 430 Β· πŸ“¦ 1.8K Β· πŸ“‹ 300 - 21% open Β· ⏱️ 10.02.2022): + + ``` + git clone https://github.com/PyTorchLightning/metrics + ``` +- [PyPi](https://pypi.org/project/metrics) (πŸ“₯ 2.7K / month Β· πŸ“¦ 14 Β· ⏱️ 28.04.2018): + ``` + pip install metrics + ``` +- [Conda](https://anaconda.org/conda-forge/torchmetrics) (πŸ“₯ 280K Β· ⏱️ 04.02.2022): + ``` + conda install -c conda-forge torchmetrics + ``` +
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FairScale (πŸ₯ˆ30 Β· ⭐ 1.6K) - PyTorch extensions for high performance and large scale training. BSD-3 -- [GitHub](https://github.com/facebookresearch/fairscale) (πŸ‘¨β€πŸ’» 53 Β· πŸ”€ 140 Β· πŸ“¦ 140 Β· πŸ“‹ 270 - 23% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/facebookresearch/fairscale) (πŸ‘¨β€πŸ’» 54 Β· πŸ”€ 150 Β· πŸ“¦ 160 Β· πŸ“‹ 270 - 22% open Β· ⏱️ 08.02.2022): ``` git clone https://github.com/facebookresearch/fairscale ``` -- [PyPi](https://pypi.org/project/fairscale) (πŸ“₯ 38K / month Β· πŸ“¦ 13 Β· ⏱️ 21.12.2021): +- [PyPi](https://pypi.org/project/fairscale) (πŸ“₯ 59K / month Β· πŸ“¦ 13 Β· ⏱️ 14.01.2022): ``` pip install fairscale ``` +- [Conda](https://anaconda.org/conda-forge/fairscale) (πŸ“₯ 4.8K Β· ⏱️ 05.02.2022): + ``` + conda install -c conda-forge fairscale + ```
dask-ml (πŸ₯ˆ29 Β· ⭐ 780) - Scalable Machine Learning with Dask. BSD-3 -- [GitHub](https://github.com/dask/dask-ml) (πŸ‘¨β€πŸ’» 70 Β· πŸ”€ 220 Β· πŸ“¦ 540 Β· πŸ“‹ 460 - 48% open Β· ⏱️ 05.01.2022): +- [GitHub](https://github.com/dask/dask-ml) (πŸ‘¨β€πŸ’» 71 Β· πŸ”€ 220 Β· πŸ“¦ 550 Β· πŸ“‹ 470 - 49% open Β· ⏱️ 20.01.2022): ``` git clone https://github.com/dask/dask-ml ``` -- [PyPi](https://pypi.org/project/dask-ml) (πŸ“₯ 47K / month Β· πŸ“¦ 55 Β· ⏱️ 30.11.2021): +- [PyPi](https://pypi.org/project/dask-ml) (πŸ“₯ 62K / month Β· πŸ“¦ 55 Β· ⏱️ 22.01.2022): ``` pip install dask-ml ``` -- [Conda](https://anaconda.org/conda-forge/dask-ml) (πŸ“₯ 260K Β· ⏱️ 30.11.2021): +- [Conda](https://anaconda.org/conda-forge/dask-ml) (πŸ“₯ 260K Β· ⏱️ 22.01.2022): ``` conda install -c conda-forge dask-ml ```
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metrics (πŸ₯ˆ29 Β· ⭐ 610) - Machine learning metrics for distributed, scalable PyTorch.. Apache-2 +
analytics-zoo (πŸ₯ˆ28 Β· ⭐ 2.5K) - Distributed Tensorflow, Keras and PyTorch on Apache.. Apache-2 -- [GitHub](https://github.com/PyTorchLightning/metrics) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 140 Β· πŸ“₯ 360 Β· πŸ“¦ 1.6K Β· πŸ“‹ 260 - 17% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/intel-analytics/analytics-zoo) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 710 Β· πŸ“¦ 3 Β· πŸ“‹ 1.4K - 40% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/PyTorchLightning/metrics + git clone https://github.com/intel-analytics/analytics-zoo ``` -- [PyPi](https://pypi.org/project/metrics) (πŸ“₯ 2.8K / month Β· πŸ“¦ 14 Β· ⏱️ 28.04.2018): +- [PyPi](https://pypi.org/project/analytics-zoo) (πŸ“₯ 9.5K / month Β· πŸ“¦ 1 Β· ⏱️ 09.02.2022): ``` - pip install metrics + pip install analytics-zoo ```
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petastorm (πŸ₯ˆ28 Β· ⭐ 1.3K) - Petastorm library enables single machine or distributed training.. Apache-2 +
petastorm (πŸ₯ˆ28 Β· ⭐ 1.4K) - Petastorm library enables single machine or distributed training.. Apache-2 -- [GitHub](https://github.com/uber/petastorm) (πŸ‘¨β€πŸ’» 43 Β· πŸ”€ 220 Β· πŸ“₯ 310 Β· πŸ“¦ 54 Β· πŸ“‹ 270 - 50% open Β· ⏱️ 10.01.2022): +- [GitHub](https://github.com/uber/petastorm) (πŸ‘¨β€πŸ’» 43 Β· πŸ”€ 230 Β· πŸ“₯ 310 Β· πŸ“¦ 54 Β· πŸ“‹ 270 - 49% open Β· ⏱️ 10.01.2022): ``` git clone https://github.com/uber/petastorm ``` -- [PyPi](https://pypi.org/project/petastorm) (πŸ“₯ 140K / month Β· πŸ“¦ 4 Β· ⏱️ 04.09.2021): +- [PyPi](https://pypi.org/project/petastorm) (πŸ“₯ 84K / month Β· πŸ“¦ 4 Β· ⏱️ 04.09.2021): ``` pip install petastorm ```
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mpi4py (πŸ₯ˆ28 Β· ⭐ 500) - Python bindings for MPI. BSD-2 +
MMLSpark (πŸ₯‰27 Β· ⭐ 3.1K) - Simple and Distributed Machine Learning. MIT -- [GitHub](https://github.com/mpi4py/mpi4py) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 74 Β· πŸ“₯ 2.9K Β· πŸ“‹ 62 - 22% open Β· ⏱️ 10.01.2022): +- [GitHub](https://github.com/microsoft/SynapseML) (πŸ‘¨β€πŸ’» 84 Β· πŸ”€ 640 Β· πŸ“‹ 540 - 43% open Β· ⏱️ 08.02.2022): ``` - git clone https://github.com/mpi4py/mpi4py - ``` -- [PyPi](https://pypi.org/project/mpi4py) (πŸ“₯ 200K / month Β· πŸ“¦ 580 Β· ⏱️ 15.12.2021): - ``` - pip install mpi4py + git clone https://github.com/microsoft/SynapseML ``` -- [Conda](https://anaconda.org/conda-forge/mpi4py) (πŸ“₯ 880K Β· ⏱️ 25.11.2021): +- [PyPi](https://pypi.org/project/mmlspark) (πŸ“₯ 46K / month Β· ⏱️ 18.03.2020): ``` - conda install -c conda-forge mpi4py + pip install mmlspark ```
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MMLSpark (πŸ₯‰27 Β· ⭐ 3.1K) - Simple and Distributed Machine Learning. MIT +
mpi4py (πŸ₯‰27 Β· ⭐ 500) - Python bindings for MPI. BSD-2 -- [GitHub](https://github.com/microsoft/SynapseML) (πŸ‘¨β€πŸ’» 81 Β· πŸ”€ 640 Β· πŸ“‹ 490 - 40% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/mpi4py/mpi4py) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 74 Β· πŸ“₯ 3.3K Β· πŸ“‹ 64 - 20% open Β· ⏱️ 26.01.2022): ``` - git clone https://github.com/Azure/mmlspark + git clone https://github.com/mpi4py/mpi4py ``` -- [PyPi](https://pypi.org/project/mmlspark) (πŸ“₯ 41K / month Β· ⏱️ 18.03.2020): +- [PyPi](https://pypi.org/project/mpi4py) (πŸ“₯ 160K / month Β· πŸ“¦ 580 Β· ⏱️ 15.12.2021): ``` - pip install mmlspark + pip install mpi4py + ``` +- [Conda](https://anaconda.org/conda-forge/mpi4py) (πŸ“₯ 920K Β· ⏱️ 25.11.2021): + ``` + conda install -c conda-forge mpi4py ```
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analytics-zoo (πŸ₯‰27 Β· ⭐ 2.5K) - Distributed Tensorflow, Keras and PyTorch on Apache.. Apache-2 +
TensorFlowOnSpark (πŸ₯‰26 Β· ⭐ 3.8K) - TensorFlowOnSpark brings TensorFlow programs to.. Apache-2 -- [GitHub](https://github.com/intel-analytics/analytics-zoo) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 710 Β· πŸ“¦ 3 Β· πŸ“‹ 1.4K - 40% open Β· ⏱️ 06.01.2022): +- [GitHub](https://github.com/yahoo/TensorFlowOnSpark) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 960 Β· πŸ“‹ 360 - 1% open Β· ⏱️ 10.01.2022): ``` - git clone https://github.com/intel-analytics/analytics-zoo + git clone https://github.com/yahoo/TensorFlowOnSpark ``` -- [PyPi](https://pypi.org/project/analytics-zoo) (πŸ“₯ 4.2K / month Β· ⏱️ 12.01.2022): +- [PyPi](https://pypi.org/project/tensorflowonspark) (πŸ“₯ 440K / month Β· πŸ“¦ 5 Β· ⏱️ 25.05.2021): ``` - pip install analytics-zoo + pip install tensorflowonspark + ``` +- [Conda](https://anaconda.org/conda-forge/tensorflowonspark) (πŸ“₯ 9.7K Β· ⏱️ 19.12.2020): + ``` + conda install -c conda-forge tensorflowonspark ```
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Elephas (πŸ₯‰27 Β· ⭐ 1.5K) - Distributed Deep learning with Keras & Spark. MIT keras +
SynapseML (πŸ₯‰26 Β· ⭐ 3.1K Β· βž•) - Simple and Distributed Machine Learning. MIT -- [GitHub](https://github.com/maxpumperla/elephas) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 290 Β· πŸ“¦ 52 Β· πŸ“‹ 160 - 15% open Β· ⏱️ 17.08.2021): +- [GitHub](https://github.com/microsoft/SynapseML) (πŸ‘¨β€πŸ’» 84 Β· πŸ”€ 640 Β· πŸ“‹ 540 - 43% open Β· ⏱️ 08.02.2022): ``` - git clone https://github.com/maxpumperla/elephas + git clone https://github.com/microsoft/SynapseML ``` -- [PyPi](https://pypi.org/project/elephas) (πŸ“₯ 17K / month Β· πŸ“¦ 3 Β· ⏱️ 17.08.2021): +- [PyPi](https://pypi.org/project/synapseml) (πŸ“₯ 5.1K / month Β· ⏱️ 12.01.2022): ``` - pip install elephas + pip install synapseml ```
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TensorFlowOnSpark (πŸ₯‰26 Β· ⭐ 3.8K) - TensorFlowOnSpark brings TensorFlow programs to.. Apache-2 +
Mesh (πŸ₯‰26 Β· ⭐ 1.2K) - Mesh TensorFlow: Model Parallelism Made Easier. Apache-2 -- [GitHub](https://github.com/yahoo/TensorFlowOnSpark) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 960 Β· πŸ“‹ 360 - 1% open Β· ⏱️ 10.01.2022): +- [GitHub](https://github.com/tensorflow/mesh) (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 200 Β· πŸ“¦ 630 Β· πŸ“‹ 100 - 86% open Β· ⏱️ 26.01.2022): ``` - git clone https://github.com/yahoo/TensorFlowOnSpark + git clone https://github.com/tensorflow/mesh ``` -- [PyPi](https://pypi.org/project/tensorflowonspark) (πŸ“₯ 380K / month Β· πŸ“¦ 5 Β· ⏱️ 25.05.2021): +- [PyPi](https://pypi.org/project/mesh-tensorflow) (πŸ“₯ 53K / month Β· πŸ“¦ 32 Β· ⏱️ 24.03.2021): ``` - pip install tensorflowonspark + pip install mesh-tensorflow ```
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Mesh (πŸ₯‰26 Β· ⭐ 1.2K) - Mesh TensorFlow: Model Parallelism Made Easier. Apache-2 +
Elephas (πŸ₯‰25 Β· ⭐ 1.5K Β· πŸ“‰) - Distributed Deep learning with Keras & Spark. MIT keras -- [GitHub](https://github.com/tensorflow/mesh) (πŸ‘¨β€πŸ’» 44 Β· πŸ”€ 200 Β· πŸ“¦ 620 Β· πŸ“‹ 100 - 86% open Β· ⏱️ 18.10.2021): +- [GitHub](https://github.com/maxpumperla/elephas) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 290 Β· πŸ“¦ 52 Β· πŸ“‹ 160 - 15% open Β· ⏱️ 17.08.2021): ``` - git clone https://github.com/tensorflow/mesh + git clone https://github.com/maxpumperla/elephas ``` -- [PyPi](https://pypi.org/project/mesh-tensorflow) (πŸ“₯ 160K / month Β· πŸ“¦ 32 Β· ⏱️ 24.03.2021): +- [PyPi](https://pypi.org/project/elephas) (πŸ“₯ 28K / month Β· πŸ“¦ 3 Β· ⏱️ 17.08.2021): ``` - pip install mesh-tensorflow + pip install elephas + ``` +- [Conda](https://anaconda.org/conda-forge/elephas) (πŸ“₯ 7.7K Β· ⏱️ 02.06.2021): + ``` + conda install -c conda-forge elephas ```
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Hivemind (πŸ₯‰21 Β· ⭐ 900) - Decentralized deep learning in PyTorch. Built to train models on.. MIT +
Hivemind (πŸ₯‰21 Β· ⭐ 910) - Decentralized deep learning in PyTorch. Built to train models on.. MIT -- [GitHub](https://github.com/learning-at-home/hivemind) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 58 Β· πŸ“¦ 4 Β· πŸ“‹ 110 - 36% open Β· ⏱️ 09.01.2022): +- [GitHub](https://github.com/learning-at-home/hivemind) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 59 Β· πŸ“¦ 4 Β· πŸ“‹ 120 - 36% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/learning-at-home/hivemind ``` -- [PyPi](https://pypi.org/project/hivemind) (πŸ“₯ 320 / month Β· πŸ“¦ 1 Β· ⏱️ 20.12.2021): +- [PyPi](https://pypi.org/project/hivemind) (πŸ“₯ 240 / month Β· πŸ“¦ 1 Β· ⏱️ 20.12.2021): ``` pip install hivemind ```
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Submit it (πŸ₯‰21 Β· ⭐ 520) - Python 3.6+ toolbox for submitting jobs to Slurm. MIT +
Submit it (πŸ₯‰21 Β· ⭐ 550) - Python 3.6+ toolbox for submitting jobs to Slurm. MIT -- [GitHub](https://github.com/facebookincubator/submitit) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 49 Β· πŸ“‹ 57 - 43% open Β· ⏱️ 09.12.2021): +- [GitHub](https://github.com/facebookincubator/submitit) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 52 Β· πŸ“‹ 58 - 43% open Β· ⏱️ 09.12.2021): ``` git clone https://github.com/facebookincubator/submitit ``` -- [PyPi](https://pypi.org/project/submitit) (πŸ“₯ 11K / month Β· πŸ“¦ 6 Β· ⏱️ 30.11.2021): +- [PyPi](https://pypi.org/project/submitit) (πŸ“₯ 14K / month Β· πŸ“¦ 6 Β· ⏱️ 30.11.2021): ``` pip install submitit ``` -- [Conda](https://anaconda.org/conda-forge/submitit) (πŸ“₯ 5.1K Β· ⏱️ 10.02.2021): +- [Conda](https://anaconda.org/conda-forge/submitit) (πŸ“₯ 5.2K Β· ⏱️ 10.02.2021): ``` conda install -c conda-forge submitit ```
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Apache Singa (πŸ₯‰20 Β· ⭐ 2.4K) - a distributed deep learning platform. Apache-2 +
BytePS (πŸ₯‰20 Β· ⭐ 3.1K) - A high performance and generic framework for distributed DNN training. Apache-2 -- [GitHub](https://github.com/apache/singa) (πŸ‘¨β€πŸ’» 76 Β· πŸ”€ 720 Β· πŸ“¦ 1 Β· πŸ“‹ 89 - 44% open Β· ⏱️ 10.08.2021): +- [GitHub](https://github.com/bytedance/byteps) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 430 Β· πŸ“‹ 260 - 38% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/apache/singa + git clone https://github.com/bytedance/byteps ``` -- [Conda](https://anaconda.org/nusdbsystem/singa) (πŸ“₯ 410 Β· ⏱️ 09.08.2021): +- [PyPi](https://pypi.org/project/byteps) (πŸ“₯ 84 / month Β· ⏱️ 02.08.2021): ``` - conda install -c nusdbsystem singa + pip install byteps ``` -- [Docker Hub](https://hub.docker.com/r/apache/singa) (πŸ“₯ 210 Β· ⭐ 4 Β· ⏱️ 04.06.2019): +- [Docker Hub](https://hub.docker.com/r/bytepsimage/tensorflow) (πŸ“₯ 1.2K Β· ⏱️ 03.03.2020): ``` - docker pull apache/singa + docker pull bytepsimage/tensorflow ```
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BytePS (πŸ₯‰19 Β· ⭐ 3K) - A high performance and generic framework for distributed DNN training. Apache-2 +
Apache Singa (πŸ₯‰20 Β· ⭐ 2.5K) - a distributed deep learning platform. Apache-2 -- [GitHub](https://github.com/bytedance/byteps) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 430 Β· πŸ“‹ 260 - 39% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/apache/singa) (πŸ‘¨β€πŸ’» 76 Β· πŸ”€ 760 Β· πŸ“¦ 1 Β· πŸ“‹ 89 - 44% open Β· ⏱️ 10.08.2021): ``` - git clone https://github.com/bytedance/byteps + git clone https://github.com/apache/singa ``` -- [PyPi](https://pypi.org/project/byteps) (πŸ“₯ 63 / month Β· ⏱️ 02.08.2021): +- [Conda](https://anaconda.org/nusdbsystem/singa) (πŸ“₯ 410 Β· ⏱️ 09.08.2021): ``` - pip install byteps + conda install -c nusdbsystem singa ``` -- [Docker Hub](https://hub.docker.com/r/bytepsimage/tensorflow) (πŸ“₯ 1.2K Β· ⏱️ 03.03.2020): +- [Docker Hub](https://hub.docker.com/r/apache/singa) (πŸ“₯ 220 Β· ⭐ 4 Β· ⏱️ 04.06.2019): ``` - docker pull bytepsimage/tensorflow + docker pull apache/singa ```
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Fiber (πŸ₯‰18 Β· ⭐ 950 Β· πŸ’€) - Distributed Computing for AI Made Simple. Apache-2 +
Fiber (πŸ₯‰18 Β· ⭐ 960 Β· πŸ’€) - Distributed Computing for AI Made Simple. Apache-2 - [GitHub](https://github.com/uber/fiber) (πŸ‘¨β€πŸ’» 5 Β· πŸ”€ 100 Β· πŸ“¦ 31 Β· πŸ“‹ 28 - 71% open Β· ⏱️ 15.03.2021): ``` git clone https://github.com/uber/fiber ``` -- [PyPi](https://pypi.org/project/fiber) (πŸ“₯ 1.5K / month Β· πŸ“¦ 1 Β· ⏱️ 09.07.2020): +- [PyPi](https://pypi.org/project/fiber) (πŸ“₯ 2K / month Β· πŸ“¦ 1 Β· ⏱️ 09.07.2020): ``` pip install fiber ```
+
parallelformers (πŸ₯‰18 Β· ⭐ 440 Β· βž•) - Parallelformers: An Efficient Model Parallelization.. Apache-2 + +- [GitHub](https://github.com/tunib-ai/parallelformers) (πŸ‘¨β€πŸ’» 3 Β· πŸ”€ 23 Β· πŸ“¦ 3 Β· πŸ“‹ 12 - 25% open Β· ⏱️ 29.12.2021): + + ``` + git clone https://github.com/tunib-ai/parallelformers + ``` +- [PyPi](https://pypi.org/project/parallelformers) (πŸ“₯ 220 / month Β· ⏱️ 29.12.2021): + ``` + pip install parallelformers + ``` +
+
mesh-transformer-jax (πŸ₯‰16 Β· ⭐ 3.8K Β· βž•) - Model parallel transformers in JAX and Haiku. Apache-2 + +- [GitHub](https://github.com/kingoflolz/mesh-transformer-jax) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 460 Β· πŸ“‹ 140 - 7% open Β· ⏱️ 28.01.2022): + + ``` + git clone https://github.com/kingoflolz/mesh-transformer-jax + ``` +
Show 7 hidden projects... - DEAP (πŸ₯ˆ32 Β· ⭐ 4.6K) - Distributed Evolutionary Algorithms in Python. ❗️LGPL-3.0 -- TensorFrames (πŸ₯‰20 Β· ⭐ 760 Β· πŸ’€) - [DEPRECATED] Tensorflow wrapper for DataFrames on.. Apache-2 +- TensorFrames (πŸ₯‰21 Β· ⭐ 760 Β· πŸ’€) - [DEPRECATED] Tensorflow wrapper for DataFrames on.. Apache-2 - launchpad (πŸ₯‰20 Β· ⭐ 250) - Launchpad is a library that simplifies writing distributed.. Apache-2 - somoclu (πŸ₯‰20 Β· ⭐ 230) - Massively parallel self-organizing maps: accelerate training on multicore.. MIT -- sk-dist (πŸ₯‰19 Β· ⭐ 270) - Distributed scikit-learn meta-estimators in PySpark. Apache-2 +- sk-dist (πŸ₯‰19 Β· ⭐ 280 Β· πŸ’€) - Distributed scikit-learn meta-estimators in PySpark. Apache-2 - LazyCluster (πŸ₯‰12 Β· ⭐ 43) - Distributed machine learning made simple. Apache-2 -- autodist (πŸ₯‰11 Β· ⭐ 120 Β· πŸ’€) - Simple Distributed Deep Learning on TensorFlow. Apache-2 +- autodist (πŸ₯‰11 Β· ⭐ 120 Β· πŸ’€) - Simple Distributed Deep Learning on TensorFlow. Apache-2

@@ -5515,333 +5973,346 @@ _Libraries that provide capabilities to distribute and parallelize machine learn _Libraries for hyperparameter optimization, automl and neural architecture search._ -
Optuna (πŸ₯‡38 Β· ⭐ 5.8K) - A hyperparameter optimization framework. MIT +
Optuna (πŸ₯‡38 Β· ⭐ 5.9K) - A hyperparameter optimization framework. MIT -- [GitHub](https://github.com/optuna/optuna) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 640 Β· πŸ“¦ 2.5K Β· πŸ“‹ 1.1K - 13% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/optuna/optuna) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 650 Β· πŸ“¦ 2.6K Β· πŸ“‹ 1.1K - 13% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/optuna/optuna ``` -- [PyPi](https://pypi.org/project/optuna) (πŸ“₯ 640K / month Β· πŸ“¦ 160 Β· ⏱️ 06.12.2021): +- [PyPi](https://pypi.org/project/optuna) (πŸ“₯ 830K / month Β· πŸ“¦ 180 Β· ⏱️ 07.02.2022): ``` pip install optuna ``` -- [Conda](https://anaconda.org/conda-forge/optuna) (πŸ“₯ 50K Β· ⏱️ 04.10.2021): +- [Conda](https://anaconda.org/conda-forge/optuna) (πŸ“₯ 96K Β· ⏱️ 04.10.2021): ``` conda install -c conda-forge optuna ```
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NNI (πŸ₯‡35 Β· ⭐ 11K) - An open source AutoML toolkit for automate machine learning lifecycle,.. MIT +
NNI (πŸ₯‡36 Β· ⭐ 11K) - An open source AutoML toolkit for automate machine learning lifecycle,.. MIT -- [GitHub](https://github.com/microsoft/nni) (πŸ‘¨β€πŸ’» 150 Β· πŸ”€ 1.5K Β· πŸ“¦ 170 Β· πŸ“‹ 1.5K - 16% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/microsoft/nni) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 1.5K Β· πŸ“¦ 180 Β· πŸ“‹ 1.5K - 17% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/microsoft/nni ``` -- [PyPi](https://pypi.org/project/nni) (πŸ“₯ 5.1K / month Β· πŸ“¦ 28 Β· ⏱️ 13.01.2022): +- [PyPi](https://pypi.org/project/nni) (πŸ“₯ 8.6K / month Β· πŸ“¦ 28 Β· ⏱️ 19.01.2022): ``` pip install nni ```
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featuretools (πŸ₯‡35 Β· ⭐ 5.9K) - An open source python library for automated feature engineering. BSD-3 +
featuretools (πŸ₯‡35 Β· ⭐ 6K) - An open source python library for automated feature engineering. BSD-3 -- [GitHub](https://github.com/alteryx/featuretools) (πŸ‘¨β€πŸ’» 57 Β· πŸ”€ 780 Β· πŸ“¦ 910 Β· πŸ“‹ 710 - 22% open Β· ⏱️ 11.01.2022): +- [GitHub](https://github.com/alteryx/featuretools) (πŸ‘¨β€πŸ’» 59 Β· πŸ”€ 780 Β· πŸ“¦ 920 Β· πŸ“‹ 730 - 22% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/alteryx/featuretools ``` -- [PyPi](https://pypi.org/project/featuretools) (πŸ“₯ 1.1M / month Β· πŸ“¦ 62 Β· ⏱️ 11.01.2022): +- [PyPi](https://pypi.org/project/featuretools) (πŸ“₯ 590K / month Β· πŸ“¦ 62 Β· ⏱️ 28.01.2022): ``` pip install featuretools ``` -- [Conda](https://anaconda.org/conda-forge/featuretools) (πŸ“₯ 76K Β· ⏱️ 11.01.2022): +- [Conda](https://anaconda.org/conda-forge/featuretools) (πŸ“₯ 78K Β· ⏱️ 01.02.2022): ``` conda install -c conda-forge featuretools ```
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Hyperopt (πŸ₯‡34 Β· ⭐ 6K) - Distributed Asynchronous Hyperparameter Optimization in Python. BSD-3 +
AutoKeras (πŸ₯‡34 Β· ⭐ 8.3K) - AutoML library for deep learning. Apache-2 -- [GitHub](https://github.com/hyperopt/hyperopt) (πŸ‘¨β€πŸ’» 93 Β· πŸ”€ 920 Β· πŸ“¦ 5.5K Β· πŸ“‹ 590 - 60% open Β· ⏱️ 29.11.2021): +- [GitHub](https://github.com/keras-team/autokeras) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 1.3K Β· πŸ“₯ 2.6K Β· πŸ“¦ 270 Β· πŸ“‹ 800 - 8% open Β· ⏱️ 08.02.2022): + + ``` + git clone https://github.com/keras-team/autokeras + ``` +- [PyPi](https://pypi.org/project/autokeras) (πŸ“₯ 40K / month Β· πŸ“¦ 10 Β· ⏱️ 03.02.2022): + ``` + pip install autokeras + ``` +
+
Hyperopt (πŸ₯‡34 Β· ⭐ 6.1K) - Distributed Asynchronous Hyperparameter Optimization in Python. BSD-3 + +- [GitHub](https://github.com/hyperopt/hyperopt) (πŸ‘¨β€πŸ’» 93 Β· πŸ”€ 920 Β· πŸ“¦ 5.7K Β· πŸ“‹ 590 - 60% open Β· ⏱️ 29.11.2021): ``` git clone https://github.com/hyperopt/hyperopt ``` -- [PyPi](https://pypi.org/project/hyperopt) (πŸ“₯ 1.7M / month Β· πŸ“¦ 400 Β· ⏱️ 17.11.2021): +- [PyPi](https://pypi.org/project/hyperopt) (πŸ“₯ 2M / month Β· πŸ“¦ 400 Β· ⏱️ 17.11.2021): ``` pip install hyperopt ``` -- [Conda](https://anaconda.org/conda-forge/hyperopt) (πŸ“₯ 320K Β· ⏱️ 14.10.2020): +- [Conda](https://anaconda.org/conda-forge/hyperopt) (πŸ“₯ 340K Β· ⏱️ 14.10.2020): ``` conda install -c conda-forge hyperopt ```
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auto-sklearn (πŸ₯‡33 Β· ⭐ 6K Β· πŸ“ˆ) - Automated Machine Learning with scikit-learn. BSD-3 +
auto-sklearn (πŸ₯ˆ33 Β· ⭐ 6K) - Automated Machine Learning with scikit-learn. BSD-3 -- [GitHub](https://github.com/automl/auto-sklearn) (πŸ‘¨β€πŸ’» 77 Β· πŸ”€ 1.1K Β· πŸ“₯ 3 Β· πŸ“¦ 250 Β· πŸ“‹ 830 - 13% open Β· ⏱️ 24.12.2021): +- [GitHub](https://github.com/automl/auto-sklearn) (πŸ‘¨β€πŸ’» 79 Β· πŸ”€ 1.1K Β· πŸ“₯ 14 Β· πŸ“¦ 260 Β· πŸ“‹ 850 - 13% open Β· ⏱️ 25.01.2022): ``` git clone https://github.com/automl/auto-sklearn ``` -- [PyPi](https://pypi.org/project/auto-sklearn) (πŸ“₯ 23K / month Β· πŸ“¦ 30 Β· ⏱️ 11.01.2022): +- [PyPi](https://pypi.org/project/auto-sklearn) (πŸ“₯ 28K / month Β· πŸ“¦ 30 Β· ⏱️ 25.01.2022): ``` pip install auto-sklearn ``` +- [Conda](https://anaconda.org/conda-forge/auto-sklearn) (πŸ“₯ 2.9K Β· ⏱️ 28.01.2022): + ``` + conda install -c conda-forge auto-sklearn + ```
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Keras Tuner (πŸ₯‡33 Β· ⭐ 2.5K) - Hyperparameter tuning for humans. Apache-2 +
Keras Tuner (πŸ₯ˆ33 Β· ⭐ 2.5K) - Hyperparameter tuning for humans. Apache-2 -- [GitHub](https://github.com/keras-team/keras-tuner) (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 320 Β· πŸ“¦ 1.1K Β· πŸ“‹ 360 - 45% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/keras-team/keras-tuner) (πŸ‘¨β€πŸ’» 42 Β· πŸ”€ 320 Β· πŸ“¦ 1.1K Β· πŸ“‹ 360 - 44% open Β· ⏱️ 20.01.2022): ``` git clone https://github.com/keras-team/keras-tuner ``` -- [PyPi](https://pypi.org/project/keras-tuner) (πŸ“₯ 520K / month Β· πŸ“¦ 34 Β· ⏱️ 05.11.2021): +- [PyPi](https://pypi.org/project/keras-tuner) (πŸ“₯ 530K / month Β· πŸ“¦ 34 Β· ⏱️ 05.11.2021): ``` pip install keras-tuner ``` -
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Ax (πŸ₯‡33 Β· ⭐ 1.7K) - Adaptive Experimentation Platform. MIT - -- [GitHub](https://github.com/facebook/Ax) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 180 Β· πŸ“¦ 230 Β· πŸ“‹ 350 - 11% open Β· ⏱️ 12.01.2022): - - ``` - git clone https://github.com/facebook/Ax - ``` -- [PyPi](https://pypi.org/project/ax-platform) (πŸ“₯ 90K / month Β· πŸ“¦ 14 Β· ⏱️ 16.12.2021): +- [Conda](https://anaconda.org/conda-forge/keras-tuner) (πŸ“₯ 4.9K Β· ⏱️ 12.01.2022): ``` - pip install ax-platform + conda install -c conda-forge keras-tuner ```
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AutoKeras (πŸ₯ˆ32 Β· ⭐ 8.3K) - AutoML library for deep learning. Apache-2 +
scikit-optimize (πŸ₯ˆ33 Β· ⭐ 2.3K) - Sequential model-based optimization with a `scipy.optimize`.. BSD-3 -- [GitHub](https://github.com/keras-team/autokeras) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 1.3K Β· πŸ“₯ 2.2K Β· πŸ“¦ 270 Β· πŸ“‹ 790 - 8% open Β· ⏱️ 22.12.2021): +- [GitHub](https://github.com/scikit-optimize/scikit-optimize) (πŸ‘¨β€πŸ’» 75 Β· πŸ”€ 420 Β· πŸ“¦ 2.4K Β· πŸ“‹ 620 - 37% open Β· ⏱️ 12.10.2021): ``` - git clone https://github.com/keras-team/autokeras + git clone https://github.com/scikit-optimize/scikit-optimize ``` -- [PyPi](https://pypi.org/project/autokeras) (πŸ“₯ 40K / month Β· πŸ“¦ 9 Β· ⏱️ 02.11.2021): +- [PyPi](https://pypi.org/project/scikit-optimize) (πŸ“₯ 780K / month Β· πŸ“¦ 170 Β· ⏱️ 12.10.2021): ``` - pip install autokeras + pip install scikit-optimize + ``` +- [Conda](https://anaconda.org/conda-forge/scikit-optimize) (πŸ“₯ 530K Β· ⏱️ 15.12.2021): + ``` + conda install -c conda-forge scikit-optimize ```
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scikit-optimize (πŸ₯ˆ32 Β· ⭐ 2.3K) - Sequential model-based optimization with a `scipy.optimize`.. BSD-3 +
Ax (πŸ₯ˆ33 Β· ⭐ 1.7K) - Adaptive Experimentation Platform. MIT -- [GitHub](https://github.com/scikit-optimize/scikit-optimize) (πŸ‘¨β€πŸ’» 75 Β· πŸ”€ 420 Β· πŸ“¦ 2.3K Β· πŸ“‹ 620 - 37% open Β· ⏱️ 12.10.2021): +- [GitHub](https://github.com/facebook/Ax) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 180 Β· πŸ“¦ 240 Β· πŸ“‹ 360 - 10% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/scikit-optimize/scikit-optimize + git clone https://github.com/facebook/Ax ``` -- [PyPi](https://pypi.org/project/scikit-optimize) (πŸ“₯ 380K / month Β· πŸ“¦ 170 Β· ⏱️ 12.10.2021): +- [PyPi](https://pypi.org/project/ax-platform) (πŸ“₯ 110K / month Β· πŸ“¦ 14 Β· ⏱️ 16.12.2021): ``` - pip install scikit-optimize + pip install ax-platform ``` -- [Conda](https://anaconda.org/conda-forge/scikit-optimize) (πŸ“₯ 520K Β· ⏱️ 15.12.2021): +- [Conda](https://anaconda.org/conda-forge/ax-platform) (πŸ“₯ 690 Β· ⏱️ 22.06.2021): ``` - conda install -c conda-forge scikit-optimize + conda install -c conda-forge ax-platform ```
BoTorch (πŸ₯ˆ32 Β· ⭐ 2.2K) - Bayesian optimization in PyTorch. MIT -- [GitHub](https://github.com/pytorch/botorch) (πŸ‘¨β€πŸ’» 67 Β· πŸ”€ 230 Β· πŸ“¦ 200 Β· πŸ“‹ 240 - 23% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/pytorch/botorch) (πŸ‘¨β€πŸ’» 68 Β· πŸ”€ 240 Β· πŸ“¦ 210 Β· πŸ“‹ 240 - 23% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/pytorch/botorch ``` -- [PyPi](https://pypi.org/project/botorch) (πŸ“₯ 110K / month Β· πŸ“¦ 12 Β· ⏱️ 09.12.2021): +- [PyPi](https://pypi.org/project/botorch) (πŸ“₯ 130K / month Β· πŸ“¦ 12 Β· ⏱️ 09.12.2021): ``` pip install botorch ``` +- [Conda](https://anaconda.org/conda-forge/botorch) (πŸ“₯ 17K Β· ⏱️ 09.12.2021): + ``` + conda install -c conda-forge botorch + ```
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AutoGluon (πŸ₯ˆ30 Β· ⭐ 4K) - AutoGluon: AutoML for Text, Image, and Tabular Data. Apache-2 +
AutoGluon (πŸ₯ˆ29 Β· ⭐ 4.1K) - AutoGluon: AutoML for Image, Text, and Tabular Data. Apache-2 -- [GitHub](https://github.com/awslabs/autogluon) (πŸ‘¨β€πŸ’» 64 Β· πŸ”€ 540 Β· πŸ“¦ 89 Β· πŸ“‹ 600 - 22% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/awslabs/autogluon) (πŸ‘¨β€πŸ’» 65 Β· πŸ”€ 550 Β· πŸ“¦ 97 Β· πŸ“‹ 620 - 21% open Β· ⏱️ 08.02.2022): ``` git clone https://github.com/awslabs/autogluon ``` -- [PyPi](https://pypi.org/project/autogluon) (πŸ“₯ 20K / month Β· πŸ“¦ 4 Β· ⏱️ 13.01.2022): +- [PyPi](https://pypi.org/project/autogluon) (πŸ“₯ 45K / month Β· πŸ“¦ 4 Β· ⏱️ 10.02.2022): ``` pip install autogluon ```
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nevergrad (πŸ₯ˆ30 Β· ⭐ 3.2K) - A Python toolbox for performing gradient-free optimization. MIT +
nevergrad (πŸ₯ˆ29 Β· ⭐ 3.2K) - A Python toolbox for performing gradient-free optimization. MIT -- [GitHub](https://github.com/facebookresearch/nevergrad) (πŸ‘¨β€πŸ’» 46 Β· πŸ”€ 300 Β· πŸ“¦ 270 Β· πŸ“‹ 250 - 38% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/facebookresearch/nevergrad) (πŸ‘¨β€πŸ’» 47 Β· πŸ”€ 300 Β· πŸ“¦ 280 Β· πŸ“‹ 250 - 38% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/facebookresearch/nevergrad ``` -- [PyPi](https://pypi.org/project/nevergrad) (πŸ“₯ 16K / month Β· πŸ“¦ 17 Β· ⏱️ 10.11.2021): +- [PyPi](https://pypi.org/project/nevergrad) (πŸ“₯ 20K / month Β· πŸ“¦ 17 Β· ⏱️ 10.11.2021): ``` pip install nevergrad ``` -- [Conda](https://anaconda.org/conda-forge/nevergrad) (πŸ“₯ 20K Β· ⏱️ 14.06.2021): +- [Conda](https://anaconda.org/conda-forge/nevergrad) (πŸ“₯ 22K Β· ⏱️ 14.06.2021): ``` conda install -c conda-forge nevergrad ```
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Hyperas (πŸ₯ˆ27 Β· ⭐ 2.1K) - Keras + Hyperopt: A very simple wrapper for convenient.. MIT +
mljar-supervised (πŸ₯ˆ27 Β· ⭐ 1.8K) - Python package for AutoML on Tabular Data with Feature.. MIT -- [GitHub](https://github.com/maxpumperla/hyperas) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 300 Β· πŸ“¦ 220 Β· πŸ“‹ 250 - 36% open Β· ⏱️ 19.11.2021): +- [GitHub](https://github.com/mljar/mljar-supervised) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 250 Β· πŸ“¦ 36 Β· πŸ“‹ 460 - 17% open Β· ⏱️ 06.12.2021): ``` - git clone https://github.com/maxpumperla/hyperas + git clone https://github.com/mljar/mljar-supervised ``` -- [PyPi](https://pypi.org/project/hyperas) (πŸ“₯ 13K / month Β· πŸ“¦ 24 Β· ⏱️ 28.02.2019): +- [PyPi](https://pypi.org/project/mljar-supervised) (πŸ“₯ 25K / month Β· ⏱️ 01.10.2021): ``` - pip install hyperas + pip install mljar-supervised + ``` +- [Conda](https://anaconda.org/conda-forge/mljar-supervised) (πŸ“₯ 1K Β· ⏱️ 03.12.2021): + ``` + conda install -c conda-forge mljar-supervised ```
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mljar-supervised (πŸ₯ˆ27 Β· ⭐ 1.7K) - Python package for AutoML on Tabular Data with Feature.. MIT +
SMAC3 (πŸ₯ˆ27 Β· ⭐ 660) - Sequential Model-based Algorithm Configuration. BSD-3 -- [GitHub](https://github.com/mljar/mljar-supervised) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 240 Β· πŸ“¦ 35 Β· πŸ“‹ 450 - 17% open Β· ⏱️ 06.12.2021): +- [GitHub](https://github.com/automl/SMAC3) (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 170 Β· πŸ“‹ 360 - 18% open Β· ⏱️ 05.11.2021): ``` - git clone https://github.com/mljar/mljar-supervised + git clone https://github.com/automl/SMAC3 ``` -- [PyPi](https://pypi.org/project/mljar-supervised) (πŸ“₯ 23K / month Β· ⏱️ 01.10.2021): +- [PyPi](https://pypi.org/project/smac) (πŸ“₯ 23K / month Β· πŸ“¦ 32 Β· ⏱️ 05.11.2021): ``` - pip install mljar-supervised + pip install smac + ``` +- [Conda](https://anaconda.org/conda-forge/smac) (πŸ“₯ 2.2K Β· ⏱️ 21.10.2021): + ``` + conda install -c conda-forge smac ```
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SMAC3 (πŸ₯ˆ26 Β· ⭐ 650) - Sequential Model-based Algorithm Configuration. BSD-3 +
Hyperas (πŸ₯ˆ26 Β· ⭐ 2.1K) - Keras + Hyperopt: A very simple wrapper for convenient.. MIT -- [GitHub](https://github.com/automl/SMAC3) (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 170 Β· πŸ“‹ 360 - 19% open Β· ⏱️ 05.11.2021): +- [GitHub](https://github.com/maxpumperla/hyperas) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 300 Β· πŸ“¦ 220 Β· πŸ“‹ 250 - 36% open Β· ⏱️ 19.11.2021): ``` - git clone https://github.com/automl/SMAC3 + git clone https://github.com/maxpumperla/hyperas ``` -- [PyPi](https://pypi.org/project/smac) (πŸ“₯ 18K / month Β· πŸ“¦ 32 Β· ⏱️ 05.11.2021): +- [PyPi](https://pypi.org/project/hyperas) (πŸ“₯ 12K / month Β· πŸ“¦ 24 Β· ⏱️ 28.02.2019): ``` - pip install smac + pip install hyperas ```
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AdaNet (πŸ₯‰24 Β· ⭐ 3.4K) - Fast and flexible AutoML with learning guarantees. Apache-2 +
Talos (πŸ₯ˆ26 Β· ⭐ 1.5K Β· πŸ“ˆ) - Hyperparameter Optimization for TensorFlow, Keras and PyTorch. MIT -- [GitHub](https://github.com/tensorflow/adanet) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 520 Β· πŸ“¦ 42 Β· πŸ“‹ 110 - 58% open Β· ⏱️ 30.08.2021): +- [GitHub](https://github.com/autonomio/talos) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 250 Β· πŸ“¦ 140 Β· πŸ“‹ 400 - 8% open Β· ⏱️ 28.01.2022): ``` - git clone https://github.com/tensorflow/adanet + git clone https://github.com/autonomio/talos ``` -- [PyPi](https://pypi.org/project/adanet) (πŸ“₯ 840 / month Β· πŸ“¦ 2 Β· ⏱️ 09.07.2020): +- [PyPi](https://pypi.org/project/talos) (πŸ“₯ 1.1K / month Β· πŸ“¦ 6 Β· ⏱️ 28.01.2022): ``` - pip install adanet + pip install talos ```
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Hyperactive (πŸ₯‰23 Β· ⭐ 340) - An optimization and data collection toolbox for convenient and fast.. MIT +
AdaNet (πŸ₯‰25 Β· ⭐ 3.4K) - Fast and flexible AutoML with learning guarantees. Apache-2 -- [GitHub](https://github.com/SimonBlanke/Hyperactive) (πŸ‘¨β€πŸ’» 4 Β· πŸ”€ 32 Β· πŸ“₯ 97 Β· πŸ“¦ 11 Β· πŸ“‹ 41 - 17% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/tensorflow/adanet) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 520 Β· πŸ“¦ 42 Β· πŸ“‹ 110 - 57% open Β· ⏱️ 30.08.2021): ``` - git clone https://github.com/SimonBlanke/Hyperactive + git clone https://github.com/tensorflow/adanet ``` -- [PyPi](https://pypi.org/project/hyperactive) (πŸ“₯ 480 / month Β· πŸ“¦ 3 Β· ⏱️ 05.12.2021): +- [PyPi](https://pypi.org/project/adanet) (πŸ“₯ 1.1K / month Β· πŸ“¦ 2 Β· ⏱️ 09.07.2020): ``` - pip install hyperactive + pip install adanet ```
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Talos (πŸ₯‰22 Β· ⭐ 1.5K Β· πŸ’€) - Hyperparameter Optimization for TensorFlow, Keras and PyTorch. MIT +
Hyperactive (πŸ₯‰23 Β· ⭐ 360) - An optimization and data collection toolbox for convenient and fast.. MIT -- [GitHub](https://github.com/autonomio/talos) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 250 Β· πŸ“¦ 140 Β· πŸ“‹ 390 - 8% open Β· ⏱️ 27.05.2021): +- [GitHub](https://github.com/SimonBlanke/Hyperactive) (πŸ‘¨β€πŸ’» 4 Β· πŸ”€ 32 Β· πŸ“₯ 98 Β· πŸ“¦ 11 Β· πŸ“‹ 43 - 16% open Β· ⏱️ 18.01.2022): ``` - git clone https://github.com/autonomio/talos + git clone https://github.com/SimonBlanke/Hyperactive ``` -- [PyPi](https://pypi.org/project/talos) (πŸ“₯ 780 / month Β· πŸ“¦ 6 Β· ⏱️ 09.11.2020): +- [PyPi](https://pypi.org/project/hyperactive) (πŸ“₯ 530 / month Β· πŸ“¦ 3 Β· ⏱️ 05.12.2021): ``` - pip install talos + pip install hyperactive ```
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Neuraxle (πŸ₯‰22 Β· ⭐ 490) - A Sklearn-like Framework for Hyperparameter Tuning and AutoML in.. Apache-2 +
Neuraxle (πŸ₯‰22 Β· ⭐ 500) - A Sklearn-like Framework for Hyperparameter Tuning and AutoML in.. Apache-2 -- [GitHub](https://github.com/Neuraxio/Neuraxle) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 52 Β· πŸ“¦ 24 Β· πŸ“‹ 340 - 41% open Β· ⏱️ 01.11.2021): +- [GitHub](https://github.com/Neuraxio/Neuraxle) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 53 Β· πŸ“¦ 26 Β· πŸ“‹ 350 - 41% open Β· ⏱️ 01.11.2021): ``` git clone https://github.com/Neuraxio/Neuraxle ``` -- [PyPi](https://pypi.org/project/neuraxle) (πŸ“₯ 220 / month Β· πŸ“¦ 1 Β· ⏱️ 17.10.2021): +- [PyPi](https://pypi.org/project/neuraxle) (πŸ“₯ 320 / month Β· πŸ“¦ 1 Β· ⏱️ 17.10.2021): ``` pip install neuraxle ```
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Auto ViML (πŸ₯‰20 Β· ⭐ 320) - Automatically Build Multiple ML Models with a Single Line of Code... Apache-2 +
Auto ViML (πŸ₯‰20 Β· ⭐ 330) - Automatically Build Multiple ML Models with a Single Line of Code... Apache-2 - [GitHub](https://github.com/AutoViML/Auto_ViML) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 70 Β· πŸ“¦ 15 Β· πŸ“‹ 18 - 22% open Β· ⏱️ 06.12.2021): ``` git clone https://github.com/AutoViML/Auto_ViML ``` -- [PyPi](https://pypi.org/project/autoviml) (πŸ“₯ 1.5K / month Β· πŸ“¦ 2 Β· ⏱️ 06.12.2021): +- [PyPi](https://pypi.org/project/autoviml) (πŸ“₯ 1.1K / month Β· πŸ“¦ 2 Β· ⏱️ 06.12.2021): ``` pip install autoviml ```
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sklearn-deap (πŸ₯‰19 Β· ⭐ 670) - Use evolutionary algorithms instead of gridsearch in scikit-.. MIT - -- [GitHub](https://github.com/rsteca/sklearn-deap) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 110 Β· πŸ“¦ 31 Β· πŸ“‹ 55 - 38% open Β· ⏱️ 30.07.2021): - - ``` - git clone https://github.com/rsteca/sklearn-deap - ``` -- [PyPi](https://pypi.org/project/sklearn-deap) (πŸ“₯ 730 / month Β· πŸ“¦ 2 Β· ⏱️ 30.07.2021): - ``` - pip install sklearn-deap - ``` -
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AlphaPy (πŸ₯‰18 Β· ⭐ 690) - Automated Machine Learning [AutoML] with Python, scikit-learn, Keras,.. Apache-2 +
AlphaPy (πŸ₯‰19 Β· ⭐ 710) - Automated Machine Learning [AutoML] with Python, scikit-learn, Keras,.. Apache-2 - [GitHub](https://github.com/ScottfreeLLC/AlphaPy) (πŸ‘¨β€πŸ’» 3 Β· πŸ”€ 150 Β· πŸ“¦ 3 Β· πŸ“‹ 41 - 29% open Β· ⏱️ 23.10.2021): ``` git clone https://github.com/ScottfreeLLC/AlphaPy ``` -- [PyPi](https://pypi.org/project/alphapy) (πŸ“₯ 120 / month Β· ⏱️ 29.08.2020): +- [PyPi](https://pypi.org/project/alphapy) (πŸ“₯ 87 / month Β· ⏱️ 29.08.2020): ``` pip install alphapy ```
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HyperparameterHunter (πŸ₯‰16 Β· ⭐ 680 Β· πŸ’€) - Easy hyperparameter optimization and automatic result.. MIT +
sklearn-deap (πŸ₯‰19 Β· ⭐ 680 Β· πŸ’€) - Use evolutionary algorithms instead of gridsearch in.. MIT -- [GitHub](https://github.com/HunterMcGushion/hyperparameter_hunter) (πŸ‘¨β€πŸ’» 4 Β· πŸ”€ 87 Β· πŸ“₯ 330 Β· πŸ“‹ 120 - 30% open Β· ⏱️ 20.01.2021): +- [GitHub](https://github.com/rsteca/sklearn-deap) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 110 Β· πŸ“¦ 31 Β· πŸ“‹ 55 - 38% open Β· ⏱️ 30.07.2021): ``` - git clone https://github.com/HunterMcGushion/hyperparameter_hunter + git clone https://github.com/rsteca/sklearn-deap ``` -- [PyPi](https://pypi.org/project/hyperparameter-hunter) (πŸ“₯ 91 / month Β· πŸ“¦ 2 Β· ⏱️ 06.08.2019): +- [PyPi](https://pypi.org/project/sklearn-deap) (πŸ“₯ 730 / month Β· πŸ“¦ 2 Β· ⏱️ 30.07.2021): ``` - pip install hyperparameter-hunter + pip install sklearn-deap ```
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model_search (πŸ₯‰11 Β· ⭐ 3.2K Β· πŸ’€) - AutoML algorithms for model architecture search at scale. Apache-2 +
model_search (πŸ₯‰11 Β· ⭐ 3.2K) - AutoML algorithms for model architecture search at scale. Apache-2 -- [GitHub](https://github.com/google/model_search) (πŸ‘¨β€πŸ’» 1 Β· πŸ”€ 310 Β· πŸ“‹ 50 - 70% open Β· ⏱️ 17.03.2021): +- [GitHub](https://github.com/google/model_search) (πŸ‘¨β€πŸ’» 1 Β· πŸ”€ 310 Β· πŸ“‹ 50 - 70% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/google/model_search ```
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Show 23 hidden projects... +
Show 24 hidden projects... +- TPOT (πŸ₯ˆ32 Β· ⭐ 8.4K Β· πŸ’€) - A Python Automated Machine Learning tool that optimizes.. ❗️LGPL-3.0 - Bayesian Optimization (πŸ₯ˆ32 Β· ⭐ 5.7K Β· πŸ’€) - A Python implementation of global optimization with.. MIT -- TPOT (πŸ₯ˆ31 Β· ⭐ 8.4K Β· πŸ’€) - A Python Automated Machine Learning tool that optimizes.. ❗️LGPL-3.0 +- Orion (πŸ₯ˆ27 Β· ⭐ 220) - Asynchronous Distributed Hyperparameter Optimization. BSD-3 - GPyOpt (πŸ₯ˆ26 Β· ⭐ 790 Β· πŸ’€) - Gaussian Process Optimization using GPy. BSD-3 -- Orion (πŸ₯ˆ26 Β· ⭐ 220) - Asynchronous Distributed Hyperparameter Optimization. BSD-3 - auto_ml (πŸ₯‰23 Β· ⭐ 1.6K Β· πŸ’€) - [UNMAINTAINED] Automated machine learning for analytics & production. MIT -- MLBox (πŸ₯‰22 Β· ⭐ 1.3K Β· πŸ’€) - MLBox is a powerful Automated Machine Learning python library. ❗️BSD-1-Clause -- HpBandSter (πŸ₯‰22 Β· ⭐ 510 Β· πŸ’€) - a distributed Hyperband implementation on Steroids. BSD-3 +- MLBox (πŸ₯‰23 Β· ⭐ 1.3K Β· πŸ’€) - MLBox is a powerful Automated Machine Learning python library. ❗️BSD-1-Clause +- HpBandSter (πŸ₯‰22 Β· ⭐ 520 Β· πŸ’€) - a distributed Hyperband implementation on Steroids. BSD-3 - optunity (πŸ₯‰22 Β· ⭐ 380 Β· πŸ’€) - optimization routines for hyperparameter tuning. BSD-3 -- lazypredict (πŸ₯‰22 Β· ⭐ 280) - Lazy Predict help build a lot of basic models without much code.. MIT +- lazypredict (πŸ₯‰22 Β· ⭐ 290) - Lazy Predict help build a lot of basic models without much code.. MIT - Test Tube (πŸ₯‰20 Β· ⭐ 710 Β· πŸ’€) - Python library to easily log experiments and parallelize.. MIT - Dragonfly (πŸ₯‰19 Β· ⭐ 620 Β· πŸ’€) - An open source python library for scalable Bayesian optimisation. MIT +- Auto Tune Models (πŸ₯‰18 Β· ⭐ 510 Β· πŸ’€) - Auto Tune Models - A multi-tenant, multi-data system for.. MIT - Sherpa (πŸ₯‰18 Β· ⭐ 310 Β· πŸ’€) - Hyperparameter optimization that enables researchers to.. ❗️GPL-3.0 +- featurewiz (πŸ₯‰18 Β· ⭐ 150) - Use advanced feature engineering strategies and select best.. Apache-2 - Advisor (πŸ₯‰17 Β· ⭐ 1.4K Β· πŸ’€) - Open-source implementation of Google Vizier for hyper parameters.. Apache-2 -- Auto Tune Models (πŸ₯‰17 Β· ⭐ 510 Β· πŸ’€) - Auto Tune Models - A multi-tenant, multi-data system for.. MIT -- featurewiz (πŸ₯‰17 Β· ⭐ 120) - Use advanced feature engineering strategies and select best.. Apache-2 -- automl-gs (πŸ₯‰16 Β· ⭐ 1.8K Β· πŸ’€) - Provide an input CSV and a target field to predict, generate a.. MIT - Xcessiv (πŸ₯‰16 Β· ⭐ 1.3K Β· πŸ’€) - A web-based application for quick, scalable, and automated.. Apache-2 +- HyperparameterHunter (πŸ₯‰16 Β· ⭐ 680 Β· πŸ’€) - Easy hyperparameter optimization and automatic result.. MIT +- automl-gs (πŸ₯‰15 Β· ⭐ 1.8K Β· πŸ’€) - Provide an input CSV and a target field to predict, generate a.. MIT - Parfit (πŸ₯‰15 Β· ⭐ 200 Β· πŸ’€) - A package for parallelizing the fit and flexibly scoring of.. MIT - ENAS (πŸ₯‰13 Β· ⭐ 2.5K Β· πŸ’€) - PyTorch implementation of Efficient Neural Architecture Search via.. Apache-2 - Auptimizer (πŸ₯‰13 Β· ⭐ 180 Β· πŸ’€) - An automatic ML model optimization tool. ❗️GPL-3.0 -- Hypermax (πŸ₯‰12 Β· ⭐ 99 Β· πŸ’€) - Better, faster hyper-parameter optimization. BSD-3 +- Hypermax (πŸ₯‰12 Β· ⭐ 100 Β· πŸ’€) - Better, faster hyper-parameter optimization. BSD-3 - Devol (πŸ₯‰11 Β· ⭐ 940 Β· πŸ’€) - Genetic neural architecture search with Keras. MIT - Hypertunity (πŸ₯‰9 Β· ⭐ 120 Β· πŸ’€) - A toolset for black-box hyperparameter optimisation. Apache-2
@@ -5855,158 +6326,178 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst
OpenAI Gym (πŸ₯‡42 Β· ⭐ 26K) - A toolkit for developing and comparing reinforcement learning.. MIT -- [GitHub](https://github.com/openai/gym) (πŸ‘¨β€πŸ’» 330 Β· πŸ”€ 7.3K Β· πŸ“¦ 26K Β· πŸ“‹ 1.5K - 7% open Β· ⏱️ 11.01.2022): +- [GitHub](https://github.com/openai/gym) (πŸ‘¨β€πŸ’» 340 Β· πŸ”€ 7.3K Β· πŸ“¦ 26K Β· πŸ“‹ 1.5K - 7% open Β· ⏱️ 08.02.2022): ``` git clone https://github.com/openai/gym ``` -- [PyPi](https://pypi.org/project/gym) (πŸ“₯ 970K / month Β· πŸ“¦ 2.3K Β· ⏱️ 06.10.2021): +- [PyPi](https://pypi.org/project/gym) (πŸ“₯ 570K / month Β· πŸ“¦ 2.3K Β· ⏱️ 06.10.2021): ``` pip install gym ``` +- [Conda](https://anaconda.org/conda-forge/gym) (πŸ“₯ 89K Β· ⏱️ 08.02.2022): + ``` + conda install -c conda-forge gym + ```
TF-Agents (πŸ₯‡33 Β· ⭐ 2.2K) - TF-Agents: A reliable, scalable and easy to use TensorFlow.. Apache-2 -- [GitHub](https://github.com/tensorflow/agents) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 590 Β· πŸ“¦ 670 Β· πŸ“‹ 520 - 20% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/tensorflow/agents) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 600 Β· πŸ“¦ 700 Β· πŸ“‹ 530 - 20% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/tensorflow/agents ``` -- [PyPi](https://pypi.org/project/tf-agents) (πŸ“₯ 70K / month Β· πŸ“¦ 14 Β· ⏱️ 15.11.2021): +- [PyPi](https://pypi.org/project/tf-agents) (πŸ“₯ 140K / month Β· πŸ“¦ 14 Β· ⏱️ 20.01.2022): ``` pip install tf-agents ```
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Dopamine (πŸ₯‡31 Β· ⭐ 9.7K) - Dopamine is a research framework for fast prototyping of.. Apache-2 +
Dopamine (πŸ₯‡30 Β· ⭐ 9.7K) - Dopamine is a research framework for fast prototyping of.. Apache-2 - [GitHub](https://github.com/google/dopamine) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 1.3K Β· πŸ“‹ 160 - 49% open Β· ⏱️ 14.12.2021): ``` git clone https://github.com/google/dopamine ``` -- [PyPi](https://pypi.org/project/dopamine-rl) (πŸ“₯ 1.2M / month Β· πŸ“¦ 37 Β· ⏱️ 13.12.2021): +- [PyPi](https://pypi.org/project/dopamine-rl) (πŸ“₯ 600K / month Β· πŸ“¦ 37 Β· ⏱️ 13.12.2021): ``` pip install dopamine-rl ```
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TensorForce (πŸ₯ˆ29 Β· ⭐ 3.1K) - Tensorforce: a TensorFlow library for applied.. Apache-2 +
FinRL (πŸ₯ˆ29 Β· ⭐ 3.3K) - FinRL: Financial Reinforcement Learning Framework. Please star. MIT -- [GitHub](https://github.com/tensorforce/tensorforce) (πŸ‘¨β€πŸ’» 82 Β· πŸ”€ 510 Β· πŸ“‹ 630 - 1% open Β· ⏱️ 08.01.2022): +- [GitHub](https://github.com/AI4Finance-Foundation/FinRL) (πŸ‘¨β€πŸ’» 52 Β· πŸ”€ 900 Β· πŸ“¦ 10 Β· πŸ“‹ 330 - 24% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/tensorforce/tensorforce + git clone https://github.com/AI4Finance-Foundation/FinRL ``` -- [PyPi](https://pypi.org/project/tensorforce) (πŸ“₯ 1.4K / month Β· πŸ“¦ 26 Β· ⏱️ 07.09.2019): +- [PyPi](https://pypi.org/project/finrl) (πŸ“₯ 400 / month Β· ⏱️ 08.01.2022): ``` - pip install tensorforce + pip install finrl ```
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FinRL (πŸ₯ˆ28 Β· ⭐ 3.2K) - FinRL: Financial Reinforcement Learning Framework. Please star. MIT +
TensorLayer (πŸ₯ˆ28 Β· ⭐ 6.8K) - Deep Learning and Reinforcement Learning Library for.. Apache-2 -- [GitHub](https://github.com/AI4Finance-Foundation/FinRL) (πŸ‘¨β€πŸ’» 50 Β· πŸ”€ 860 Β· πŸ“¦ 8 Β· πŸ“‹ 280 - 29% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/tensorlayer/TensorLayer) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 1.5K Β· πŸ“₯ 1.4K Β· πŸ“‹ 460 - 4% open Β· ⏱️ 29.10.2021): ``` - git clone https://github.com/AI4Finance-LLC/FinRL + git clone https://github.com/tensorlayer/tensorlayer ``` -- [PyPi](https://pypi.org/project/finrl) (πŸ“₯ 360 / month Β· ⏱️ 08.01.2022): +- [PyPi](https://pypi.org/project/tensorlayer) (πŸ“₯ 2.5K / month Β· πŸ“¦ 39 Β· ⏱️ 19.06.2020): ``` - pip install finrl + pip install tensorlayer ```
Acme (πŸ₯ˆ28 Β· ⭐ 2.5K) - A library of reinforcement learning components and agents. Apache-2 -- [GitHub](https://github.com/deepmind/acme) (πŸ‘¨β€πŸ’» 54 Β· πŸ”€ 290 Β· πŸ“¦ 49 Β· πŸ“‹ 160 - 25% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/deepmind/acme) (πŸ‘¨β€πŸ’» 58 Β· πŸ”€ 300 Β· πŸ“¦ 56 Β· πŸ“‹ 160 - 25% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/deepmind/acme ``` -- [PyPi](https://pypi.org/project/dm-acme) (πŸ“₯ 2.6K / month Β· πŸ“¦ 2 Β· ⏱️ 08.01.2022): +- [PyPi](https://pypi.org/project/dm-acme) (πŸ“₯ 3.9K / month Β· πŸ“¦ 2 Β· ⏱️ 10.02.2022): ``` pip install dm-acme ``` +- [Conda](https://anaconda.org/conda-forge/dm-acme) (πŸ“₯ 1.8K Β· ⏱️ 09.12.2021): + ``` + conda install -c conda-forge dm-acme + ```
ViZDoom (πŸ₯ˆ28 Β· ⭐ 1.3K) - Doom-based AI Research Platform for Reinforcement Learning from Raw.. MIT -- [GitHub](https://github.com/mwydmuch/ViZDoom) (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 310 Β· πŸ“₯ 11K Β· πŸ“¦ 120 Β· πŸ“‹ 430 - 20% open Β· ⏱️ 10.01.2022): +- [GitHub](https://github.com/mwydmuch/ViZDoom) (πŸ‘¨β€πŸ’» 46 Β· πŸ”€ 310 Β· πŸ“₯ 11K Β· πŸ“¦ 120 Β· πŸ“‹ 430 - 20% open Β· ⏱️ 20.01.2022): ``` git clone https://github.com/mwydmuch/ViZDoom ``` -- [PyPi](https://pypi.org/project/vizdoom) (πŸ“₯ 930 / month Β· πŸ“¦ 14 Β· ⏱️ 22.11.2021): +- [PyPi](https://pypi.org/project/vizdoom) (πŸ“₯ 900 / month Β· πŸ“¦ 14 Β· ⏱️ 22.11.2021): ``` pip install vizdoom ```
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TensorLayer (πŸ₯‰27 Β· ⭐ 6.8K) - Deep Learning and Reinforcement Learning Library for.. Apache-2 +
TensorForce (πŸ₯‰27 Β· ⭐ 3.1K Β· πŸ“‰) - Tensorforce: a TensorFlow library for applied.. Apache-2 -- [GitHub](https://github.com/tensorlayer/TensorLayer) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 1.5K Β· πŸ“₯ 1.3K Β· πŸ“‹ 460 - 4% open Β· ⏱️ 29.10.2021): +- [GitHub](https://github.com/tensorforce/tensorforce) (πŸ‘¨β€πŸ’» 82 Β· πŸ”€ 510 Β· πŸ“‹ 630 - 1% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/tensorlayer/tensorlayer + git clone https://github.com/tensorforce/tensorforce ``` -- [PyPi](https://pypi.org/project/tensorlayer) (πŸ“₯ 2.3K / month Β· πŸ“¦ 39 Β· ⏱️ 19.06.2020): +- [PyPi](https://pypi.org/project/tensorforce) (πŸ“₯ 1.9K / month Β· πŸ“¦ 26 Β· ⏱️ 07.09.2019): ``` - pip install tensorlayer + pip install tensorforce ```
PARL (πŸ₯‰27 Β· ⭐ 2.4K) - A high-performance distributed training framework for Reinforcement.. Apache-2 -- [GitHub](https://github.com/PaddlePaddle/PARL) (πŸ‘¨β€πŸ’» 28 Β· πŸ”€ 600 Β· πŸ“¦ 86 Β· πŸ“‹ 310 - 23% open Β· ⏱️ 07.01.2022): +- [GitHub](https://github.com/PaddlePaddle/PARL) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 620 Β· πŸ“¦ 86 Β· πŸ“‹ 310 - 23% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/PaddlePaddle/PARL ``` -- [PyPi](https://pypi.org/project/parl) (πŸ“₯ 760 / month Β· ⏱️ 30.12.2021): +- [PyPi](https://pypi.org/project/parl) (πŸ“₯ 530 / month Β· ⏱️ 30.12.2021): ``` pip install parl ```
Stable Baselines (πŸ₯‰25 Β· ⭐ 3.4K) - A fork of OpenAI Baselines, implementations of reinforcement.. MIT -- [GitHub](https://github.com/hill-a/stable-baselines) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 660 Β· πŸ“‹ 930 - 13% open Β· ⏱️ 25.08.2021): +- [GitHub](https://github.com/hill-a/stable-baselines) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 670 Β· πŸ“‹ 930 - 13% open Β· ⏱️ 25.08.2021): ``` git clone https://github.com/hill-a/stable-baselines ``` -- [PyPi](https://pypi.org/project/stable-baselines) (πŸ“₯ 9.1K / month Β· πŸ“¦ 34 Β· ⏱️ 06.04.2021): +- [PyPi](https://pypi.org/project/stable-baselines) (πŸ“₯ 8.5K / month Β· πŸ“¦ 34 Β· ⏱️ 06.04.2021): ``` pip install stable-baselines ```
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garage (πŸ₯‰24 Β· ⭐ 1.4K) - A toolkit for reproducible reinforcement learning research. MIT +
garage (πŸ₯‰25 Β· ⭐ 1.4K) - A toolkit for reproducible reinforcement learning research. MIT -- [GitHub](https://github.com/rlworkgroup/garage) (πŸ‘¨β€πŸ’» 78 Β· πŸ”€ 240 Β· πŸ“¦ 26 Β· πŸ“‹ 1K - 20% open Β· ⏱️ 20.10.2021): +- [GitHub](https://github.com/rlworkgroup/garage) (πŸ‘¨β€πŸ’» 78 Β· πŸ”€ 240 Β· πŸ“¦ 29 Β· πŸ“‹ 1K - 20% open Β· ⏱️ 20.10.2021): ``` git clone https://github.com/rlworkgroup/garage ``` -- [PyPi](https://pypi.org/project/garage) (πŸ“₯ 740 / month Β· πŸ“¦ 2 Β· ⏱️ 23.03.2021): +- [PyPi](https://pypi.org/project/garage) (πŸ“₯ 460 / month Β· πŸ“¦ 2 Β· ⏱️ 23.03.2021): ``` pip install garage ```
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TRFL (πŸ₯‰23 Β· ⭐ 3.1K) - TensorFlow Reinforcement Learning. Apache-2 +
ChainerRL (πŸ₯‰23 Β· ⭐ 1K Β· πŸ’€) - ChainerRL is a deep reinforcement learning library built on top of.. MIT -- [GitHub](https://github.com/deepmind/trfl) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 370 Β· πŸ“¦ 69 Β· πŸ“‹ 22 - 27% open Β· ⏱️ 16.08.2021): +- [GitHub](https://github.com/chainer/chainerrl) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 210 Β· πŸ“¦ 110 Β· πŸ“‹ 220 - 33% open Β· ⏱️ 17.04.2021): ``` - git clone https://github.com/deepmind/trfl + git clone https://github.com/chainer/chainerrl ``` -- [PyPi](https://pypi.org/project/trfl) (πŸ“₯ 2.7K / month Β· πŸ“¦ 3 Β· ⏱️ 16.08.2021): +- [PyPi](https://pypi.org/project/chainerrl) (πŸ“₯ 530 / month Β· πŸ“¦ 8 Β· ⏱️ 14.02.2020): ``` - pip install trfl + pip install chainerrl ```
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ChainerRL (πŸ₯‰23 Β· ⭐ 1K Β· πŸ’€) - ChainerRL is a deep reinforcement learning library built on top of.. MIT +
ReAgent (πŸ₯‰22 Β· ⭐ 3.1K) - A platform for Reasoning systems (Reinforcement Learning,.. BSD-3 -- [GitHub](https://github.com/chainer/chainerrl) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 210 Β· πŸ“¦ 110 Β· πŸ“‹ 220 - 33% open Β· ⏱️ 17.04.2021): +- [GitHub](https://github.com/facebookresearch/ReAgent) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 430 Β· πŸ“‹ 120 - 35% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/chainer/chainerrl + git clone https://github.com/facebookresearch/ReAgent ``` -- [PyPi](https://pypi.org/project/chainerrl) (πŸ“₯ 450 / month Β· πŸ“¦ 8 Β· ⏱️ 14.02.2020): +- [PyPi](https://pypi.org/project/reagent) (πŸ“₯ 17 / month Β· ⏱️ 27.05.2020): ``` - pip install chainerrl + pip install reagent + ``` +
+
TRFL (πŸ₯‰22 Β· ⭐ 3.1K) - TensorFlow Reinforcement Learning. Apache-2 + +- [GitHub](https://github.com/deepmind/trfl) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 370 Β· πŸ“¦ 71 Β· πŸ“‹ 22 - 27% open Β· ⏱️ 16.08.2021): + + ``` + git clone https://github.com/deepmind/trfl + ``` +- [PyPi](https://pypi.org/project/trfl) (πŸ“₯ 4.2K / month Β· πŸ“¦ 3 Β· ⏱️ 16.08.2021): + ``` + pip install trfl ```
Coach (πŸ₯‰22 Β· ⭐ 2.1K Β· πŸ’€) - Reinforcement Learning Coach by Intel AI Lab enables easy.. Apache-2 @@ -6021,43 +6512,48 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install rl_coach ```
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RLax (πŸ₯‰21 Β· ⭐ 730) - A library of reinforcement learning building blocks in JAX. Apache-2 jax +
RLax (πŸ₯‰21 Β· ⭐ 740) - A library of reinforcement learning building blocks in JAX. Apache-2 -- [GitHub](https://github.com/deepmind/rlax) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 56 Β· πŸ“¦ 32 Β· πŸ“‹ 18 - 50% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/deepmind/rlax) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 57 Β· πŸ“¦ 37 Β· πŸ“‹ 18 - 50% open Β· ⏱️ 04.02.2022): ``` git clone https://github.com/deepmind/rlax ``` -- [PyPi](https://pypi.org/project/rlax) (πŸ“₯ 1.9K / month Β· ⏱️ 19.11.2021): +- [PyPi](https://pypi.org/project/rlax) (πŸ“₯ 3K / month Β· ⏱️ 19.11.2021): ``` pip install rlax ```
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ReAgent (πŸ₯‰20 Β· ⭐ 3.1K) - A platform for Reasoning systems (Reinforcement Learning,.. BSD-3 +
PFRL (πŸ₯‰20 Β· ⭐ 780) - PFRL: a PyTorch-based deep reinforcement learning library. MIT -- [GitHub](https://github.com/facebookresearch/ReAgent) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 430 Β· πŸ“‹ 120 - 35% open Β· ⏱️ 29.12.2021): +- [GitHub](https://github.com/pfnet/pfrl) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 110 Β· πŸ“¦ 30 Β· πŸ“‹ 60 - 45% open Β· ⏱️ 06.12.2021): ``` - git clone https://github.com/facebookresearch/ReAgent + git clone https://github.com/pfnet/pfrl + ``` +- [PyPi](https://pypi.org/project/pfrl) (πŸ“₯ 5.3K / month Β· πŸ“¦ 1 Β· ⏱️ 07.07.2021): + ``` + pip install pfrl ```
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PFRL (πŸ₯‰20 Β· ⭐ 770) - PFRL: a PyTorch-based deep reinforcement learning library. MIT +
rliable (πŸ₯‰11 Β· ⭐ 310 Β· 🐣) - Library for reliable evaluation on RL and ML benchmarks, as.. Apache-2 -- [GitHub](https://github.com/pfnet/pfrl) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 100 Β· πŸ“¦ 30 Β· πŸ“‹ 60 - 45% open Β· ⏱️ 06.12.2021): +- [GitHub](https://github.com/google-research/rliable) (πŸ‘¨β€πŸ’» 2 Β· πŸ”€ 17 Β· πŸ“¦ 6 Β· ⏱️ 06.02.2022): ``` - git clone https://github.com/pfnet/pfrl + git clone https://github.com/google-research/rliable ``` -- [PyPi](https://pypi.org/project/pfrl) (πŸ“₯ 4.4K / month Β· πŸ“¦ 1 Β· ⏱️ 07.07.2021): +- [PyPi](https://pypi.org/project/rliable`): ``` - pip install pfrl + pip install rliable` ```
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Show 4 hidden projects... +
Show 5 hidden projects... -- baselines (πŸ₯ˆ30 Β· ⭐ 12K Β· πŸ’€) - OpenAI Baselines: high-quality implementations of reinforcement.. MIT +- baselines (πŸ₯‡30 Β· ⭐ 12K Β· πŸ’€) - OpenAI Baselines: high-quality implementations of reinforcement.. MIT - keras-rl (πŸ₯ˆ29 Β· ⭐ 5.2K Β· πŸ’€) - Deep Reinforcement Learning for Keras. MIT - DeepMind Lab (πŸ₯‰19 Β· ⭐ 6.6K) - A customisable 3D platform for agent-based AI research. ❗️GPL-2.0 +- SerpentAI (πŸ₯‰19 Β· ⭐ 6.2K Β· πŸ’€) - Game Agent Framework. Helping you create AIs / Bots that learn to.. MIT - Maze (πŸ₯‰16 Β· ⭐ 200) - Maze Applied Reinforcement Learning Framework. ❗️Custom

@@ -6068,50 +6564,42 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst _Libraries for building and evaluating recommendation systems._ -
implicit (πŸ₯‡31 Β· ⭐ 2.6K) - Fast Python Collaborative Filtering for Implicit Feedback Datasets. MIT +
Recommenders (πŸ₯‡32 Β· ⭐ 12K Β· πŸ“ˆ) - Best Practices on Recommendation Systems. MIT -- [GitHub](https://github.com/benfred/implicit) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 510 Β· πŸ“¦ 530 Β· πŸ“‹ 390 - 22% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/microsoft/recommenders) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 2.1K Β· πŸ“₯ 120 Β· πŸ“¦ 11 Β· πŸ“‹ 650 - 18% open Β· ⏱️ 13.01.2022): ``` - git clone https://github.com/benfred/implicit - ``` -- [PyPi](https://pypi.org/project/implicit) (πŸ“₯ 110K / month Β· πŸ“¦ 29 Β· ⏱️ 29.08.2021): - ``` - pip install implicit + git clone https://github.com/microsoft/recommenders ``` -- [Conda](https://anaconda.org/conda-forge/implicit) (πŸ“₯ 330K Β· ⏱️ 29.08.2021): +- [PyPi](https://pypi.org/project/recommenders) (πŸ“₯ 4.6K / month Β· πŸ“¦ 2 Β· ⏱️ 14.03.2021): ``` - conda install -c conda-forge implicit + pip install recommenders ```
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TF Recommenders (πŸ₯‡29 Β· ⭐ 1.2K) - TensorFlow Recommenders is a library for building.. Apache-2 +
implicit (πŸ₯‡32 Β· ⭐ 2.6K) - Fast Python Collaborative Filtering for Implicit Feedback Datasets. MIT -- [GitHub](https://github.com/tensorflow/recommenders) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 160 Β· πŸ“¦ 64 Β· πŸ“‹ 220 - 52% open Β· ⏱️ 07.01.2022): +- [GitHub](https://github.com/benfred/implicit) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 530 Β· πŸ“¦ 540 Β· πŸ“‹ 380 - 16% open Β· ⏱️ 29.01.2022): ``` - git clone https://github.com/tensorflow/recommenders + git clone https://github.com/benfred/implicit ``` -- [PyPi](https://pypi.org/project/tensorflow-recommenders) (πŸ“₯ 200K / month Β· πŸ“¦ 1 Β· ⏱️ 23.08.2021): +- [PyPi](https://pypi.org/project/implicit) (πŸ“₯ 160K / month Β· πŸ“¦ 31 Β· ⏱️ 29.01.2022): ``` - pip install tensorflow-recommenders + pip install implicit ``` -
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Recommenders (πŸ₯ˆ28 Β· ⭐ 12K) - Best Practices on Recommendation Systems. MIT - -- [GitHub](https://github.com/microsoft/recommenders) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 2.1K Β· πŸ“₯ 93 Β· πŸ“¦ 9 Β· πŸ“‹ 650 - 20% open Β· ⏱️ 13.01.2022): - +- [Conda](https://anaconda.org/conda-forge/implicit) (πŸ“₯ 330K Β· ⏱️ 29.01.2022): ``` - git clone https://github.com/microsoft/recommenders + conda install -c conda-forge implicit ```
lightfm (πŸ₯ˆ28 Β· ⭐ 3.9K) - A Python implementation of LightFM, a hybrid recommendation algorithm. Apache-2 -- [GitHub](https://github.com/lyst/lightfm) (πŸ‘¨β€πŸ’» 44 Β· πŸ”€ 610 Β· πŸ“¦ 620 Β· πŸ“‹ 440 - 20% open Β· ⏱️ 31.12.2021): +- [GitHub](https://github.com/lyst/lightfm) (πŸ‘¨β€πŸ’» 44 Β· πŸ”€ 610 Β· πŸ“¦ 640 Β· πŸ“‹ 440 - 20% open Β· ⏱️ 31.12.2021): ``` git clone https://github.com/lyst/lightfm ``` -- [PyPi](https://pypi.org/project/lightfm) (πŸ“₯ 190K / month Β· πŸ“¦ 45 Β· ⏱️ 27.11.2020): +- [PyPi](https://pypi.org/project/lightfm) (πŸ“₯ 300K / month Β· πŸ“¦ 45 Β· ⏱️ 27.11.2020): ``` pip install lightfm ``` @@ -6120,42 +6608,54 @@ _Libraries for building and evaluating recommendation systems._ conda install -c conda-forge lightfm ```
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TF Ranking (πŸ₯ˆ28 Β· ⭐ 2.4K) - Learning to Rank in TensorFlow. Apache-2 +
TF Recommenders (πŸ₯ˆ28 Β· ⭐ 1.2K) - TensorFlow Recommenders is a library for building.. Apache-2 + +- [GitHub](https://github.com/tensorflow/recommenders) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 160 Β· πŸ“¦ 71 Β· πŸ“‹ 230 - 54% open Β· ⏱️ 28.01.2022): + + ``` + git clone https://github.com/tensorflow/recommenders + ``` +- [PyPi](https://pypi.org/project/tensorflow-recommenders) (πŸ“₯ 270K / month Β· πŸ“¦ 1 Β· ⏱️ 23.08.2021): + ``` + pip install tensorflow-recommenders + ``` +
+
TF Ranking (πŸ₯ˆ27 Β· ⭐ 2.4K) - Learning to Rank in TensorFlow. Apache-2 -- [GitHub](https://github.com/tensorflow/ranking) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 410 Β· πŸ“‹ 280 - 16% open Β· ⏱️ 22.11.2021): +- [GitHub](https://github.com/tensorflow/ranking) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 410 Β· πŸ“‹ 280 - 17% open Β· ⏱️ 22.11.2021): ``` git clone https://github.com/tensorflow/ranking ``` -- [PyPi](https://pypi.org/project/tensorflow_ranking) (πŸ“₯ 48K / month Β· πŸ“¦ 11 Β· ⏱️ 16.11.2021): +- [PyPi](https://pypi.org/project/tensorflow_ranking) (πŸ“₯ 45K / month Β· πŸ“¦ 11 Β· ⏱️ 16.11.2021): ``` pip install tensorflow_ranking ```
RecBole (πŸ₯‰25 Β· ⭐ 1.6K) - A unified, comprehensive and efficient recommendation library. MIT -- [GitHub](https://github.com/RUCAIBox/RecBole) (πŸ‘¨β€πŸ’» 43 Β· πŸ”€ 270 Β· πŸ“‹ 280 - 20% open Β· ⏱️ 10.01.2022): +- [GitHub](https://github.com/RUCAIBox/RecBole) (πŸ‘¨β€πŸ’» 43 Β· πŸ”€ 290 Β· πŸ“‹ 300 - 21% open Β· ⏱️ 25.01.2022): ``` git clone https://github.com/RUCAIBox/RecBole ``` -- [PyPi](https://pypi.org/project/recbole) (πŸ“₯ 670 / month Β· ⏱️ 16.09.2021): +- [PyPi](https://pypi.org/project/recbole) (πŸ“₯ 560 / month Β· ⏱️ 16.09.2021): ``` pip install recbole ``` -- [Conda](https://anaconda.org/aibox/recbole) (πŸ“₯ 980 Β· ⏱️ 16.09.2021): +- [Conda](https://anaconda.org/aibox/recbole) (πŸ“₯ 1.1K Β· ⏱️ 16.09.2021): ``` conda install -c aibox recbole ```
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Cornac (πŸ₯‰25 Β· ⭐ 510) - A Comparative Framework for Multimodal Recommender Systems. Apache-2 +
Cornac (πŸ₯‰25 Β· ⭐ 530) - A Comparative Framework for Multimodal Recommender Systems. Apache-2 -- [GitHub](https://github.com/PreferredAI/cornac) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 84 Β· πŸ“¦ 72 Β· πŸ“‹ 80 - 6% open Β· ⏱️ 30.09.2021): +- [GitHub](https://github.com/PreferredAI/cornac) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 86 Β· πŸ“¦ 75 Β· πŸ“‹ 85 - 9% open Β· ⏱️ 30.09.2021): ``` git clone https://github.com/PreferredAI/cornac ``` -- [PyPi](https://pypi.org/project/cornac) (πŸ“₯ 7.1K / month Β· πŸ“¦ 14 Β· ⏱️ 26.09.2021): +- [PyPi](https://pypi.org/project/cornac) (πŸ“₯ 9.2K / month Β· πŸ“¦ 14 Β· ⏱️ 26.09.2021): ``` pip install cornac ``` @@ -6171,33 +6671,33 @@ _Libraries for building and evaluating recommendation systems._ ``` git clone https://github.com/ibayer/fastFM ``` -- [PyPi](https://pypi.org/project/fastfm) (πŸ“₯ 600 / month Β· πŸ“¦ 8 Β· ⏱️ 23.11.2017): +- [PyPi](https://pypi.org/project/fastfm) (πŸ“₯ 610 / month Β· πŸ“¦ 8 Β· ⏱️ 23.11.2017): ``` pip install fastfm ```
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Case Recommender (πŸ₯‰18 Β· ⭐ 380) - Case Recommender: A Flexible and Extensible Python.. MIT +
recmetrics (πŸ₯‰18 Β· ⭐ 340) - A library of metrics for evaluating recommender systems. MIT -- [GitHub](https://github.com/caserec/CaseRecommender) (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 77 Β· πŸ“¦ 9 Β· πŸ“‹ 27 - 25% open Β· ⏱️ 25.11.2021): +- [GitHub](https://github.com/statisticianinstilettos/recmetrics) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 79 Β· πŸ“¦ 22 Β· πŸ“‹ 17 - 41% open Β· ⏱️ 27.10.2021): ``` - git clone https://github.com/caserec/CaseRecommender + git clone https://github.com/statisticianinstilettos/recmetrics ``` -- [PyPi](https://pypi.org/project/caserecommender) (πŸ“₯ 540 / month Β· ⏱️ 25.11.2021): +- [PyPi](https://pypi.org/project/recmetrics) (πŸ“₯ 1K / month Β· ⏱️ 24.09.2021): ``` - pip install caserecommender + pip install recmetrics ```
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recmetrics (πŸ₯‰18 Β· ⭐ 340) - A library of metrics for evaluating recommender systems. MIT +
Case Recommender (πŸ₯‰17 Β· ⭐ 380) - Case Recommender: A Flexible and Extensible Python.. MIT -- [GitHub](https://github.com/statisticianinstilettos/recmetrics) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 76 Β· πŸ“¦ 22 Β· πŸ“‹ 17 - 41% open Β· ⏱️ 27.10.2021): +- [GitHub](https://github.com/caserec/CaseRecommender) (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 77 Β· πŸ“¦ 9 Β· πŸ“‹ 27 - 25% open Β· ⏱️ 25.11.2021): ``` - git clone https://github.com/statisticianinstilettos/recmetrics + git clone https://github.com/caserec/CaseRecommender ``` -- [PyPi](https://pypi.org/project/recmetrics) (πŸ“₯ 600 / month Β· ⏱️ 24.09.2021): +- [PyPi](https://pypi.org/project/caserecommender) (πŸ“₯ 350 / month Β· ⏱️ 25.11.2021): ``` - pip install recmetrics + pip install caserecommender ```
Show 5 hidden projects... @@ -6205,7 +6705,7 @@ _Libraries for building and evaluating recommendation systems._ - scikit-surprise (πŸ₯ˆ28 Β· ⭐ 5.2K Β· πŸ’€) - A Python scikit for building and analyzing recommender.. BSD-3 - tensorrec (πŸ₯‰22 Β· ⭐ 1.2K Β· πŸ’€) - A TensorFlow recommendation algorithm and framework in.. Apache-2 - lkpy (πŸ₯‰21 Β· ⭐ 190) - Python recommendation toolkit. MIT -- Spotlight (πŸ₯‰18 Β· ⭐ 2.6K Β· πŸ’€) - Deep recommender models using PyTorch. MIT +- Spotlight (πŸ₯‰18 Β· ⭐ 2.7K Β· πŸ’€) - Deep recommender models using PyTorch. MIT - OpenRec (πŸ₯‰16 Β· ⭐ 390 Β· πŸ’€) - OpenRec is an open-source and modular library for neural network-.. Apache-2

@@ -6216,58 +6716,66 @@ _Libraries for building and evaluating recommendation systems._ _Libraries for encrypted and privacy-preserving machine learning using methods like federated learning & differential privacy._ -
PySyft (πŸ₯‡35 Β· ⭐ 7.9K) - A library for answering questions using data you cannot see. Apache-2 +
PySyft (πŸ₯‡34 Β· ⭐ 7.9K) - A library for answering questions using data you cannot see. Apache-2 -- [GitHub](https://github.com/OpenMined/PySyft) (πŸ‘¨β€πŸ’» 430 Β· πŸ”€ 1.7K Β· πŸ“‹ 3.1K - 9% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/OpenMined/PySyft) (πŸ‘¨β€πŸ’» 430 Β· πŸ”€ 1.7K Β· πŸ“‹ 3.1K - 9% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/OpenMined/PySyft ``` -- [PyPi](https://pypi.org/project/syft) (πŸ“₯ 3.3K / month Β· πŸ“¦ 5 Β· ⏱️ 01.12.2021): +- [PyPi](https://pypi.org/project/syft) (πŸ“₯ 3.6K / month Β· πŸ“¦ 5 Β· ⏱️ 01.12.2021): ``` pip install syft ```
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FATE (πŸ₯ˆ28 Β· ⭐ 3.9K) - An Industrial Grade Federated Learning Framework. Apache-2 +
TensorFlow Privacy (πŸ₯ˆ27 Β· ⭐ 1.5K) - Library for training machine learning models with.. Apache-2 -- [GitHub](https://github.com/FederatedAI/FATE) (πŸ‘¨β€πŸ’» 69 Β· πŸ”€ 1.1K Β· πŸ“‹ 1.1K - 32% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/tensorflow/privacy) (πŸ‘¨β€πŸ’» 44 Β· πŸ”€ 330 Β· πŸ“₯ 62 Β· πŸ“‹ 150 - 41% open Β· ⏱️ 09.02.2022): ``` - git clone https://github.com/FederatedAI/FATE + git clone https://github.com/tensorflow/privacy + ``` +- [PyPi](https://pypi.org/project/tensorflow-privacy) (πŸ“₯ 31K / month Β· πŸ“¦ 6 Β· ⏱️ 01.09.2021): + ``` + pip install tensorflow-privacy ```
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Opacus (πŸ₯ˆ28 Β· ⭐ 1K) - Training PyTorch models with differential privacy. Apache-2 +
Opacus (πŸ₯ˆ27 Β· ⭐ 1K) - Training PyTorch models with differential privacy. Apache-2 -- [GitHub](https://github.com/pytorch/opacus) (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 170 Β· πŸ“₯ 40 Β· πŸ“¦ 72 Β· πŸ“‹ 120 - 20% open Β· ⏱️ 04.01.2022): +- [GitHub](https://github.com/pytorch/opacus) (πŸ‘¨β€πŸ’» 42 Β· πŸ”€ 180 Β· πŸ“₯ 42 Β· πŸ“¦ 74 Β· πŸ“‹ 140 - 18% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/pytorch/opacus ``` -- [PyPi](https://pypi.org/project/opacus) (πŸ“₯ 2.8K / month Β· πŸ“¦ 10 Β· ⏱️ 04.01.2022): +- [PyPi](https://pypi.org/project/opacus) (πŸ“₯ 4.6K / month Β· πŸ“¦ 11 Β· ⏱️ 09.02.2022): ``` pip install opacus ``` +- [Conda](https://anaconda.org/conda-forge/opacus) (πŸ“₯ 82 Β· ⏱️ 10.02.2022): + ``` + conda install -c conda-forge opacus + ```
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TensorFlow Privacy (πŸ₯‰26 Β· ⭐ 1.5K) - Library for training machine learning models with.. Apache-2 +
FATE (πŸ₯‰25 Β· ⭐ 3.9K Β· πŸ“‰) - An Industrial Grade Federated Learning Framework. Apache-2 -- [GitHub](https://github.com/tensorflow/privacy) (πŸ‘¨β€πŸ’» 43 Β· πŸ”€ 330 Β· πŸ“₯ 59 Β· πŸ“‹ 150 - 41% open Β· ⏱️ 10.01.2022): +- [GitHub](https://github.com/FederatedAI/FATE) (πŸ‘¨β€πŸ’» 69 Β· πŸ”€ 1.1K Β· πŸ“‹ 1.1K - 32% open Β· ⏱️ 27.01.2022): ``` - git clone https://github.com/tensorflow/privacy + git clone https://github.com/FederatedAI/FATE ``` -- [PyPi](https://pypi.org/project/tensorflow-privacy) (πŸ“₯ 22K / month Β· πŸ“¦ 6 Β· ⏱️ 01.09.2021): +- [PyPi](https://pypi.org/project/ETAF) (πŸ“₯ 1 / month Β· ⏱️ 06.05.2020): ``` - pip install tensorflow-privacy + pip install ETAF ```
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CrypTen (πŸ₯‰24 Β· ⭐ 980) - A framework for Privacy Preserving Machine Learning. MIT +
CrypTen (πŸ₯‰23 Β· ⭐ 990) - A framework for Privacy Preserving Machine Learning. MIT -- [GitHub](https://github.com/facebookresearch/CrypTen) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 150 Β· πŸ“¦ 12 Β· πŸ“‹ 140 - 23% open Β· ⏱️ 15.12.2021): +- [GitHub](https://github.com/facebookresearch/CrypTen) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 160 Β· πŸ“¦ 12 Β· πŸ“‹ 140 - 23% open Β· ⏱️ 31.01.2022): ``` git clone https://github.com/facebookresearch/CrypTen ``` -- [PyPi](https://pypi.org/project/crypten) (πŸ“₯ 240 / month Β· ⏱️ 09.09.2021): +- [PyPi](https://pypi.org/project/crypten) (πŸ“₯ 250 / month Β· ⏱️ 09.09.2021): ``` pip install crypten ``` @@ -6284,288 +6792,308 @@ _Libraries for encrypted and privacy-preserving machine learning using methods l _Libraries to organize, track, and visualize machine learning experiments._ -
Tensorboard (πŸ₯‡42 Β· ⭐ 5.7K) - TensorFlows Visualization Toolkit. Apache-2 +
Tensorboard (πŸ₯‡42 Β· ⭐ 5.8K) - TensorFlows Visualization Toolkit. Apache-2 -- [GitHub](https://github.com/tensorflow/tensorboard) (πŸ‘¨β€πŸ’» 280 Β· πŸ”€ 1.5K Β· πŸ“¦ 91K Β· πŸ“‹ 1.6K - 34% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/tensorflow/tensorboard) (πŸ‘¨β€πŸ’» 280 Β· πŸ”€ 1.5K Β· πŸ“¦ 94K Β· πŸ“‹ 1.6K - 33% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/tensorflow/tensorboard ``` -- [PyPi](https://pypi.org/project/tensorboard) (πŸ“₯ 11M / month Β· πŸ“¦ 2.3K Β· ⏱️ 13.10.2021): +- [PyPi](https://pypi.org/project/tensorboard) (πŸ“₯ 13M / month Β· πŸ“¦ 2.3K Β· ⏱️ 20.01.2022): ``` pip install tensorboard ``` -- [Conda](https://anaconda.org/conda-forge/tensorboard) (πŸ“₯ 2.7M Β· ⏱️ 10.11.2021): +- [Conda](https://anaconda.org/conda-forge/tensorboard) (πŸ“₯ 2.7M Β· ⏱️ 04.02.2022): ``` conda install -c conda-forge tensorboard ```
mlflow (πŸ₯‡40 Β· ⭐ 11K) - Open source platform for the machine learning lifecycle. Apache-2 -- [GitHub](https://github.com/mlflow/mlflow) (πŸ‘¨β€πŸ’» 350 Β· πŸ”€ 2.4K Β· πŸ“‹ 2.1K - 44% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/mlflow/mlflow) (πŸ‘¨β€πŸ’» 350 Β· πŸ”€ 2.5K Β· πŸ“‹ 2.2K - 45% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/mlflow/mlflow ``` -- [PyPi](https://pypi.org/project/mlflow) (πŸ“₯ 15M / month Β· πŸ“¦ 260 Β· ⏱️ 30.11.2021): +- [PyPi](https://pypi.org/project/mlflow) (πŸ“₯ 14M / month Β· πŸ“¦ 280 Β· ⏱️ 27.01.2022): ``` pip install mlflow ``` -- [Conda](https://anaconda.org/conda-forge/mlflow) (πŸ“₯ 460K Β· ⏱️ 08.12.2021): +- [Conda](https://anaconda.org/conda-forge/mlflow) (πŸ“₯ 480K Β· ⏱️ 27.01.2022): ``` conda install -c conda-forge mlflow ```
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DVC (πŸ₯‡36 Β· ⭐ 9.1K) - Data Version Control | Git for Data & Models | ML Experiments Management. Apache-2 +
PyCaret (πŸ₯‡37 Β· ⭐ 5.1K) - An open-source, low-code machine learning library in Python. MIT -- [GitHub](https://github.com/iterative/dvc) (πŸ‘¨β€πŸ’» 260 Β· πŸ”€ 880 Β· πŸ“₯ 54K Β· πŸ“‹ 3.5K - 17% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/pycaret/pycaret) (πŸ‘¨β€πŸ’» 72 Β· πŸ”€ 1.1K Β· πŸ“₯ 520 Β· πŸ“¦ 1.8K Β· πŸ“‹ 1.3K - 15% open Β· ⏱️ 03.02.2022): ``` - git clone https://github.com/iterative/dvc + git clone https://github.com/pycaret/pycaret ``` -- [PyPi](https://pypi.org/project/dvc) (πŸ“₯ 260K / month Β· πŸ“¦ 46 Β· ⏱️ 22.12.2021): +- [PyPi](https://pypi.org/project/pycaret) (πŸ“₯ 320K / month Β· πŸ“¦ 12 Β· ⏱️ 12.01.2022): ``` - pip install dvc + pip install pycaret ``` -- [Conda](https://anaconda.org/conda-forge/dvc) (πŸ“₯ 970K Β· ⏱️ 25.12.2021): +- [Conda](https://anaconda.org/conda-forge/pycaret) (πŸ“₯ 7.2K Β· ⏱️ 12.01.2022): ``` - conda install -c conda-forge dvc + conda install -c conda-forge pycaret ```
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PyCaret (πŸ₯‡36 Β· ⭐ 4.8K Β· πŸ“ˆ) - An open-source, low-code machine learning library in Python. MIT +
DVC (πŸ₯‡36 Β· ⭐ 9.2K) - Data Version Control | Git for Data & Models | ML Experiments Management. Apache-2 -- [GitHub](https://github.com/pycaret/pycaret) (πŸ‘¨β€πŸ’» 69 Β· πŸ”€ 1.1K Β· πŸ“₯ 510 Β· πŸ“¦ 1.7K Β· πŸ“‹ 1.3K - 16% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/iterative/dvc) (πŸ‘¨β€πŸ’» 260 Β· πŸ”€ 880 Β· πŸ“₯ 60K Β· πŸ“‹ 3.5K - 17% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/pycaret/pycaret + git clone https://github.com/iterative/dvc ``` -- [PyPi](https://pypi.org/project/pycaret) (πŸ“₯ 280K / month Β· πŸ“¦ 11 Β· ⏱️ 12.01.2022): +- [PyPi](https://pypi.org/project/dvc) (πŸ“₯ 340K / month Β· πŸ“¦ 46 Β· ⏱️ 22.12.2021): ``` - pip install pycaret + pip install dvc + ``` +- [Conda](https://anaconda.org/conda-forge/dvc) (πŸ“₯ 980K Β· ⏱️ 25.12.2021): + ``` + conda install -c conda-forge dvc ```
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SageMaker SDK (πŸ₯‡36 Β· ⭐ 1.5K) - A library for training and deploying machine learning.. Apache-2 +
SageMaker SDK (πŸ₯‡36 Β· ⭐ 1.6K) - A library for training and deploying machine learning.. Apache-2 -- [GitHub](https://github.com/aws/sagemaker-python-sdk) (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 730 Β· πŸ“¦ 1K Β· πŸ“‹ 980 - 33% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/aws/sagemaker-python-sdk) (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 740 Β· πŸ“¦ 1.1K Β· πŸ“‹ 970 - 33% open Β· ⏱️ 07.02.2022): ``` git clone https://github.com/aws/sagemaker-python-sdk ``` -- [PyPi](https://pypi.org/project/sagemaker) (πŸ“₯ 2.1M / month Β· πŸ“¦ 44 Β· ⏱️ 10.01.2022): +- [PyPi](https://pypi.org/project/sagemaker) (πŸ“₯ 2.7M / month Β· πŸ“¦ 44 Β· ⏱️ 08.02.2022): ``` pip install sagemaker ``` +- [Conda](https://anaconda.org/conda-forge/sagemaker-python-sdk) (πŸ“₯ 230K Β· ⏱️ 08.02.2022): + ``` + conda install -c conda-forge sagemaker-python-sdk + ```
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tensorboardX (πŸ₯ˆ34 Β· ⭐ 7.2K) - tensorboard for pytorch (and chainer, mxnet, numpy, ...). MIT +
wandb client (πŸ₯ˆ35 Β· ⭐ 3.7K) - A tool for visualizing and tracking your machine learning.. MIT -- [GitHub](https://github.com/lanpa/tensorboardX) (πŸ‘¨β€πŸ’» 70 Β· πŸ”€ 840 Β· πŸ“₯ 340 Β· πŸ“¦ 16K Β· πŸ“‹ 440 - 16% open Β· ⏱️ 26.12.2021): +- [GitHub](https://github.com/wandb/client) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 290 Β· πŸ“‹ 1.7K - 21% open Β· ⏱️ 09.02.2022): ``` - git clone https://github.com/lanpa/tensorboardX + git clone https://github.com/wandb/client ``` -- [PyPi](https://pypi.org/project/tensorboardX) (πŸ“₯ 540K / month Β· πŸ“¦ 860 Β· ⏱️ 21.11.2021): +- [PyPi](https://pypi.org/project/wandb) (πŸ“₯ 650K / month Β· πŸ“¦ 200 Β· ⏱️ 01.02.2022): ``` - pip install tensorboardX + pip install wandb ``` -- [Conda](https://anaconda.org/conda-forge/tensorboardx) (πŸ“₯ 630K Β· ⏱️ 10.08.2021): +- [Conda](https://anaconda.org/conda-forge/wandb) (πŸ“₯ 43K Β· ⏱️ 02.02.2022): ``` - conda install -c conda-forge tensorboardx + conda install -c conda-forge wandb ```
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wandb client (πŸ₯ˆ34 Β· ⭐ 3.6K) - A tool for visualizing and tracking your machine learning.. MIT +
tensorboardX (πŸ₯ˆ34 Β· ⭐ 7.2K) - tensorboard for pytorch (and chainer, mxnet, numpy, ...). MIT -- [GitHub](https://github.com/wandb/client) (πŸ‘¨β€πŸ’» 98 Β· πŸ”€ 280 Β· πŸ“‹ 1.6K - 22% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/lanpa/tensorboardX) (πŸ‘¨β€πŸ’» 70 Β· πŸ”€ 840 Β· πŸ“₯ 340 Β· πŸ“¦ 17K Β· πŸ“‹ 440 - 16% open Β· ⏱️ 06.02.2022): ``` - git clone https://github.com/wandb/client + git clone https://github.com/lanpa/tensorboardX ``` -- [PyPi](https://pypi.org/project/wandb) (πŸ“₯ 490K / month Β· πŸ“¦ 190 Β· ⏱️ 17.12.2021): +- [PyPi](https://pypi.org/project/tensorboardX) (πŸ“₯ 660K / month Β· πŸ“¦ 860 Β· ⏱️ 21.11.2021): ``` - pip install wandb + pip install tensorboardX + ``` +- [Conda](https://anaconda.org/conda-forge/tensorboardx) (πŸ“₯ 640K Β· ⏱️ 10.08.2021): + ``` + conda install -c conda-forge tensorboardx ```
AzureML SDK (πŸ₯ˆ34 Β· ⭐ 2.8K) - Python notebooks with ML and deep learning examples with Azure.. MIT -- [GitHub](https://github.com/Azure/MachineLearningNotebooks) (πŸ‘¨β€πŸ’» 57 Β· πŸ”€ 2K Β· πŸ“₯ 430 Β· πŸ“‹ 1.2K - 16% open Β· ⏱️ 13.12.2021): +- [GitHub](https://github.com/Azure/MachineLearningNotebooks) (πŸ‘¨β€πŸ’» 59 Β· πŸ”€ 2K Β· πŸ“₯ 430 Β· πŸ“‹ 1.2K - 16% open Β· ⏱️ 02.02.2022): ``` git clone https://github.com/Azure/MachineLearningNotebooks ``` -- [PyPi](https://pypi.org/project/azureml-sdk) (πŸ“₯ 1.8M / month Β· πŸ“¦ 45 Β· ⏱️ 13.12.2021): +- [PyPi](https://pypi.org/project/azureml-sdk) (πŸ“₯ 1.5M / month Β· πŸ“¦ 45 Β· ⏱️ 24.01.2022): ``` pip install azureml-sdk ```
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snakemake (πŸ₯ˆ33 Β· ⭐ 1.2K) - This is the development home of the workflow management system.. MIT +
snakemake (πŸ₯ˆ34 Β· ⭐ 1.2K) - This is the development home of the workflow management system.. MIT -- [GitHub](https://github.com/snakemake/snakemake) (πŸ‘¨β€πŸ’» 230 Β· πŸ”€ 280 Β· πŸ“¦ 1K Β· πŸ“‹ 820 - 64% open Β· ⏱️ 11.01.2022): +- [GitHub](https://github.com/snakemake/snakemake) (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 290 Β· πŸ“¦ 1K Β· πŸ“‹ 830 - 63% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/snakemake/snakemake ``` -- [PyPi](https://pypi.org/project/snakemake) (πŸ“₯ 49K / month Β· πŸ“¦ 200 Β· ⏱️ 11.01.2022): +- [PyPi](https://pypi.org/project/snakemake) (πŸ“₯ 70K / month Β· πŸ“¦ 200 Β· ⏱️ 09.02.2022): ``` pip install snakemake ``` -- [Conda](https://anaconda.org/bioconda/snakemake) (πŸ“₯ 370K Β· ⏱️ 12.01.2022): +- [Conda](https://anaconda.org/bioconda/snakemake) (πŸ“₯ 380K Β· ⏱️ 10.02.2022): ``` conda install -c bioconda snakemake ```
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Metaflow (πŸ₯ˆ32 Β· ⭐ 5.2K) - Build and manage real-life data science projects with ease!. Apache-2 +
ClearML (πŸ₯ˆ33 Β· ⭐ 3K) - ClearML - Auto-Magical CI/CD to streamline your ML workflow... Apache-2 -- [GitHub](https://github.com/Netflix/metaflow) (πŸ‘¨β€πŸ’» 44 Β· πŸ”€ 460 Β· πŸ“¦ 240 Β· πŸ“‹ 410 - 53% open Β· ⏱️ 11.01.2022): +- [GitHub](https://github.com/allegroai/clearml) (πŸ‘¨β€πŸ’» 46 Β· πŸ”€ 410 Β· πŸ“₯ 380 Β· πŸ“¦ 190 Β· πŸ“‹ 460 - 36% open Β· ⏱️ 07.02.2022): ``` - git clone https://github.com/Netflix/metaflow + git clone https://github.com/allegroai/clearml ``` -- [PyPi](https://pypi.org/project/metaflow) (πŸ“₯ 45K / month Β· πŸ“¦ 4 Β· ⏱️ 11.01.2022): +- [PyPi](https://pypi.org/project/clearml) (πŸ“₯ 62K / month Β· πŸ“¦ 4 Β· ⏱️ 07.02.2022): ``` - pip install metaflow + pip install clearml ``` -- [Conda](https://anaconda.org/conda-forge/metaflow) (πŸ“₯ 30K Β· ⏱️ 11.01.2022): +- [Docker Hub](https://hub.docker.com/r/allegroai/trains) (πŸ“₯ 30K Β· ⏱️ 05.10.2020): ``` - conda install -c conda-forge metaflow + docker pull allegroai/trains ```
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ClearML (πŸ₯ˆ32 Β· ⭐ 2.9K) - ClearML - Auto-Magical CI/CD to streamline your ML workflow... Apache-2 +
Metaflow (πŸ₯ˆ32 Β· ⭐ 5.3K) - Build and manage real-life data science projects with ease!. Apache-2 -- [GitHub](https://github.com/allegroai/clearml) (πŸ‘¨β€πŸ’» 44 Β· πŸ”€ 400 Β· πŸ“₯ 380 Β· πŸ“¦ 170 Β· πŸ“‹ 440 - 33% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/Netflix/metaflow) (πŸ‘¨β€πŸ’» 47 Β· πŸ”€ 460 Β· πŸ“¦ 240 Β· πŸ“‹ 420 - 53% open Β· ⏱️ 03.02.2022): ``` - git clone https://github.com/allegroai/clearml + git clone https://github.com/Netflix/metaflow ``` -- [PyPi](https://pypi.org/project/clearml) (πŸ“₯ 59K / month Β· πŸ“¦ 4 Β· ⏱️ 08.01.2022): +- [PyPi](https://pypi.org/project/metaflow) (πŸ“₯ 45K / month Β· πŸ“¦ 5 Β· ⏱️ 26.01.2022): ``` - pip install clearml + pip install metaflow ``` -- [Docker Hub](https://hub.docker.com/r/allegroai/trains) (πŸ“₯ 30K Β· ⏱️ 05.10.2020): +- [Conda](https://anaconda.org/conda-forge/metaflow) (πŸ“₯ 31K Β· ⏱️ 26.01.2022): ``` - docker pull allegroai/trains + conda install -c conda-forge metaflow ```
VisualDL (πŸ₯ˆ31 Β· ⭐ 4.3K) - Deep Learning Visualization Toolkit. Apache-2 -- [GitHub](https://github.com/PaddlePaddle/VisualDL) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 580 Β· πŸ“₯ 160 Β· πŸ“¦ 900 Β· πŸ“‹ 390 - 14% open Β· ⏱️ 30.12.2021): +- [GitHub](https://github.com/PaddlePaddle/VisualDL) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 580 Β· πŸ“₯ 160 Β· πŸ“¦ 960 Β· πŸ“‹ 390 - 15% open Β· ⏱️ 30.12.2021): ``` git clone https://github.com/PaddlePaddle/VisualDL ``` -- [PyPi](https://pypi.org/project/visualdl) (πŸ“₯ 42K / month Β· πŸ“¦ 23 Β· ⏱️ 06.01.2022): +- [PyPi](https://pypi.org/project/visualdl) (πŸ“₯ 54K / month Β· πŸ“¦ 23 Β· ⏱️ 06.01.2022): ``` pip install visualdl ```
Catalyst (πŸ₯ˆ31 Β· ⭐ 2.8K) - Accelerated deep learning R&D. Apache-2 -- [GitHub](https://github.com/catalyst-team/catalyst) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 350 Β· πŸ“¦ 460 Β· πŸ“‹ 330 - 1% open Β· ⏱️ 28.12.2021): +- [GitHub](https://github.com/catalyst-team/catalyst) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 350 Β· πŸ“¦ 470 Β· πŸ“‹ 330 - 1% open Β· ⏱️ 07.02.2022): ``` git clone https://github.com/catalyst-team/catalyst ``` -- [PyPi](https://pypi.org/project/catalyst) (πŸ“₯ 8.9K / month Β· πŸ“¦ 29 Β· ⏱️ 28.12.2021): +- [PyPi](https://pypi.org/project/catalyst) (πŸ“₯ 11K / month Β· πŸ“¦ 29 Β· ⏱️ 07.02.2022): ``` pip install catalyst ```
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aim (πŸ₯ˆ31 Β· ⭐ 1.9K) - Aim an easy-to-use and performant open-source experiment tracker. Apache-2 +
aim (πŸ₯ˆ31 Β· ⭐ 2.1K) - Aim an easy-to-use and performant open-source experiment tracker. Apache-2 -- [GitHub](https://github.com/aimhubio/aim) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 110 Β· πŸ“¦ 49 Β· πŸ“‹ 300 - 37% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/aimhubio/aim) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 120 Β· πŸ“¦ 52 Β· πŸ“‹ 330 - 33% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/aimhubio/aim ``` -- [PyPi](https://pypi.org/project/aim) (πŸ“₯ 8.5K / month Β· πŸ“¦ 2 Β· ⏱️ 10.01.2022): +- [PyPi](https://pypi.org/project/aim) (πŸ“₯ 12K / month Β· πŸ“¦ 2 Β· ⏱️ 04.02.2022): ``` pip install aim ``` +- [Conda](https://anaconda.org/conda-forge/aim) (πŸ“₯ 7.1K Β· ⏱️ 15.10.2021): + ``` + conda install -c conda-forge aim + ```
sacred (πŸ₯ˆ29 Β· ⭐ 3.7K) - Sacred is a tool to help you configure, organize, log and reproduce.. MIT -- [GitHub](https://github.com/IDSIA/sacred) (πŸ‘¨β€πŸ’» 95 Β· πŸ”€ 340 Β· πŸ“¦ 1.2K Β· πŸ“‹ 520 - 18% open Β· ⏱️ 05.11.2021): +- [GitHub](https://github.com/IDSIA/sacred) (πŸ‘¨β€πŸ’» 96 Β· πŸ”€ 340 Β· πŸ“¦ 1.2K Β· πŸ“‹ 520 - 18% open Β· ⏱️ 26.01.2022): ``` git clone https://github.com/IDSIA/sacred ``` -- [PyPi](https://pypi.org/project/sacred) (πŸ“₯ 30K / month Β· πŸ“¦ 100 Β· ⏱️ 14.12.2020): +- [PyPi](https://pypi.org/project/sacred) (πŸ“₯ 25K / month Β· πŸ“¦ 100 Β· ⏱️ 14.12.2020): ``` pip install sacred ``` +- [Conda](https://anaconda.org/conda-forge/sacred) (πŸ“₯ 130 Β· ⏱️ 14.11.2021): + ``` + conda install -c conda-forge sacred + ```
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kaggle (πŸ₯‰28 Β· ⭐ 4.5K Β· πŸ’€) - Official Kaggle API. Apache-2 +
kaggle (πŸ₯‰28 Β· ⭐ 4.6K Β· πŸ’€) - Official Kaggle API. Apache-2 -- [GitHub](https://github.com/Kaggle/kaggle-api) (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 870 Β· πŸ“‹ 330 - 56% open Β· ⏱️ 15.03.2021): +- [GitHub](https://github.com/Kaggle/kaggle-api) (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 880 Β· πŸ“‹ 340 - 56% open Β· ⏱️ 15.03.2021): ``` git clone https://github.com/Kaggle/kaggle-api ``` -- [PyPi](https://pypi.org/project/kaggle) (πŸ“₯ 110K / month Β· πŸ“¦ 320 Β· ⏱️ 13.03.2021): +- [PyPi](https://pypi.org/project/kaggle) (πŸ“₯ 130K / month Β· πŸ“¦ 320 Β· ⏱️ 13.03.2021): ``` pip install kaggle ``` -- [Conda](https://anaconda.org/conda-forge/kaggle) (πŸ“₯ 76K Β· ⏱️ 17.12.2021): +- [Conda](https://anaconda.org/conda-forge/kaggle) (πŸ“₯ 77K Β· ⏱️ 17.12.2021): ``` conda install -c conda-forge kaggle ```
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ml-metadata (πŸ₯‰28 Β· ⭐ 420) - For recording and retrieving metadata associated with ML.. Apache-2 +
ml-metadata (πŸ₯‰28 Β· ⭐ 430) - For recording and retrieving metadata associated with ML.. Apache-2 -- [GitHub](https://github.com/google/ml-metadata) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 81 Β· πŸ“₯ 1.7K Β· πŸ“¦ 170 Β· πŸ“‹ 78 - 25% open Β· ⏱️ 24.12.2021): +- [GitHub](https://github.com/google/ml-metadata) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 87 Β· πŸ“₯ 1.7K Β· πŸ“¦ 180 Β· πŸ“‹ 82 - 26% open Β· ⏱️ 25.01.2022): ``` git clone https://github.com/google/ml-metadata ``` -- [PyPi](https://pypi.org/project/ml-metadata) (πŸ“₯ 460K / month Β· πŸ“¦ 18 Β· ⏱️ 30.11.2021): +- [PyPi](https://pypi.org/project/ml-metadata) (πŸ“₯ 450K / month Β· πŸ“¦ 18 Β· ⏱️ 21.01.2022): ``` pip install ml-metadata ```
livelossplot (πŸ₯‰25 Β· ⭐ 1.2K) - Live training loss plot in Jupyter Notebook for Keras,.. MIT -- [GitHub](https://github.com/stared/livelossplot) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 140 Β· πŸ“¦ 700 Β· πŸ“‹ 74 - 5% open Β· ⏱️ 12.10.2021): +- [GitHub](https://github.com/stared/livelossplot) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 140 Β· πŸ“¦ 720 Β· πŸ“‹ 74 - 5% open Β· ⏱️ 12.10.2021): ``` git clone https://github.com/stared/livelossplot ``` -- [PyPi](https://pypi.org/project/livelossplot) (πŸ“₯ 65K / month Β· πŸ“¦ 8 Β· ⏱️ 03.02.2021): +- [PyPi](https://pypi.org/project/livelossplot) (πŸ“₯ 64K / month Β· πŸ“¦ 8 Β· ⏱️ 03.02.2021): ``` pip install livelossplot ```
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Labml (πŸ₯‰25 Β· ⭐ 940) - Monitor deep learning model training and hardware usage from your mobile.. MIT +
Labml (πŸ₯‰25 Β· ⭐ 1K) - Monitor deep learning model training and hardware usage from your mobile phone. MIT -- [GitHub](https://github.com/labmlai/labml) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 69 Β· πŸ“¦ 41 Β· πŸ“‹ 25 - 52% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/labmlai/labml) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 71 Β· πŸ“¦ 42 Β· πŸ“‹ 25 - 52% open Β· ⏱️ 05.02.2022): ``` git clone https://github.com/labmlai/labml ``` -- [PyPi](https://pypi.org/project/labml) (πŸ“₯ 16K / month Β· πŸ“¦ 6 Β· ⏱️ 13.01.2022): +- [PyPi](https://pypi.org/project/labml) (πŸ“₯ 7.6K / month Β· πŸ“¦ 6 Β· ⏱️ 18.01.2022): ``` pip install labml ```
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Guild AI (πŸ₯‰25 Β· ⭐ 650) - Experiment tracking, ML developer tools. Apache-2 +
Guild AI (πŸ₯‰25 Β· ⭐ 660) - Experiment tracking, ML developer tools. Apache-2 -- [GitHub](https://github.com/guildai/guildai) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 59 Β· πŸ“¦ 42 Β· πŸ“‹ 300 - 40% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/guildai/guildai) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 59 Β· πŸ“¦ 42 Β· πŸ“‹ 300 - 38% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/guildai/guildai ``` -- [PyPi](https://pypi.org/project/guildai) (πŸ“₯ 2.8K / month Β· ⏱️ 07.01.2022): +- [PyPi](https://pypi.org/project/guildai) (πŸ“₯ 3.8K / month Β· ⏱️ 07.02.2022): ``` pip install guildai ```
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TNT (πŸ₯‰23 Β· ⭐ 1.4K Β· πŸ’€) - Simple tools for logging and visualizing, loading and training. BSD-3 +
lore (πŸ₯‰22 Β· ⭐ 1.5K) - Lore makes machine learning approachable for Software Engineers and.. MIT -- [GitHub](https://github.com/pytorch/tnt) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 190 Β· πŸ“‹ 65 - 46% open Β· ⏱️ 05.01.2021): +- [GitHub](https://github.com/instacart/lore) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 130 Β· πŸ“¦ 17 Β· πŸ“‹ 44 - 59% open Β· ⏱️ 02.02.2022): ``` - git clone https://github.com/pytorch/tnt + git clone https://github.com/instacart/lore ``` -- [PyPi](https://pypi.org/project/torchnet) (πŸ“₯ 17K / month Β· πŸ“¦ 36 Β· ⏱️ 29.07.2018): +- [PyPi](https://pypi.org/project/lore) (πŸ“₯ 2.5K / month Β· πŸ“¦ 1 Β· ⏱️ 02.02.2022): ``` - pip install torchnet + pip install lore ```
Studio.ml (πŸ₯‰22 Β· ⭐ 370) - Studio: Simplify and expedite model building process. Apache-2 @@ -6575,60 +7103,51 @@ _Libraries to organize, track, and visualize machine learning experiments._ ``` git clone https://github.com/studioml/studio ``` -- [PyPi](https://pypi.org/project/studioml) (πŸ“₯ 260 / month Β· ⏱️ 14.09.2021): +- [PyPi](https://pypi.org/project/studioml) (πŸ“₯ 710 / month Β· ⏱️ 14.09.2021): ``` pip install studioml ```
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TensorWatch (πŸ₯‰21 Β· ⭐ 3.2K Β· πŸ’€) - Debugging, monitoring and visualization for Python Machine.. MIT - -- [GitHub](https://github.com/microsoft/tensorwatch) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 340 Β· πŸ“¦ 65 Β· πŸ“‹ 65 - 76% open Β· ⏱️ 15.01.2021): - - ``` - git clone https://github.com/microsoft/tensorwatch - ``` -- [PyPi](https://pypi.org/project/tensorwatch) (πŸ“₯ 2.9K / month Β· πŸ“¦ 6 Β· ⏱️ 04.03.2020): - ``` - pip install tensorwatch - ``` -
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quinn (πŸ₯‰19 Β· ⭐ 300 Β· πŸ’€) - pyspark methods to enhance developer productivity. Apache-2 +
quinn (πŸ₯‰19 Β· ⭐ 310 Β· πŸ’€) - pyspark methods to enhance developer productivity. Apache-2 - [GitHub](https://github.com/MrPowers/quinn) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 40 Β· πŸ“‹ 26 - 65% open Β· ⏱️ 09.02.2021): ``` git clone https://github.com/MrPowers/quinn ``` -- [PyPi](https://pypi.org/project/quinn) (πŸ“₯ 470K / month Β· πŸ“¦ 4 Β· ⏱️ 06.02.2021): +- [PyPi](https://pypi.org/project/quinn) (πŸ“₯ 460K / month Β· πŸ“¦ 4 Β· ⏱️ 06.02.2021): ``` pip install quinn ```
keepsake (πŸ₯‰18 Β· ⭐ 1.5K Β· πŸ’€) - Version control for machine learning. Apache-2 -- [GitHub](https://github.com/replicate/keepsake) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 59 Β· πŸ“‹ 190 - 65% open Β· ⏱️ 07.05.2021): +- [GitHub](https://github.com/replicate/keepsake) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 60 Β· πŸ“‹ 190 - 65% open Β· ⏱️ 07.05.2021): ``` git clone https://github.com/replicate/keepsake ``` -- [PyPi](https://pypi.org/project/keepsake) (πŸ“₯ 730 / month Β· ⏱️ 11.03.2021): +- [PyPi](https://pypi.org/project/keepsake) (πŸ“₯ 840 / month Β· ⏱️ 11.03.2021): ``` pip install keepsake ```
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Show 11 hidden projects... +
Show 14 hidden projects... - SKLL (πŸ₯‰25 Β· ⭐ 530) - SciKit-Learn Laboratory (SKLL) makes it easy to run machine.. ❗️BSD-1-Clause -- knockknock (πŸ₯‰22 Β· ⭐ 2.3K Β· πŸ’€) - Knock Knock: Get notified when your training ends with only two.. MIT +- knockknock (πŸ₯‰23 Β· ⭐ 2.4K Β· πŸ’€) - Knock Knock: Get notified when your training ends with only two.. MIT +- TNT (πŸ₯‰23 Β· ⭐ 1.4K Β· πŸ’€) - Simple tools for logging and visualizing, loading and training. BSD-3 +- TensorWatch (πŸ₯‰21 Β· ⭐ 3.2K Β· πŸ’€) - Debugging, monitoring and visualization for Python Machine.. MIT - hiddenlayer (πŸ₯‰21 Β· ⭐ 1.6K Β· πŸ’€) - Neural network graphs and training metrics for.. MIT -- lore (πŸ₯‰21 Β· ⭐ 1.5K Β· πŸ’€) - Lore makes machine learning approachable for Software Engineers and.. MIT - TensorBoard Logger (πŸ₯‰21 Β· ⭐ 620 Β· πŸ’€) - Log TensorBoard events without touching TensorFlow. MIT - gokart (πŸ₯‰21 Β· ⭐ 230) - Gokart solves reproducibility, task dependencies, constraints of good code,.. MIT - MXBoard (πŸ₯‰20 Β· ⭐ 330 Β· πŸ’€) - Logging MXNet data for visualization in TensorBoard. Apache-2 -- datmo (πŸ₯‰19 Β· ⭐ 340 Β· πŸ’€) - Open source production model management tool for data scientists. MIT +- chitra (πŸ₯‰19 Β· ⭐ 180 Β· βž•) - A multi-functional library for full-stack Deep Learning... Apache-2 +- datmo (πŸ₯‰18 Β· ⭐ 340 Β· πŸ’€) - Open source production model management tool for data scientists. MIT - steppy (πŸ₯‰16 Β· ⭐ 130 Β· πŸ’€) - Lightweight, Python library for fast and reproducible experimentation. MIT +- caliban (πŸ₯‰14 Β· ⭐ 410 Β· πŸ’€) - Research workflows made easy, locally and in the Cloud. Apache-2 - ModelChimp (πŸ₯‰13 Β· ⭐ 120) - Experiment tracking for machine and deep learning projects. BSD-2 -- traintool (πŸ₯‰8 Β· ⭐ 9 Β· πŸ’€) - Train off-the-shelf machine learning models in one.. Apache-2 +- traintool (πŸ₯‰9 Β· ⭐ 9 Β· πŸ’€) - Train off-the-shelf machine learning models in one.. Apache-2

@@ -6638,25 +7157,25 @@ _Libraries to organize, track, and visualize machine learning experiments._ _Libraries to serialize models to files, convert between a variety of model formats, and optimize models for deployment._ -
onnx (πŸ₯‡40 Β· ⭐ 12K) - Open standard for machine learning interoperability. Apache-2 +
onnx (πŸ₯‡41 Β· ⭐ 12K) - Open standard for machine learning interoperability. Apache-2 -- [GitHub](https://github.com/onnx/onnx) (πŸ‘¨β€πŸ’» 220 Β· πŸ”€ 2.3K Β· πŸ“₯ 17K Β· πŸ“¦ 5.2K Β· πŸ“‹ 1.8K - 26% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/onnx/onnx) (πŸ‘¨β€πŸ’» 220 Β· πŸ”€ 2.3K Β· πŸ“₯ 17K Β· πŸ“¦ 5.5K Β· πŸ“‹ 1.8K - 26% open Β· ⏱️ 07.02.2022): ``` git clone https://github.com/onnx/onnx ``` -- [PyPi](https://pypi.org/project/onnx) (πŸ“₯ 1.2M / month Β· πŸ“¦ 320 Β· ⏱️ 26.10.2021): +- [PyPi](https://pypi.org/project/onnx) (πŸ“₯ 1.4M / month Β· πŸ“¦ 320 Β· ⏱️ 26.10.2021): ``` pip install onnx ``` -- [Conda](https://anaconda.org/conda-forge/onnx) (πŸ“₯ 340K Β· ⏱️ 14.12.2021): +- [Conda](https://anaconda.org/conda-forge/onnx) (πŸ“₯ 350K Β· ⏱️ 14.12.2021): ``` conda install -c conda-forge onnx ```
Core ML Tools (πŸ₯‡31 Β· ⭐ 2.5K) - Core ML tools contain supporting tools for Core ML model.. BSD-3 -- [GitHub](https://github.com/apple/coremltools) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 390 Β· πŸ“₯ 3.9K Β· πŸ“¦ 730 Β· πŸ“‹ 850 - 37% open Β· ⏱️ 10.01.2022): +- [GitHub](https://github.com/apple/coremltools) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 390 Β· πŸ“₯ 4K Β· πŸ“¦ 760 Β· πŸ“‹ 870 - 36% open Β· ⏱️ 21.01.2022): ``` git clone https://github.com/apple/coremltools @@ -6665,82 +7184,102 @@ _Libraries to serialize models to files, convert between a variety of model form ``` pip install coremltools ``` +- [Conda](https://anaconda.org/conda-forge/coremltools) (πŸ“₯ 27K Β· ⏱️ 15.10.2021): + ``` + conda install -c conda-forge coremltools + ```
TorchServe (πŸ₯ˆ30 Β· ⭐ 2.4K) - Model Serving on PyTorch. Apache-2 -- [GitHub](https://github.com/pytorch/serve) (πŸ‘¨β€πŸ’» 95 Β· πŸ”€ 430 Β· πŸ“₯ 790 Β· πŸ“‹ 770 - 16% open Β· ⏱️ 07.01.2022): +- [GitHub](https://github.com/pytorch/serve) (πŸ‘¨β€πŸ’» 95 Β· πŸ”€ 450 Β· πŸ“₯ 950 Β· πŸ“‹ 790 - 16% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/pytorch/serve ``` -- [PyPi](https://pypi.org/project/torchserve) (πŸ“₯ 9.2K / month Β· πŸ“¦ 8 Β· ⏱️ 29.12.2021): +- [PyPi](https://pypi.org/project/torchserve) (πŸ“₯ 11K / month Β· πŸ“¦ 8 Β· ⏱️ 29.12.2021): ``` pip install torchserve ``` -- [Conda](https://anaconda.org/pytorch/torchserve) (πŸ“₯ 18K Β· ⏱️ 29.12.2021): +- [Conda](https://anaconda.org/pytorch/torchserve) (πŸ“₯ 19K Β· ⏱️ 29.12.2021): ``` conda install -c pytorch torchserve ``` -- [Docker Hub](https://hub.docker.com/r/pytorch/torchserve) (πŸ“₯ 960K Β· ⭐ 11 Β· ⏱️ 29.12.2021): +- [Docker Hub](https://hub.docker.com/r/pytorch/torchserve) (πŸ“₯ 970K Β· ⭐ 11 Β· ⏱️ 29.12.2021): ``` docker pull pytorch/torchserve ```
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BentoML (πŸ₯ˆ29 Β· ⭐ 3.1K) - Model Serving Made Easy. Apache-2 +
huggingface_hub (πŸ₯ˆ29 Β· ⭐ 330) - All the open source things related to the Hugging Face Hub. Apache-2 -- [GitHub](https://github.com/bentoml/BentoML) (πŸ‘¨β€πŸ’» 90 Β· πŸ”€ 360 Β· πŸ“₯ 930 Β· πŸ“¦ 160 Β· πŸ“‹ 520 - 17% open Β· ⏱️ 03.12.2021): +- [GitHub](https://github.com/huggingface/huggingface_hub) (πŸ‘¨β€πŸ’» 55 Β· πŸ”€ 71 Β· πŸ“‹ 210 - 48% open Β· ⏱️ 09.02.2022): ``` - git clone https://github.com/bentoml/BentoML + git clone https://github.com/huggingface/huggingface_hub ``` -- [PyPi](https://pypi.org/project/bentoml) (πŸ“₯ 10K / month Β· πŸ“¦ 1 Β· ⏱️ 14.12.2021): +- [PyPi](https://pypi.org/project/huggingface_hub) (πŸ“₯ 2.5M / month Β· πŸ“¦ 51 Β· ⏱️ 11.01.2022): ``` - pip install bentoml + pip install huggingface_hub + ``` +- [Conda](https://anaconda.org/conda-forge/huggingface_hub) (πŸ“₯ 27K Β· ⏱️ 12.01.2022): + ``` + conda install -c conda-forge huggingface_hub ```
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huggingface_hub (πŸ₯ˆ29 Β· ⭐ 310) - All the open source things related to the Hugging Face Hub. Apache-2 +
triton (πŸ₯ˆ28 Β· ⭐ 3.5K Β· βž•) - Development repository for the Triton language and compiler. MIT -- [GitHub](https://github.com/huggingface/huggingface_hub) (πŸ‘¨β€πŸ’» 50 Β· πŸ”€ 64 Β· πŸ“‹ 200 - 52% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/openai/triton) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 260 Β· πŸ“¦ 66 Β· πŸ“‹ 180 - 34% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/huggingface/huggingface_hub - ``` -- [PyPi](https://pypi.org/project/huggingface_hub) (πŸ“₯ 1.9M / month Β· πŸ“¦ 51 Β· ⏱️ 11.01.2022): - ``` - pip install huggingface_hub + git clone https://github.com/openai/triton ``` -- [Conda](https://anaconda.org/conda-forge/huggingface_hub) (πŸ“₯ 24K Β· ⏱️ 12.01.2022): +- [PyPi](https://pypi.org/project/triton) (πŸ“₯ 52K / month Β· πŸ“¦ 2 Β· ⏱️ 10.02.2022): ``` - conda install -c conda-forge huggingface_hub + pip install triton ```
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cortex (πŸ₯ˆ26 Β· ⭐ 7.6K) - Production infrastructure for machine learning at scale. Apache-2 +
cortex (πŸ₯ˆ27 Β· ⭐ 7.7K) - Production infrastructure for machine learning at scale. Apache-2 -- [GitHub](https://github.com/cortexlabs/cortex) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 590 Β· πŸ“‹ 1.1K - 9% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/cortexlabs/cortex) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 590 Β· πŸ“‹ 1.1K - 9% open Β· ⏱️ 06.02.2022): ``` git clone https://github.com/cortexlabs/cortex ``` -- [PyPi](https://pypi.org/project/cortex) (πŸ“₯ 920 / month Β· πŸ“¦ 1 Β· ⏱️ 10.01.2022): +- [PyPi](https://pypi.org/project/cortex) (πŸ“₯ 1.2K / month Β· πŸ“¦ 1 Β· ⏱️ 10.01.2022): ``` pip install cortex ```
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Hummingbird (πŸ₯ˆ26 Β· ⭐ 2.7K) - Hummingbird compiles trained ML models into tensor computation for.. MIT +
BentoML (πŸ₯ˆ27 Β· ⭐ 3.2K Β· πŸ“‰) - The Unified Model Serving Framework. Apache-2 + +- [GitHub](https://github.com/bentoml/BentoML) (πŸ‘¨β€πŸ’» 98 Β· πŸ”€ 370 Β· πŸ“₯ 930 Β· πŸ“‹ 530 - 8% open Β· ⏱️ 08.02.2022): + + ``` + git clone https://github.com/bentoml/BentoML + ``` +- [PyPi](https://pypi.org/project/bentoml) (πŸ“₯ 13K / month Β· πŸ“¦ 2 Β· ⏱️ 28.01.2022): + ``` + pip install bentoml + ``` +
+
Hummingbird (πŸ₯ˆ27 Β· ⭐ 2.7K) - Hummingbird compiles trained ML models into tensor computation for.. MIT -- [GitHub](https://github.com/microsoft/hummingbird) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 210 Β· πŸ“₯ 150 Β· πŸ“¦ 20 Β· πŸ“‹ 230 - 23% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/microsoft/hummingbird) (πŸ‘¨β€πŸ’» 28 Β· πŸ”€ 210 Β· πŸ“₯ 160 Β· πŸ“¦ 20 Β· πŸ“‹ 240 - 22% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/microsoft/hummingbird ``` -- [PyPi](https://pypi.org/project/hummingbird-ml) (πŸ“₯ 1.5K / month Β· ⏱️ 14.12.2021): +- [PyPi](https://pypi.org/project/hummingbird-ml) (πŸ“₯ 2K / month Β· ⏱️ 14.12.2021): ``` pip install hummingbird-ml ``` +- [Conda](https://anaconda.org/conda-forge/hummingbird-ml) (πŸ“₯ 5.2K Β· ⏱️ 14.12.2021): + ``` + conda install -c conda-forge hummingbird-ml + ```
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m2cgen (πŸ₯‰24 Β· ⭐ 2K) - Transform ML models into a native code (Java, C, Python, Go, JavaScript,.. MIT +
m2cgen (πŸ₯‰25 Β· ⭐ 2K) - Transform ML models into a native code (Java, C, Python, Go, JavaScript,.. MIT -- [GitHub](https://github.com/BayesWitnesses/m2cgen) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 170 Β· πŸ“¦ 9 Β· πŸ“‹ 87 - 41% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/BayesWitnesses/m2cgen) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 170 Β· πŸ“¦ 15 Β· πŸ“‹ 100 - 35% open Β· ⏱️ 08.02.2022): ``` git clone https://github.com/BayesWitnesses/m2cgen @@ -6752,33 +7291,22 @@ _Libraries to serialize models to files, convert between a variety of model form
pytorch2keras (πŸ₯‰18 Β· ⭐ 770) - PyTorch to Keras model convertor. MIT -- [GitHub](https://github.com/gmalivenko/pytorch2keras) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 130 Β· πŸ“¦ 26 Β· πŸ“‹ 120 - 42% open Β· ⏱️ 06.08.2021): +- [GitHub](https://github.com/gmalivenko/pytorch2keras) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 130 Β· πŸ“¦ 28 Β· πŸ“‹ 120 - 44% open Β· ⏱️ 06.08.2021): ``` git clone https://github.com/gmalivenko/pytorch2keras ``` -- [PyPi](https://pypi.org/project/pytorch2keras) (πŸ“₯ 620 / month Β· πŸ“¦ 1 Β· ⏱️ 14.05.2020): +- [PyPi](https://pypi.org/project/pytorch2keras) (πŸ“₯ 730 / month Β· πŸ“¦ 1 Β· ⏱️ 14.05.2020): ``` pip install pytorch2keras ```
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tfdeploy (πŸ₯‰16 Β· ⭐ 340 Β· πŸ’€) - Deploy tensorflow graphs for fast evaluation and export to.. BSD-3 - -- [GitHub](https://github.com/riga/tfdeploy) (πŸ‘¨β€πŸ’» 4 Β· πŸ”€ 38 Β· πŸ“‹ 34 - 32% open Β· ⏱️ 08.01.2021): - - ``` - git clone https://github.com/riga/tfdeploy - ``` -- [PyPi](https://pypi.org/project/tfdeploy) (πŸ“₯ 66 / month Β· πŸ“¦ 2 Β· ⏱️ 30.03.2017): - ``` - pip install tfdeploy - ``` -
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Show 4 hidden projects... +
Show 5 hidden projects... - mmdnn (πŸ₯‰25 Β· ⭐ 5.5K Β· πŸ’€) - MMdnn is a set of tools to help users inter-operate among different deep.. MIT -- Larq Compute Engine (πŸ₯‰20 Β· ⭐ 180) - Highly optimized inference engine for Binarized.. Apache-2 -- sklearn-porter (πŸ₯‰19 Β· ⭐ 1.1K Β· πŸ’€) - Transpile trained scikit-learn estimators to C, Java,.. MIT +- Larq Compute Engine (πŸ₯‰21 Β· ⭐ 180) - Highly optimized inference engine for Binarized.. Apache-2 +- sklearn-porter (πŸ₯‰20 Β· ⭐ 1.1K Β· πŸ’€) - Transpile trained scikit-learn estimators to C, Java,.. MIT +- tfdeploy (πŸ₯‰16 Β· ⭐ 350 Β· πŸ’€) - Deploy tensorflow graphs for fast evaluation and export to.. BSD-3 - backprop (πŸ₯‰13 Β· ⭐ 220 Β· πŸ’€) - Backprop makes it simple to use, finetune, and deploy state-of-.. Apache-2

@@ -6791,154 +7319,174 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin
shap (πŸ₯‡39 Β· ⭐ 15K) - A game theoretic approach to explain the output of any machine learning model. MIT -- [GitHub](https://github.com/slundberg/shap) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 2.2K Β· πŸ“¦ 4.2K Β· πŸ“‹ 1.8K - 68% open Β· ⏱️ 04.12.2021): +- [GitHub](https://github.com/slundberg/shap) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 2.3K Β· πŸ“¦ 4.5K Β· πŸ“‹ 1.8K - 68% open Β· ⏱️ 04.12.2021): ``` git clone https://github.com/slundberg/shap ``` -- [PyPi](https://pypi.org/project/shap) (πŸ“₯ 4.7M / month Β· πŸ“¦ 220 Β· ⏱️ 20.10.2021): +- [PyPi](https://pypi.org/project/shap) (πŸ“₯ 4.6M / month Β· πŸ“¦ 220 Β· ⏱️ 20.10.2021): ``` pip install shap ``` -- [Conda](https://anaconda.org/conda-forge/shap) (πŸ“₯ 750K Β· ⏱️ 24.10.2021): +- [Conda](https://anaconda.org/conda-forge/shap) (πŸ“₯ 840K Β· ⏱️ 23.01.2022): ``` conda install -c conda-forge shap ```
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arviz (πŸ₯‡34 Β· ⭐ 1.1K) - Exploratory analysis of Bayesian models with Python. Apache-2 +
Lime (πŸ₯‡33 Β· ⭐ 9.6K Β· πŸ’€) - Lime: Explaining the predictions of any machine learning classifier. BSD-2 -- [GitHub](https://github.com/arviz-devs/arviz) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 260 Β· πŸ“₯ 110 Β· πŸ“¦ 1.8K Β· πŸ“‹ 750 - 25% open Β· ⏱️ 07.01.2022): +- [GitHub](https://github.com/marcotcr/lime) (πŸ‘¨β€πŸ’» 61 Β· πŸ”€ 1.5K Β· πŸ“¦ 1.9K Β· πŸ“‹ 550 - 4% open Β· ⏱️ 29.07.2021): ``` - git clone https://github.com/arviz-devs/arviz + git clone https://github.com/marcotcr/lime ``` -- [PyPi](https://pypi.org/project/arviz) (πŸ“₯ 240K / month Β· πŸ“¦ 71 Β· ⏱️ 03.10.2021): +- [PyPi](https://pypi.org/project/lime) (πŸ“₯ 740K / month Β· πŸ“¦ 110 Β· ⏱️ 26.06.2020): ``` - pip install arviz + pip install lime ``` -- [Conda](https://anaconda.org/conda-forge/arviz) (πŸ“₯ 600K Β· ⏱️ 03.10.2021): +- [Conda](https://anaconda.org/conda-forge/lime) (πŸ“₯ 92K Β· ⏱️ 28.06.2020): ``` - conda install -c conda-forge arviz + conda install -c conda-forge lime ```
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Lime (πŸ₯‡32 Β· ⭐ 9.5K) - Lime: Explaining the predictions of any machine learning classifier. BSD-2 +
arviz (πŸ₯‡33 Β· ⭐ 1.2K) - Exploratory analysis of Bayesian models with Python. Apache-2 -- [GitHub](https://github.com/marcotcr/lime) (πŸ‘¨β€πŸ’» 61 Β· πŸ”€ 1.5K Β· πŸ“¦ 1.9K Β· πŸ“‹ 550 - 4% open Β· ⏱️ 29.07.2021): +- [GitHub](https://github.com/arviz-devs/arviz) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 260 Β· πŸ“₯ 110 Β· πŸ“¦ 1.9K Β· πŸ“‹ 750 - 25% open Β· ⏱️ 08.02.2022): ``` - git clone https://github.com/marcotcr/lime + git clone https://github.com/arviz-devs/arviz ``` -- [PyPi](https://pypi.org/project/lime) (πŸ“₯ 1.2M / month Β· πŸ“¦ 110 Β· ⏱️ 26.06.2020): +- [PyPi](https://pypi.org/project/arviz) (πŸ“₯ 320K / month Β· πŸ“¦ 71 Β· ⏱️ 03.10.2021): ``` - pip install lime + pip install arviz ``` -- [Conda](https://anaconda.org/conda-forge/lime) (πŸ“₯ 90K Β· ⏱️ 28.06.2020): +- [Conda](https://anaconda.org/conda-forge/arviz) (πŸ“₯ 620K Β· ⏱️ 03.10.2021): ``` - conda install -c conda-forge lime + conda install -c conda-forge arviz ```
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InterpretML (πŸ₯‡31 Β· ⭐ 4.4K) - Fit interpretable models. Explain blackbox machine learning. MIT +
InterpretML (πŸ₯‡32 Β· ⭐ 4.5K) - Fit interpretable models. Explain blackbox machine learning. MIT -- [GitHub](https://github.com/interpretml/interpret) (πŸ‘¨β€πŸ’» 28 Β· πŸ”€ 540 Β· πŸ“¦ 140 Β· πŸ“‹ 270 - 31% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/interpretml/interpret) (πŸ‘¨β€πŸ’» 28 Β· πŸ”€ 560 Β· πŸ“¦ 160 Β· πŸ“‹ 270 - 32% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/interpretml/interpret ``` -- [PyPi](https://pypi.org/project/interpret) (πŸ“₯ 53K / month Β· πŸ“¦ 8 Β· ⏱️ 23.09.2021): +- [PyPi](https://pypi.org/project/interpret) (πŸ“₯ 88K / month Β· πŸ“¦ 8 Β· ⏱️ 23.09.2021): ``` pip install interpret ```
Captum (πŸ₯‡31 Β· ⭐ 2.9K) - Model interpretability and understanding for PyTorch. BSD-3 -- [GitHub](https://github.com/pytorch/captum) (πŸ‘¨β€πŸ’» 77 Β· πŸ”€ 300 Β· πŸ“¦ 360 Β· πŸ“‹ 320 - 24% open Β· ⏱️ 14.12.2021): +- [GitHub](https://github.com/pytorch/captum) (πŸ‘¨β€πŸ’» 78 Β· πŸ”€ 300 Β· πŸ“¦ 390 Β· πŸ“‹ 330 - 23% open Β· ⏱️ 27.01.2022): ``` git clone https://github.com/pytorch/captum ``` -- [PyPi](https://pypi.org/project/captum) (πŸ“₯ 25K / month Β· πŸ“¦ 17 Β· ⏱️ 02.11.2021): +- [PyPi](https://pypi.org/project/captum) (πŸ“₯ 33K / month Β· πŸ“¦ 17 Β· ⏱️ 02.11.2021): ``` pip install captum ``` +- [Conda](https://anaconda.org/conda-forge/captum) (πŸ“₯ 180 Β· ⏱️ 27.01.2022): + ``` + conda install -c conda-forge captum + ``` +
+
Model Analysis (πŸ₯‡31 Β· ⭐ 1.1K) - Model analysis tools for TensorFlow. Apache-2 + +- [GitHub](https://github.com/tensorflow/model-analysis) (πŸ‘¨β€πŸ’» 37 Β· πŸ”€ 240 Β· πŸ“‹ 74 - 36% open Β· ⏱️ 09.02.2022): + + ``` + git clone https://github.com/tensorflow/model-analysis + ``` +- [PyPi](https://pypi.org/project/tensorflow-model-analysis) (πŸ“₯ 5.4M / month Β· πŸ“¦ 21 Β· ⏱️ 24.01.2022): + ``` + pip install tensorflow-model-analysis + ```
pyLDAvis (πŸ₯ˆ30 Β· ⭐ 1.6K Β· πŸ’€) - Python library for interactive topic model visualization... BSD-3 -- [GitHub](https://github.com/bmabey/pyLDAvis) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 320 Β· πŸ“¦ 3K Β· πŸ“‹ 160 - 52% open Β· ⏱️ 24.03.2021): +- [GitHub](https://github.com/bmabey/pyLDAvis) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 320 Β· πŸ“¦ 3.1K Β· πŸ“‹ 160 - 52% open Β· ⏱️ 24.03.2021): ``` git clone https://github.com/bmabey/pyLDAvis ``` -- [PyPi](https://pypi.org/project/pyldavis) (πŸ“₯ 470K / month Β· πŸ“¦ 130 Β· ⏱️ 24.03.2021): +- [PyPi](https://pypi.org/project/pyldavis) (πŸ“₯ 610K / month Β· πŸ“¦ 130 Β· ⏱️ 24.03.2021): ``` pip install pyldavis ``` -- [Conda](https://anaconda.org/conda-forge/pyldavis) (πŸ“₯ 33K Β· ⏱️ 24.03.2021): +- [Conda](https://anaconda.org/conda-forge/pyldavis) (πŸ“₯ 34K Β· ⏱️ 24.03.2021): ``` conda install -c conda-forge pyldavis ```
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Model Analysis (πŸ₯ˆ30 Β· ⭐ 1.1K) - Model analysis tools for TensorFlow. Apache-2 +
shapash (πŸ₯ˆ29 Β· ⭐ 1.6K) - Shapash makes Machine Learning models transparent and.. Apache-2 -- [GitHub](https://github.com/tensorflow/model-analysis) (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 240 Β· πŸ“‹ 72 - 34% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/MAIF/shapash) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 210 Β· πŸ“¦ 61 Β· πŸ“‹ 98 - 12% open Β· ⏱️ 08.02.2022): ``` - git clone https://github.com/tensorflow/model-analysis + git clone https://github.com/MAIF/shapash ``` -- [PyPi](https://pypi.org/project/tensorflow-model-analysis) (πŸ“₯ 6.5M / month Β· πŸ“¦ 21 Β· ⏱️ 02.12.2021): +- [PyPi](https://pypi.org/project/shapash) (πŸ“₯ 21K / month Β· ⏱️ 14.01.2022): ``` - pip install tensorflow-model-analysis + pip install shapash ```
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shapash (πŸ₯ˆ29 Β· ⭐ 1.5K) - Shapash makes Machine Learning models transparent and.. Apache-2 +
Alibi (πŸ₯ˆ29 Β· ⭐ 1.5K) - Algorithms for explaining machine learning models. Apache-2 -- [GitHub](https://github.com/MAIF/shapash) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 200 Β· πŸ“¦ 59 Β· πŸ“‹ 96 - 11% open Β· ⏱️ 04.01.2022): +- [GitHub](https://github.com/SeldonIO/alibi) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 180 Β· πŸ“¦ 140 Β· πŸ“‹ 260 - 41% open Β· ⏱️ 04.02.2022): ``` - git clone https://github.com/MAIF/shapash + git clone https://github.com/SeldonIO/alibi ``` -- [PyPi](https://pypi.org/project/shapash) (πŸ“₯ 13K / month Β· ⏱️ 06.12.2021): +- [PyPi](https://pypi.org/project/alibi) (πŸ“₯ 45K / month Β· πŸ“¦ 22 Β· ⏱️ 28.01.2022): ``` - pip install shapash + pip install alibi ```
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DoWhy (πŸ₯ˆ27 Β· ⭐ 3.5K) - DoWhy is a Python library for causal inference that supports explicit.. MIT +
DoWhy (πŸ₯ˆ28 Β· ⭐ 3.6K) - DoWhy is a Python library for causal inference that supports explicit.. MIT -- [GitHub](https://github.com/microsoft/dowhy) (πŸ‘¨β€πŸ’» 47 Β· πŸ”€ 540 Β· πŸ“₯ 24 Β· πŸ“¦ 80 Β· πŸ“‹ 170 - 31% open Β· ⏱️ 11.01.2022): +- [GitHub](https://github.com/microsoft/dowhy) (πŸ‘¨β€πŸ’» 48 Β· πŸ”€ 560 Β· πŸ“₯ 24 Β· πŸ“¦ 83 Β· πŸ“‹ 180 - 29% open Β· ⏱️ 06.02.2022): ``` git clone https://github.com/Microsoft/dowhy ``` -- [PyPi](https://pypi.org/project/dowhy) (πŸ“₯ 50K / month Β· πŸ“¦ 3 Β· ⏱️ 10.01.2022): +- [PyPi](https://pypi.org/project/dowhy) (πŸ“₯ 99K / month Β· πŸ“¦ 4 Β· ⏱️ 10.01.2022): ``` pip install dowhy ``` -- [Conda](https://anaconda.org/conda-forge/dowhy) (πŸ“₯ 4.2K Β· ⏱️ 28.04.2021): +- [Conda](https://anaconda.org/conda-forge/dowhy) (πŸ“₯ 4.3K Β· ⏱️ 22.01.2022): ``` conda install -c conda-forge dowhy ```
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dtreeviz (πŸ₯ˆ27 Β· ⭐ 1.9K) - A python library for decision tree visualization and model interpretation. MIT +
dtreeviz (πŸ₯ˆ28 Β· ⭐ 2K) - A python library for decision tree visualization and model interpretation. MIT -- [GitHub](https://github.com/parrt/dtreeviz) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 240 Β· πŸ“¦ 290 Β· πŸ“‹ 110 - 17% open Β· ⏱️ 03.01.2022): +- [GitHub](https://github.com/parrt/dtreeviz) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 250 Β· πŸ“¦ 300 Β· πŸ“‹ 120 - 17% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/parrt/dtreeviz ``` -- [PyPi](https://pypi.org/project/dtreeviz) (πŸ“₯ 56K / month Β· πŸ“¦ 13 Β· ⏱️ 10.11.2021): +- [PyPi](https://pypi.org/project/dtreeviz) (πŸ“₯ 75K / month Β· πŸ“¦ 14 Β· ⏱️ 09.02.2022): ``` pip install dtreeviz ``` +- [Conda](https://anaconda.org/conda-forge/dtreeviz) (πŸ“₯ 7.2K Β· ⏱️ 03.12.2021): + ``` + conda install -c conda-forge dtreeviz + ```
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Alibi (πŸ₯ˆ27 Β· ⭐ 1.5K) - Algorithms for explaining machine learning models. Apache-2 +
Lucid (πŸ₯ˆ26 Β· ⭐ 4.4K Β· πŸ’€) - A collection of infrastructure and tools for research in.. Apache-2 -- [GitHub](https://github.com/SeldonIO/alibi) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 160 Β· πŸ“¦ 130 Β· πŸ“‹ 250 - 41% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/tensorflow/lucid) (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 590 Β· πŸ“¦ 600 Β· πŸ“‹ 170 - 41% open Β· ⏱️ 19.03.2021): ``` - git clone https://github.com/SeldonIO/alibi + git clone https://github.com/tensorflow/lucid ``` -- [PyPi](https://pypi.org/project/alibi) (πŸ“₯ 35K / month Β· πŸ“¦ 17 Β· ⏱️ 18.11.2021): +- [PyPi](https://pypi.org/project/lucid) (πŸ“₯ 1.5K / month Β· πŸ“¦ 6 Β· ⏱️ 19.03.2021): ``` - pip install alibi + pip install lucid ```
yellowbrick (πŸ₯ˆ26 Β· ⭐ 3.5K) - Visual analysis and diagnostic tools to facilitate machine.. Apache-2 @@ -6948,344 +7496,364 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin ``` git clone https://github.com/DistrictDataLabs/yellowbrick ``` -- [PyPi](https://pypi.org/project/yellowbrick) (πŸ“₯ 260K / month Β· πŸ“¦ 47 Β· ⏱️ 13.02.2021): +- [PyPi](https://pypi.org/project/yellowbrick) (πŸ“₯ 350K / month Β· πŸ“¦ 47 Β· ⏱️ 13.02.2021): ``` pip install yellowbrick ``` +- [Conda](https://anaconda.org/conda-forge/yellowbrick) (πŸ“₯ 20K Β· ⏱️ 06.05.2021): + ``` + conda install -c conda-forge yellowbrick + ```
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Lucid (πŸ₯ˆ25 Β· ⭐ 4.4K Β· πŸ’€) - A collection of infrastructure and tools for research in.. Apache-2 +
fairlearn (πŸ₯ˆ26 Β· ⭐ 1.2K) - A Python package to assess and improve fairness of machine.. MIT -- [GitHub](https://github.com/tensorflow/lucid) (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 590 Β· πŸ“¦ 600 Β· πŸ“‹ 170 - 41% open Β· ⏱️ 19.03.2021): +- [GitHub](https://github.com/fairlearn/fairlearn) (πŸ‘¨β€πŸ’» 63 Β· πŸ”€ 280 Β· πŸ“‹ 330 - 40% open Β· ⏱️ 31.01.2022): ``` - git clone https://github.com/tensorflow/lucid + git clone https://github.com/fairlearn/fairlearn ``` -- [PyPi](https://pypi.org/project/lucid) (πŸ“₯ 930 / month Β· πŸ“¦ 6 Β· ⏱️ 19.03.2021): +- [PyPi](https://pypi.org/project/fairlearn) (πŸ“₯ 56K / month Β· πŸ“¦ 9 Β· ⏱️ 07.07.2021): ``` - pip install lucid + pip install fairlearn + ``` +- [Conda](https://anaconda.org/conda-forge/fairlearn) (πŸ“₯ 17K Β· ⏱️ 07.07.2021): + ``` + conda install -c conda-forge fairlearn + ``` +
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Fairness 360 (πŸ₯ˆ25 Β· ⭐ 1.6K) - A comprehensive set of fairness metrics for datasets and.. Apache-2 + +- [GitHub](https://github.com/Trusted-AI/AIF360) (πŸ‘¨β€πŸ’» 48 Β· πŸ”€ 510 Β· πŸ“¦ 140 Β· πŸ“‹ 120 - 51% open Β· ⏱️ 21.01.2022): + + ``` + git clone https://github.com/Trusted-AI/AIF360 + ``` +- [PyPi](https://pypi.org/project/aif360) (πŸ“₯ 7.9K / month Β· πŸ“¦ 8 Β· ⏱️ 04.03.2021): + ``` + pip install aif360 + ``` +- [Conda](https://anaconda.org/conda-forge/aif360) (πŸ“₯ 1.5K Β· ⏱️ 29.09.2021): + ``` + conda install -c conda-forge aif360 ```
checklist (πŸ₯ˆ25 Β· ⭐ 1.6K) - Beyond Accuracy: Behavioral Testing of NLP models with CheckList. MIT -- [GitHub](https://github.com/marcotcr/checklist) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 150 Β· πŸ“¦ 67 Β· πŸ“‹ 91 - 13% open Β· ⏱️ 28.09.2021): +- [GitHub](https://github.com/marcotcr/checklist) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 150 Β· πŸ“¦ 80 Β· πŸ“‹ 92 - 13% open Β· ⏱️ 28.09.2021): ``` git clone https://github.com/marcotcr/checklist ``` -- [PyPi](https://pypi.org/project/checklist) (πŸ“₯ 22K / month Β· πŸ“¦ 3 Β· ⏱️ 24.05.2021): +- [PyPi](https://pypi.org/project/checklist) (πŸ“₯ 18K / month Β· πŸ“¦ 3 Β· ⏱️ 24.05.2021): ``` pip install checklist ``` +- [Conda](https://anaconda.org/conda-forge/checklist) (πŸ“₯ 2.3K Β· ⏱️ 15.07.2021): + ``` + conda install -c conda-forge checklist + ```
CausalNex (πŸ₯ˆ25 Β· ⭐ 1.4K) - A Python library that helps data scientists to infer.. Apache-2 -- [GitHub](https://github.com/quantumblacklabs/causalnex) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 150 Β· πŸ“¦ 36 Β· πŸ“‹ 100 - 14% open Β· ⏱️ 11.11.2021): +- [GitHub](https://github.com/quantumblacklabs/causalnex) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 160 Β· πŸ“¦ 38 Β· πŸ“‹ 100 - 14% open Β· ⏱️ 11.11.2021): ``` git clone https://github.com/quantumblacklabs/causalnex ``` -- [PyPi](https://pypi.org/project/causalnex) (πŸ“₯ 4.8K / month Β· πŸ“¦ 2 Β· ⏱️ 11.11.2021): +- [PyPi](https://pypi.org/project/causalnex) (πŸ“₯ 2.2K / month Β· πŸ“¦ 2 Β· ⏱️ 11.11.2021): ``` pip install causalnex ```
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fairlearn (πŸ₯ˆ25 Β· ⭐ 1.2K) - A Python package to assess and improve fairness of machine.. MIT +
explainerdashboard (πŸ₯ˆ25 Β· ⭐ 1.1K) - Quickly build Explainable AI dashboards that show the inner.. MIT -- [GitHub](https://github.com/fairlearn/fairlearn) (πŸ‘¨β€πŸ’» 61 Β· πŸ”€ 270 Β· πŸ“‹ 330 - 40% open Β· ⏱️ 15.12.2021): +- [GitHub](https://github.com/oegedijk/explainerdashboard) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 130 Β· πŸ“¦ 58 Β· πŸ“‹ 140 - 8% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/fairlearn/fairlearn + git clone https://github.com/oegedijk/explainerdashboard ``` -- [PyPi](https://pypi.org/project/fairlearn) (πŸ“₯ 24K / month Β· πŸ“¦ 9 Β· ⏱️ 07.07.2021): +- [PyPi](https://pypi.org/project/explainerdashboard) (πŸ“₯ 16K / month Β· πŸ“¦ 2 Β· ⏱️ 10.02.2022): ``` - pip install fairlearn + pip install explainerdashboard ``` -- [Conda](https://anaconda.org/conda-forge/fairlearn) (πŸ“₯ 17K Β· ⏱️ 07.07.2021): +- [Conda](https://anaconda.org/conda-forge/explainerdashboard) (πŸ“₯ 14K Β· ⏱️ 04.08.2021): ``` - conda install -c conda-forge fairlearn + conda install -c conda-forge explainerdashboard ```
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responsible-ai-widgets (πŸ₯ˆ25 Β· ⭐ 380) - This project provides responsible AI user interfaces.. MIT +
responsible-ai-widgets (πŸ₯ˆ25 Β· ⭐ 420) - This project provides responsible AI user interfaces.. MIT -- [GitHub](https://github.com/microsoft/responsible-ai-toolbox) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 91 Β· πŸ“¦ 18 Β· πŸ“‹ 220 - 21% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/microsoft/responsible-ai-toolbox) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 98 Β· πŸ“¦ 20 Β· πŸ“‹ 240 - 26% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/microsoft/responsible-ai-widgets + git clone https://github.com/microsoft/responsible-ai-toolbox ``` -- [PyPi](https://pypi.org/project/raiwidgets) (πŸ“₯ 3.7K / month Β· πŸ“¦ 2 Β· ⏱️ 05.01.2022): +- [PyPi](https://pypi.org/project/raiwidgets) (πŸ“₯ 5.8K / month Β· πŸ“¦ 2 Β· ⏱️ 05.01.2022): ``` pip install raiwidgets ```
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LIT (πŸ₯‰24 Β· ⭐ 2.7K) - The Language Interpretability Tool: Interactively analyze NLP models for.. Apache-2 +
LIT (πŸ₯‰24 Β· ⭐ 2.8K) - The Language Interpretability Tool: Interactively analyze NLP models for.. Apache-2 -- [GitHub](https://github.com/PAIR-code/lit) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 270 Β· πŸ“¦ 7 Β· πŸ“‹ 130 - 50% open Β· ⏱️ 21.12.2021): +- [GitHub](https://github.com/PAIR-code/lit) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 280 Β· πŸ“¦ 7 Β· πŸ“‹ 130 - 50% open Β· ⏱️ 21.12.2021): ``` git clone https://github.com/PAIR-code/lit ``` -- [PyPi](https://pypi.org/project/lit-nlp) (πŸ“₯ 650 / month Β· ⏱️ 21.12.2021): +- [PyPi](https://pypi.org/project/lit-nlp) (πŸ“₯ 1.1K / month Β· ⏱️ 21.12.2021): ``` pip install lit-nlp ``` -
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Fairness 360 (πŸ₯‰24 Β· ⭐ 1.6K) - A comprehensive set of fairness metrics for datasets and.. Apache-2 - -- [GitHub](https://github.com/Trusted-AI/AIF360) (πŸ‘¨β€πŸ’» 46 Β· πŸ”€ 500 Β· πŸ“¦ 130 Β· πŸ“‹ 120 - 50% open Β· ⏱️ 18.11.2021): - - ``` - git clone https://github.com/Trusted-AI/AIF360 - ``` -- [PyPi](https://pypi.org/project/aif360) (πŸ“₯ 5.5K / month Β· πŸ“¦ 8 Β· ⏱️ 04.03.2021): +- [Conda](https://anaconda.org/conda-forge/lit-nlp) (πŸ“₯ 32K Β· ⏱️ 09.11.2021): ``` - pip install aif360 + conda install -c conda-forge lit-nlp ```
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Explainability 360 (πŸ₯‰23 Β· ⭐ 1K) - Interpretability and explainability of data and machine.. Apache-2 +
Explainability 360 (πŸ₯‰23 Β· ⭐ 1.1K) - Interpretability and explainability of data and.. Apache-2 -- [GitHub](https://github.com/Trusted-AI/AIX360) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 210 Β· πŸ“¦ 37 Β· πŸ“‹ 63 - 60% open Β· ⏱️ 12.10.2021): +- [GitHub](https://github.com/Trusted-AI/AIX360) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 220 Β· πŸ“¦ 37 Β· πŸ“‹ 63 - 60% open Β· ⏱️ 12.10.2021): ``` git clone https://github.com/Trusted-AI/AIX360 ``` -- [PyPi](https://pypi.org/project/aix360) (πŸ“₯ 1.2K / month Β· πŸ“¦ 1 Β· ⏱️ 28.10.2020): +- [PyPi](https://pypi.org/project/aix360) (πŸ“₯ 1.5K / month Β· πŸ“¦ 1 Β· ⏱️ 28.10.2020): ``` pip install aix360 ```
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explainerdashboard (πŸ₯‰23 Β· ⭐ 960) - Quickly build Explainable AI dashboards that show the inner.. MIT +
keract (πŸ₯‰23 Β· ⭐ 960) - Layers Outputs and Gradients in Keras. Made easy. MIT -- [GitHub](https://github.com/oegedijk/explainerdashboard) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 120 Β· πŸ“¦ 51 Β· πŸ“‹ 150 - 11% open Β· ⏱️ 24.12.2021): +- [GitHub](https://github.com/philipperemy/keract) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 180 Β· πŸ“¦ 110 Β· πŸ“‹ 84 - 3% open Β· ⏱️ 24.01.2022): ``` - git clone https://github.com/oegedijk/explainerdashboard + git clone https://github.com/philipperemy/keract ``` -- [PyPi](https://pypi.org/project/explainerdashboard) (πŸ“₯ 5.2K / month Β· ⏱️ 24.10.2021): +- [PyPi](https://pypi.org/project/keract) (πŸ“₯ 1.2K / month Β· πŸ“¦ 5 Β· ⏱️ 19.06.2021): ``` - pip install explainerdashboard + pip install keract ```
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tf-explain (πŸ₯‰23 Β· ⭐ 890) - Interpretability Methods for tf.keras models with Tensorflow 2.x. MIT +
ecco (πŸ₯‰22 Β· ⭐ 1.3K) - Explain, analyze, and visualize NLP language models. Ecco creates.. BSD-3 -- [GitHub](https://github.com/sicara/tf-explain) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 91 Β· πŸ“¦ 95 Β· πŸ“‹ 89 - 43% open Β· ⏱️ 30.11.2021): +- [GitHub](https://github.com/jalammar/ecco) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 82 Β· πŸ“₯ 12 Β· πŸ“¦ 3 Β· πŸ“‹ 34 - 38% open Β· ⏱️ 18.01.2022): ``` - git clone https://github.com/sicara/tf-explain + git clone https://github.com/jalammar/ecco ``` -- [PyPi](https://pypi.org/project/tf-explain) (πŸ“₯ 1.4K / month Β· πŸ“¦ 6 Β· ⏱️ 18.11.2021): +- [PyPi](https://pypi.org/project/ecco) (πŸ“₯ 440 / month Β· πŸ“¦ 1 Β· ⏱️ 09.01.2022): ``` - pip install tf-explain + pip install ecco + ``` +- [Conda](https://anaconda.org/conda-forge/ecco) (πŸ“₯ 130 Β· ⏱️ 10.01.2022): + ``` + conda install -c conda-forge ecco ```
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keract (πŸ₯‰22 Β· ⭐ 960) - Layers Outputs and Gradients in Keras. Made easy. MIT +
tf-explain (πŸ₯‰22 Β· ⭐ 900) - Interpretability Methods for tf.keras models with Tensorflow 2.x. MIT -- [GitHub](https://github.com/philipperemy/keract) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 180 Β· πŸ“¦ 110 Β· πŸ“‹ 84 - 3% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/sicara/tf-explain) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 91 Β· πŸ“¦ 98 Β· πŸ“‹ 90 - 43% open Β· ⏱️ 30.11.2021): ``` - git clone https://github.com/philipperemy/keract + git clone https://github.com/sicara/tf-explain ``` -- [PyPi](https://pypi.org/project/keract) (πŸ“₯ 1.3K / month Β· πŸ“¦ 5 Β· ⏱️ 19.06.2021): +- [PyPi](https://pypi.org/project/tf-explain) (πŸ“₯ 2.3K / month Β· πŸ“¦ 6 Β· ⏱️ 18.11.2021): ``` - pip install keract + pip install tf-explain ```
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DiCE (πŸ₯‰22 Β· ⭐ 750) - Generate Diverse Counterfactual Explanations for any machine.. MIT +
DiCE (πŸ₯‰22 Β· ⭐ 770) - Generate Diverse Counterfactual Explanations for any machine.. MIT -- [GitHub](https://github.com/interpretml/DiCE) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 100 Β· πŸ“‹ 99 - 46% open Β· ⏱️ 07.01.2022): +- [GitHub](https://github.com/interpretml/DiCE) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 100 Β· πŸ“‹ 100 - 46% open Β· ⏱️ 08.02.2022): ``` git clone https://github.com/interpretml/DiCE ``` -- [PyPi](https://pypi.org/project/dice-ml) (πŸ“₯ 16K / month Β· πŸ“¦ 3 Β· ⏱️ 27.09.2021): +- [PyPi](https://pypi.org/project/dice-ml) (πŸ“₯ 34K / month Β· πŸ“¦ 3 Β· ⏱️ 27.09.2021): ``` pip install dice-ml ```
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TreeInterpreter (πŸ₯‰22 Β· ⭐ 690 Β· πŸ’€) - Package for interpreting scikit-learns decision tree.. BSD-3 +
TreeInterpreter (πŸ₯‰22 Β· ⭐ 700 Β· πŸ’€) - Package for interpreting scikit-learns decision tree.. BSD-3 -- [GitHub](https://github.com/andosa/treeinterpreter) (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 130 Β· πŸ“¦ 190 Β· πŸ“‹ 28 - 85% open Β· ⏱️ 28.02.2021): +- [GitHub](https://github.com/andosa/treeinterpreter) (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 130 Β· πŸ“¦ 200 Β· πŸ“‹ 28 - 85% open Β· ⏱️ 28.02.2021): ``` git clone https://github.com/andosa/treeinterpreter ``` -- [PyPi](https://pypi.org/project/treeinterpreter) (πŸ“₯ 160K / month Β· πŸ“¦ 10 Β· ⏱️ 10.01.2021): +- [PyPi](https://pypi.org/project/treeinterpreter) (πŸ“₯ 210K / month Β· πŸ“¦ 10 Β· ⏱️ 10.01.2021): ``` pip install treeinterpreter ``` +- [Conda](https://anaconda.org/conda-forge/treeinterpreter) (πŸ“₯ 970 Β· ⏱️ 03.10.2020): + ``` + conda install -c conda-forge treeinterpreter + ```
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What-If Tool (πŸ₯‰22 Β· ⭐ 620) - Source code/webpage/demos for the What-If Tool. Apache-2 +
What-If Tool (πŸ₯‰22 Β· ⭐ 640) - Source code/webpage/demos for the What-If Tool. Apache-2 - [GitHub](https://github.com/PAIR-code/what-if-tool) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 120 Β· πŸ“‹ 100 - 54% open Β· ⏱️ 05.01.2022): ``` git clone https://github.com/PAIR-code/what-if-tool ``` -- [PyPi](https://pypi.org/project/witwidget) (πŸ“₯ 6.2K / month Β· πŸ“¦ 3 Β· ⏱️ 12.10.2021): +- [PyPi](https://pypi.org/project/witwidget) (πŸ“₯ 7.5K / month Β· πŸ“¦ 3 Β· ⏱️ 12.10.2021): ``` pip install witwidget ``` -- [npm](https://www.npmjs.com/package/wit-widget) (πŸ“₯ 3.2K / month Β· ⏱️ 12.10.2021): - ``` - npm install wit-widget - ``` -
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random-forest-importances (πŸ₯‰22 Β· ⭐ 490 Β· πŸ’€) - Code to compute permutation and drop-column.. MIT - -- [GitHub](https://github.com/parrt/random-forest-importances) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 110 Β· πŸ“¦ 88 Β· πŸ“‹ 34 - 17% open Β· ⏱️ 30.01.2021): - - ``` - git clone https://github.com/parrt/random-forest-importances +- [Conda](https://anaconda.org/conda-forge/tensorboard-plugin-wit) (πŸ“₯ 850K Β· ⏱️ 06.01.2022): ``` -- [PyPi](https://pypi.org/project/rfpimp) (πŸ“₯ 13K / month Β· πŸ“¦ 5 Β· ⏱️ 28.01.2021): + conda install -c conda-forge tensorboard-plugin-wit ``` - pip install rfpimp +- [npm](https://www.npmjs.com/package/wit-widget) (πŸ“₯ 3.7K / month Β· ⏱️ 12.10.2021): ``` -
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ecco (πŸ₯‰21 Β· ⭐ 1.3K) - Explain, analyze, and visualize NLP language models. Ecco creates.. BSD-3 - -- [GitHub](https://github.com/jalammar/ecco) (πŸ‘¨β€πŸ’» 9 Β· πŸ”€ 79 Β· πŸ“₯ 2 Β· πŸ“¦ 3 Β· πŸ“‹ 28 - 28% open Β· ⏱️ 12.01.2022): - - ``` - git clone https://github.com/jalammar/ecco - ``` -- [PyPi](https://pypi.org/project/ecco) (πŸ“₯ 560 / month Β· πŸ“¦ 1 Β· ⏱️ 09.01.2022): - ``` - pip install ecco + npm install wit-widget ```
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imodels (πŸ₯‰21 Β· ⭐ 430) - Interpretable ML package for concise, transparent, and accurate predictive.. MIT +
imodels (πŸ₯‰22 Β· ⭐ 490) - Interpretable ML package for concise, transparent, and accurate predictive.. MIT -- [GitHub](https://github.com/csinva/imodels) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 43 Β· πŸ“¦ 10 Β· πŸ“‹ 18 - 22% open Β· ⏱️ 09.01.2022): +- [GitHub](https://github.com/csinva/imodels) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 49 Β· πŸ“¦ 12 Β· πŸ“‹ 26 - 23% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/csinva/imodels ``` -- [PyPi](https://pypi.org/project/imodels) (πŸ“₯ 640 / month Β· ⏱️ 07.12.2021): +- [PyPi](https://pypi.org/project/imodels) (πŸ“₯ 1.3K / month Β· ⏱️ 29.01.2022): ``` pip install imodels ```
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iNNvestigate (πŸ₯‰20 Β· ⭐ 940) - A toolbox to iNNvestigate neural networks predictions!. BSD-2 +
iNNvestigate (πŸ₯‰20 Β· ⭐ 950) - A toolbox to iNNvestigate neural networks predictions!. BSD-2 - [GitHub](https://github.com/albermax/innvestigate) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 200 Β· πŸ“‹ 230 - 30% open Β· ⏱️ 03.08.2021): ``` git clone https://github.com/albermax/innvestigate ``` -- [PyPi](https://pypi.org/project/innvestigate) (πŸ“₯ 370 / month Β· πŸ“¦ 1 Β· ⏱️ 14.11.2020): +- [PyPi](https://pypi.org/project/innvestigate) (πŸ“₯ 470 / month Β· πŸ“¦ 1 Β· ⏱️ 14.11.2020): ``` pip install innvestigate ```
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deeplift (πŸ₯‰20 Β· ⭐ 600) - Public facing deeplift repo. MIT +
deeplift (πŸ₯‰20 Β· ⭐ 610) - Public facing deeplift repo. MIT -- [GitHub](https://github.com/kundajelab/deeplift) (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 130 Β· πŸ“¦ 53 Β· πŸ“‹ 82 - 41% open Β· ⏱️ 11.11.2021): +- [GitHub](https://github.com/kundajelab/deeplift) (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 140 Β· πŸ“¦ 54 Β· πŸ“‹ 82 - 41% open Β· ⏱️ 11.11.2021): ``` git clone https://github.com/kundajelab/deeplift ``` -- [PyPi](https://pypi.org/project/deeplift) (πŸ“₯ 400 / month Β· πŸ“¦ 4 Β· ⏱️ 11.11.2020): +- [PyPi](https://pypi.org/project/deeplift) (πŸ“₯ 530 / month Β· πŸ“¦ 4 Β· ⏱️ 11.11.2020): ``` pip install deeplift ```
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aequitas (πŸ₯‰20 Β· ⭐ 450 Β· πŸ’€) - Bias and Fairness Audit Toolkit. MIT +
aequitas (πŸ₯‰20 Β· ⭐ 460 Β· πŸ’€) - Bias and Fairness Audit Toolkit. MIT -- [GitHub](https://github.com/dssg/aequitas) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 85 Β· πŸ“¦ 87 Β· πŸ“‹ 58 - 63% open Β· ⏱️ 27.05.2021): +- [GitHub](https://github.com/dssg/aequitas) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 85 Β· πŸ“¦ 89 Β· πŸ“‹ 58 - 63% open Β· ⏱️ 27.05.2021): ``` git clone https://github.com/dssg/aequitas ``` -- [PyPi](https://pypi.org/project/aequitas) (πŸ“₯ 740 / month Β· πŸ“¦ 6 Β· ⏱️ 16.12.2020): +- [PyPi](https://pypi.org/project/aequitas) (πŸ“₯ 760 / month Β· πŸ“¦ 6 Β· ⏱️ 16.12.2020): ``` pip install aequitas ```
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sklearn-evaluation (πŸ₯‰20 Β· ⭐ 320) - Machine learning model evaluation made easy: plots,.. MIT +
tcav (πŸ₯‰19 Β· ⭐ 510) - Code for the TCAV ML interpretability project. Apache-2 -- [GitHub](https://github.com/edublancas/sklearn-evaluation) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 28 Β· πŸ“¦ 38 Β· πŸ“‹ 37 - 21% open Β· ⏱️ 17.10.2021): +- [GitHub](https://github.com/tensorflow/tcav) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 120 Β· πŸ“¦ 11 Β· πŸ“‹ 60 - 11% open Β· ⏱️ 16.09.2021): ``` - git clone https://github.com/edublancas/sklearn-evaluation + git clone https://github.com/tensorflow/tcav ``` -- [PyPi](https://pypi.org/project/sklearn-evaluation) (πŸ“₯ 670 / month Β· πŸ“¦ 2 Β· ⏱️ 17.10.2021): +- [PyPi](https://pypi.org/project/tcav) (πŸ“₯ 120 / month Β· πŸ“¦ 3 Β· ⏱️ 23.02.2021): ``` - pip install sklearn-evaluation + pip install tcav ```
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tcav (πŸ₯‰19 Β· ⭐ 500) - Code for the TCAV ML interpretability project. Apache-2 +
sklearn-evaluation (πŸ₯‰19 Β· ⭐ 320) - Machine learning model evaluation made easy: plots,.. MIT -- [GitHub](https://github.com/tensorflow/tcav) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 120 Β· πŸ“¦ 11 Β· πŸ“‹ 59 - 10% open Β· ⏱️ 16.09.2021): +- [GitHub](https://github.com/edublancas/sklearn-evaluation) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 28 Β· πŸ“¦ 38 Β· πŸ“‹ 37 - 21% open Β· ⏱️ 17.10.2021): ``` - git clone https://github.com/tensorflow/tcav + git clone https://github.com/edublancas/sklearn-evaluation ``` -- [PyPi](https://pypi.org/project/tcav) (πŸ“₯ 97 / month Β· πŸ“¦ 3 Β· ⏱️ 23.02.2021): +- [PyPi](https://pypi.org/project/sklearn-evaluation) (πŸ“₯ 1K / month Β· πŸ“¦ 2 Β· ⏱️ 17.10.2021): ``` - pip install tcav + pip install sklearn-evaluation ```
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XAI (πŸ₯‰18 Β· ⭐ 760) - XAI - An eXplainability toolbox for machine learning. MIT +
XAI (πŸ₯‰18 Β· ⭐ 770) - XAI - An eXplainability toolbox for machine learning. MIT -- [GitHub](https://github.com/EthicalML/xai) (πŸ‘¨β€πŸ’» 3 Β· πŸ”€ 120 Β· πŸ“¦ 11 Β· πŸ“‹ 8 - 12% open Β· ⏱️ 30.10.2021): +- [GitHub](https://github.com/EthicalML/xai) (πŸ‘¨β€πŸ’» 3 Β· πŸ”€ 120 Β· πŸ“¦ 12 Β· πŸ“‹ 9 - 22% open Β· ⏱️ 30.10.2021): ``` git clone https://github.com/EthicalML/xai ``` -- [PyPi](https://pypi.org/project/xai) (πŸ“₯ 330 / month Β· πŸ“¦ 6 Β· ⏱️ 30.10.2021): +- [PyPi](https://pypi.org/project/xai) (πŸ“₯ 240 / month Β· πŸ“¦ 6 Β· ⏱️ 30.10.2021): ``` pip install xai ```
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Anchor (πŸ₯‰16 Β· ⭐ 680) - Code for High-Precision Model-Agnostic Explanations paper. BSD-2 +
LOFO (πŸ₯‰16 Β· ⭐ 440) - Leave One Feature Out Importance. MIT -- [GitHub](https://github.com/marcotcr/anchor) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 93 Β· πŸ“‹ 69 - 26% open Β· ⏱️ 17.11.2021): +- [GitHub](https://github.com/aerdem4/lofo-importance) (πŸ‘¨β€πŸ’» 3 Β· πŸ”€ 52 Β· πŸ“¦ 7 Β· πŸ“‹ 18 - 27% open Β· ⏱️ 04.10.2021): ``` - git clone https://github.com/marcotcr/anchor + git clone https://github.com/aerdem4/lofo-importance ``` -- [PyPi](https://pypi.org/project/anchor_exp) (πŸ“₯ 3.2K / month Β· ⏱️ 26.06.2020): +- [PyPi](https://pypi.org/project/lofo-importance) (πŸ“₯ 240 / month Β· ⏱️ 04.10.2021): ``` - pip install anchor_exp + pip install lofo-importance ```
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LOFO (πŸ₯‰16 Β· ⭐ 420) - Leave One Feature Out Importance. MIT +
Anchor (πŸ₯‰15 Β· ⭐ 680) - Code for High-Precision Model-Agnostic Explanations paper. BSD-2 -- [GitHub](https://github.com/aerdem4/lofo-importance) (πŸ‘¨β€πŸ’» 3 Β· πŸ”€ 52 Β· πŸ“¦ 6 Β· πŸ“‹ 17 - 23% open Β· ⏱️ 04.10.2021): +- [GitHub](https://github.com/marcotcr/anchor) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 95 Β· πŸ“‹ 69 - 26% open Β· ⏱️ 17.11.2021): ``` - git clone https://github.com/aerdem4/lofo-importance + git clone https://github.com/marcotcr/anchor ``` -- [PyPi](https://pypi.org/project/lofo-importance) (πŸ“₯ 200 / month Β· ⏱️ 04.10.2021): +- [PyPi](https://pypi.org/project/anchor_exp) (πŸ“₯ 1.8K / month Β· ⏱️ 26.06.2020): ``` - pip install lofo-importance + pip install anchor_exp ```
FlashTorch (πŸ₯‰15 Β· ⭐ 640 Β· πŸ’€) - Visualization toolkit for neural networks in PyTorch! Demo --. MIT -- [GitHub](https://github.com/MisaOgura/flashtorch) (πŸ‘¨β€πŸ’» 2 Β· πŸ”€ 76 Β· πŸ“¦ 9 Β· πŸ“‹ 32 - 31% open Β· ⏱️ 27.04.2021): +- [GitHub](https://github.com/MisaOgura/flashtorch) (πŸ‘¨β€πŸ’» 2 Β· πŸ”€ 80 Β· πŸ“¦ 9 Β· πŸ“‹ 32 - 31% open Β· ⏱️ 27.04.2021): ``` git clone https://github.com/MisaOgura/flashtorch ``` -- [PyPi](https://pypi.org/project/flashtorch) (πŸ“₯ 280 / month Β· ⏱️ 29.05.2020): +- [PyPi](https://pypi.org/project/flashtorch) (πŸ“₯ 480 / month Β· ⏱️ 29.05.2020): ``` pip install flashtorch ```
+
interpret-text (πŸ₯‰15 Β· ⭐ 300) - A library that incorporates state-of-the-art explainers for.. MIT + +- [GitHub](https://github.com/interpretml/interpret-text) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 54 Β· πŸ“‹ 74 - 78% open Β· ⏱️ 06.12.2021): + + ``` + git clone https://github.com/interpretml/interpret-text + ``` +- [PyPi](https://pypi.org/project/interpret-text) (πŸ“₯ 91 / month Β· ⏱️ 07.12.2021): + ``` + pip install interpret-text + ``` +
Show 12 hidden projects... - eli5 (πŸ₯ˆ27 Β· ⭐ 2.5K Β· πŸ’€) - A library for debugging/inspecting machine learning classifiers and.. MIT +- keras-vis (πŸ₯ˆ26 Β· ⭐ 2.9K Β· πŸ’€) - Neural network visualization toolkit for keras. MIT - scikit-plot (πŸ₯ˆ26 Β· ⭐ 2.2K Β· πŸ’€) - An intuitive library to add plotting functionality to.. MIT -- keras-vis (πŸ₯ˆ25 Β· ⭐ 2.9K Β· πŸ’€) - Neural network visualization toolkit for keras. MIT -- DALEX (πŸ₯‰22 Β· ⭐ 980) - moDel Agnostic Language for Exploration and eXplanation. ❗️GPL-3.0 -- Skater (πŸ₯‰21 Β· ⭐ 1K Β· πŸ’€) - Python Library for Model Interpretation/Explanations. ❗️UPL-1.0 +- DALEX (πŸ₯‰22 Β· ⭐ 1K) - moDel Agnostic Language for Exploration and eXplanation. ❗️GPL-3.0 +- random-forest-importances (πŸ₯‰22 Β· ⭐ 490 Β· πŸ’€) - Code to compute permutation and drop-column.. MIT +- Skater (πŸ₯‰20 Β· ⭐ 1K Β· πŸ’€) - Python Library for Model Interpretation/Explanations. ❗️UPL-1.0 - model-card-toolkit (πŸ₯‰18 Β· ⭐ 250) - a tool that leverages rich metadata and lineage.. Apache-2 - fairness-indicators (πŸ₯‰18 Β· ⭐ 240) - Tensorflows Fairness Evaluation and Visualization.. Apache-2 -- interpret-text (πŸ₯‰15 Β· ⭐ 290) - A library that incorporates state-of-the-art explainers for.. MIT -- ExplainX.ai (πŸ₯‰15 Β· ⭐ 270 Β· πŸ’€) - Explainable AI framework for data scientists. Explain & debug any.. MIT -- Attribution Priors (πŸ₯‰12 Β· ⭐ 91 Β· πŸ’€) - Tools for training explainable models using.. MIT -- contextual-ai (πŸ₯‰12 Β· ⭐ 77) - Contextual AI adds explainability to different stages of.. Apache-2 +- ExplainX.ai (πŸ₯‰15 Β· ⭐ 290 Β· πŸ’€) - Explainable AI framework for data scientists. Explain & debug any.. MIT +- Attribution Priors (πŸ₯‰12 Β· ⭐ 93 Β· πŸ’€) - Tools for training explainable models using.. MIT +- contextual-ai (πŸ₯‰12 Β· ⭐ 78) - Contextual AI adds explainability to different stages of.. Apache-2 - bias-detector (πŸ₯‰12 Β· ⭐ 37) - Bias Detector is a python package for detecting bias in machine.. MIT

@@ -7296,116 +7864,124 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarity Search._ -πŸ”— ANN Benchmarks ( ⭐ 2.7K) - Benchmarks of approximate nearest neighbor libraries in Python. +πŸ”— ANN Benchmarks ( ⭐ 2.8K) - Benchmarks of approximate nearest neighbor libraries in Python. -
Milvus (πŸ₯‡38 Β· ⭐ 9.2K) - An open-source vector database for embedding similarity search and AI.. Apache-2 +
Milvus (πŸ₯‡39 Β· ⭐ 9.4K) - An open-source vector database for scalable similarity search and AI.. Apache-2 -- [GitHub](https://github.com/milvus-io/milvus) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 1.4K Β· πŸ“₯ 6.3K Β· πŸ“‹ 4.3K - 5% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/milvus-io/milvus) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 1.3K Β· πŸ“₯ 6.8K Β· πŸ“‹ 4.5K - 5% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/milvus-io/milvus ``` -- [PyPi](https://pypi.org/project/pymilvus) (πŸ“₯ 24K / month Β· πŸ“¦ 15 Β· ⏱️ 31.12.2021): +- [PyPi](https://pypi.org/project/pymilvus) (πŸ“₯ 32K / month Β· πŸ“¦ 15 Β· ⏱️ 25.01.2022): ``` pip install pymilvus ``` -- [Docker Hub](https://hub.docker.com/r/milvusdb/milvus) (πŸ“₯ 720K Β· ⭐ 17 Β· ⏱️ 31.12.2021): +- [Docker Hub](https://hub.docker.com/r/milvusdb/milvus) (πŸ“₯ 800K Β· ⭐ 18 Β· ⏱️ 25.01.2022): ``` docker pull milvusdb/milvus ```
-
Faiss (πŸ₯‡34 Β· ⭐ 16K Β· πŸ“ˆ) - A library for efficient similarity search and clustering of dense vectors. MIT +
Faiss (πŸ₯‡34 Β· ⭐ 16K) - A library for efficient similarity search and clustering of dense vectors. MIT -- [GitHub](https://github.com/facebookresearch/faiss) (πŸ‘¨β€πŸ’» 90 Β· πŸ”€ 2.4K Β· πŸ“¦ 540 Β· πŸ“‹ 1.7K - 14% open Β· ⏱️ 10.01.2022): +- [GitHub](https://github.com/facebookresearch/faiss) (πŸ‘¨β€πŸ’» 92 Β· πŸ”€ 2.5K Β· πŸ“¦ 550 Β· πŸ“‹ 1.7K - 10% open Β· ⏱️ 08.02.2022): ``` git clone https://github.com/facebookresearch/faiss ``` -- [PyPi](https://pypi.org/project/pymilvus) (πŸ“₯ 24K / month Β· πŸ“¦ 15 Β· ⏱️ 31.12.2021): +- [PyPi](https://pypi.org/project/pymilvus) (πŸ“₯ 32K / month Β· πŸ“¦ 15 Β· ⏱️ 25.01.2022): ``` pip install pymilvus ``` -- [Conda](https://anaconda.org/conda-forge/faiss) (πŸ“₯ 230K Β· ⏱️ 20.11.2021): +- [Conda](https://anaconda.org/conda-forge/faiss) (πŸ“₯ 240K Β· ⏱️ 09.02.2022): ``` conda install -c conda-forge faiss ```
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Annoy (πŸ₯ˆ33 Β· ⭐ 9.3K) - Approximate Nearest Neighbors in C++/Python optimized for memory usage.. Apache-2 +
Annoy (πŸ₯ˆ32 Β· ⭐ 9.4K) - Approximate Nearest Neighbors in C++/Python optimized for memory usage.. Apache-2 -- [GitHub](https://github.com/spotify/annoy) (πŸ‘¨β€πŸ’» 76 Β· πŸ”€ 960 Β· πŸ“¦ 1.9K Β· πŸ“‹ 340 - 11% open Β· ⏱️ 03.01.2022): +- [GitHub](https://github.com/spotify/annoy) (πŸ‘¨β€πŸ’» 80 Β· πŸ”€ 960 Β· πŸ“¦ 1.9K Β· πŸ“‹ 340 - 11% open Β· ⏱️ 03.01.2022): ``` git clone https://github.com/spotify/annoy ``` -- [PyPi](https://pypi.org/project/annoy) (πŸ“₯ 780K / month Β· πŸ“¦ 240 Β· ⏱️ 18.09.2020): +- [PyPi](https://pypi.org/project/annoy) (πŸ“₯ 850K / month Β· πŸ“¦ 240 Β· ⏱️ 18.09.2020): ``` pip install annoy ``` +- [Conda](https://anaconda.org/conda-forge/python-annoy) (πŸ“₯ 210K Β· ⏱️ 28.01.2022): + ``` + conda install -c conda-forge python-annoy + ```
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NMSLIB (πŸ₯ˆ30 Β· ⭐ 2.7K) - Non-Metric Space Library (NMSLIB): An efficient similarity search.. Apache-2 +
hnswlib (πŸ₯ˆ30 Β· ⭐ 1.9K) - Header-only C++/python library for fast approximate nearest neighbors. Apache-2 -- [GitHub](https://github.com/nmslib/nmslib) (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 370 Β· πŸ“¦ 530 Β· πŸ“‹ 390 - 15% open Β· ⏱️ 19.09.2021): +- [GitHub](https://github.com/nmslib/hnswlib) (πŸ‘¨β€πŸ’» 54 Β· πŸ”€ 360 Β· πŸ“¦ 190 Β· πŸ“‹ 240 - 50% open Β· ⏱️ 06.02.2022): ``` - git clone https://github.com/nmslib/nmslib + git clone https://github.com/nmslib/hnswlib ``` -- [PyPi](https://pypi.org/project/nmslib) (πŸ“₯ 92K / month Β· πŸ“¦ 47 Β· ⏱️ 03.02.2021): +- [PyPi](https://pypi.org/project/hnswlib) (πŸ“₯ 67K / month Β· πŸ“¦ 20 Β· ⏱️ 07.02.2022): ``` - pip install nmslib + pip install hnswlib ``` -- [Conda](https://anaconda.org/conda-forge/nmslib) (πŸ“₯ 47K Β· ⏱️ 22.11.2021): +- [Conda](https://anaconda.org/conda-forge/hnswlib) (πŸ“₯ 35K Β· ⏱️ 04.02.2021): ``` - conda install -c conda-forge nmslib + conda install -c conda-forge hnswlib ```
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hnswlib (πŸ₯ˆ30 Β· ⭐ 1.8K) - Header-only C++/python library for fast approximate nearest neighbors. Apache-2 +
NMSLIB (πŸ₯ˆ29 Β· ⭐ 2.7K) - Non-Metric Space Library (NMSLIB): An efficient similarity search.. Apache-2 -- [GitHub](https://github.com/nmslib/hnswlib) (πŸ‘¨β€πŸ’» 52 Β· πŸ”€ 350 Β· πŸ“¦ 180 Β· πŸ“‹ 240 - 50% open Β· ⏱️ 09.12.2021): +- [GitHub](https://github.com/nmslib/nmslib) (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 380 Β· πŸ“¦ 550 Β· πŸ“‹ 390 - 15% open Β· ⏱️ 19.09.2021): ``` - git clone https://github.com/nmslib/hnswlib + git clone https://github.com/nmslib/nmslib ``` -- [PyPi](https://pypi.org/project/hnswlib) (πŸ“₯ 110K / month Β· πŸ“¦ 20 Β· ⏱️ 28.12.2021): +- [PyPi](https://pypi.org/project/nmslib) (πŸ“₯ 110K / month Β· πŸ“¦ 47 Β· ⏱️ 03.02.2021): ``` - pip install hnswlib + pip install nmslib + ``` +- [Conda](https://anaconda.org/conda-forge/nmslib) (πŸ“₯ 47K Β· ⏱️ 22.11.2021): + ``` + conda install -c conda-forge nmslib ```
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PyNNDescent (πŸ₯‰28 Β· ⭐ 570) - A Python nearest neighbor descent for approximate nearest neighbors. BSD-2 +
PyNNDescent (πŸ₯‰28 Β· ⭐ 580) - A Python nearest neighbor descent for approximate nearest neighbors. BSD-2 -- [GitHub](https://github.com/lmcinnes/pynndescent) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 72 Β· πŸ“¦ 1.1K Β· πŸ“‹ 94 - 46% open Β· ⏱️ 05.01.2022): +- [GitHub](https://github.com/lmcinnes/pynndescent) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 76 Β· πŸ“¦ 1.2K Β· πŸ“‹ 97 - 46% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/lmcinnes/pynndescent ``` -- [PyPi](https://pypi.org/project/pynndescent) (πŸ“₯ 1.4M / month Β· πŸ“¦ 22 Β· ⏱️ 15.10.2021): +- [PyPi](https://pypi.org/project/pynndescent) (πŸ“₯ 1.1M / month Β· πŸ“¦ 25 Β· ⏱️ 21.01.2022): ``` pip install pynndescent ``` -- [Conda](https://anaconda.org/conda-forge/pynndescent) (πŸ“₯ 430K Β· ⏱️ 15.10.2021): +- [Conda](https://anaconda.org/conda-forge/pynndescent) (πŸ“₯ 460K Β· ⏱️ 22.01.2022): ``` conda install -c conda-forge pynndescent ```
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NGT (πŸ₯‰19 Β· ⭐ 840) - Nearest Neighbor Search with Neighborhood Graph and Tree for High-.. Apache-2 +
NGT (πŸ₯‰20 Β· ⭐ 850) - Nearest Neighbor Search with Neighborhood Graph and Tree for High-.. Apache-2 -- [GitHub](https://github.com/yahoojapan/NGT) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 82 Β· πŸ“‹ 86 - 11% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/yahoojapan/NGT) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 84 Β· πŸ“‹ 88 - 12% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/yahoojapan/NGT ``` -- [PyPi](https://pypi.org/project/ngt) (πŸ“₯ 15K / month Β· πŸ“¦ 6 Β· ⏱️ 23.09.2020): +- [PyPi](https://pypi.org/project/ngt) (πŸ“₯ 17K / month Β· πŸ“¦ 8 Β· ⏱️ 10.02.2022): ``` pip install ngt ```
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N2 (πŸ₯‰18 Β· ⭐ 500 Β· πŸ’€) - TOROS N2 - lightweight approximate Nearest Neighbor library which runs.. Apache-2 +
N2 (πŸ₯‰18 Β· ⭐ 510 Β· πŸ’€) - TOROS N2 - lightweight approximate Nearest Neighbor library which runs.. Apache-2 - [GitHub](https://github.com/kakao/n2) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 61 Β· πŸ“¦ 22 Β· πŸ“‹ 37 - 45% open Β· ⏱️ 20.05.2021): ``` git clone https://github.com/kakao/n2 ``` -- [PyPi](https://pypi.org/project/n2) (πŸ“₯ 740 / month Β· πŸ“¦ 3 Β· ⏱️ 16.10.2020): +- [PyPi](https://pypi.org/project/n2) (πŸ“₯ 710 / month Β· πŸ“¦ 3 Β· ⏱️ 16.10.2020): ``` pip install n2 ``` @@ -7414,7 +7990,7 @@ _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarit - Magnitude (πŸ₯‰23 Β· ⭐ 1.5K Β· πŸ’€) - A fast, efficient universal vector embedding utility package. MIT - NearPy (πŸ₯‰21 Β· ⭐ 700 Β· πŸ’€) - Python framework for fast (approximated) nearest neighbour search in.. MIT -- PySparNN (πŸ₯‰11 Β· ⭐ 890 Β· πŸ’€) - Approximate Nearest Neighbor Search for Sparse Data in Python!. BSD-3 +- PySparNN (πŸ₯‰11 Β· ⭐ 900 Β· πŸ’€) - Approximate Nearest Neighbor Search for Sparse Data in Python!. BSD-3

@@ -7424,82 +8000,78 @@ _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarit _Libraries providing capabilities for probabilistic programming/reasoning, bayesian inference, gaussian processes, or statistics._ -
PyMC3 (πŸ₯‡39 Β· ⭐ 6.3K) - Probabilistic Programming in Python: Bayesian Modeling and.. Apache-2 +
PyMC3 (πŸ₯‡38 Β· ⭐ 6.3K) - Probabilistic Programming in Python: Bayesian Modeling and.. Apache-2 -- [GitHub](https://github.com/pymc-devs/pymc) (πŸ‘¨β€πŸ’» 350 Β· πŸ”€ 1.5K Β· πŸ“₯ 1.5K Β· πŸ“¦ 580 Β· πŸ“‹ 2.5K - 7% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/pymc-devs/pymc) (πŸ‘¨β€πŸ’» 360 Β· πŸ”€ 1.5K Β· πŸ“₯ 1.7K Β· πŸ“¦ 580 Β· πŸ“‹ 2.6K - 8% open Β· ⏱️ 09.02.2022): ``` - git clone https://github.com/pymc-devs/pymc3 + git clone https://github.com/pymc-devs/pymc ``` -- [PyPi](https://pypi.org/project/pymc3) (πŸ“₯ 240K / month Β· πŸ“¦ 230 Β· ⏱️ 24.08.2021): +- [PyPi](https://pypi.org/project/pymc3) (πŸ“₯ 320K / month Β· πŸ“¦ 230 Β· ⏱️ 24.08.2021): ``` pip install pymc3 ``` -- [Conda](https://anaconda.org/conda-forge/pymc3) (πŸ“₯ 370K Β· ⏱️ 12.10.2021): +- [Conda](https://anaconda.org/conda-forge/pymc3) (πŸ“₯ 380K Β· ⏱️ 12.10.2021): ``` conda install -c conda-forge pymc3 ```
tensorflow-probability (πŸ₯‡37 Β· ⭐ 3.6K) - Probabilistic reasoning and statistical analysis in.. Apache-2 -- [GitHub](https://github.com/tensorflow/probability) (πŸ‘¨β€πŸ’» 430 Β· πŸ”€ 950 Β· πŸ“‹ 1.2K - 45% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/tensorflow/probability) (πŸ‘¨β€πŸ’» 440 Β· πŸ”€ 960 Β· πŸ“‹ 1.2K - 45% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/tensorflow/probability ``` -- [PyPi](https://pypi.org/project/tensorflow-probability) (πŸ“₯ 760K / month Β· πŸ“¦ 300 Β· ⏱️ 17.11.2021): +- [PyPi](https://pypi.org/project/tensorflow-probability) (πŸ“₯ 710K / month Β· πŸ“¦ 310 Β· ⏱️ 17.11.2021): ``` pip install tensorflow-probability ``` -- [Conda](https://anaconda.org/conda-forge/tensorflow-probability) (πŸ“₯ 48K Β· ⏱️ 22.10.2021): +- [Conda](https://anaconda.org/conda-forge/tensorflow-probability) (πŸ“₯ 49K Β· ⏱️ 26.01.2022): ``` conda install -c conda-forge tensorflow-probability ```
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Pyro (πŸ₯‡32 Β· ⭐ 7.3K) - Deep universal probabilistic programming with Python and PyTorch. Apache-2 +
Pyro (πŸ₯‡33 Β· ⭐ 7.3K) - Deep universal probabilistic programming with Python and PyTorch. Apache-2 -- [GitHub](https://github.com/pyro-ppl/pyro) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 880 Β· πŸ“¦ 600 Β· πŸ“‹ 920 - 19% open Β· ⏱️ 28.12.2021): +- [GitHub](https://github.com/pyro-ppl/pyro) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 880 Β· πŸ“¦ 620 Β· πŸ“‹ 920 - 19% open Β· ⏱️ 27.01.2022): ``` git clone https://github.com/pyro-ppl/pyro ``` -- [PyPi](https://pypi.org/project/pyro-ppl) (πŸ“₯ 60K / month Β· πŸ“¦ 49 Β· ⏱️ 14.12.2021): +- [PyPi](https://pypi.org/project/pyro-ppl) (πŸ“₯ 74K / month Β· πŸ“¦ 49 Β· ⏱️ 14.12.2021): ``` pip install pyro-ppl ``` +- [Conda](https://anaconda.org/conda-forge/pyro-ppl) (πŸ“₯ 4.1K Β· ⏱️ 14.12.2021): + ``` + conda install -c conda-forge pyro-ppl + ```
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GPyTorch (πŸ₯‡32 Β· ⭐ 2.6K) - A highly efficient and modular implementation of Gaussian Processes.. MIT +
GPyTorch (πŸ₯‡33 Β· ⭐ 2.7K) - A highly efficient and modular implementation of Gaussian Processes.. MIT -- [GitHub](https://github.com/cornellius-gp/gpytorch) (πŸ‘¨β€πŸ’» 90 Β· πŸ”€ 390 Β· πŸ“¦ 460 Β· πŸ“‹ 1K - 23% open Β· ⏱️ 05.01.2022): +- [GitHub](https://github.com/cornellius-gp/gpytorch) (πŸ‘¨β€πŸ’» 91 Β· πŸ”€ 390 Β· πŸ“¦ 480 Β· πŸ“‹ 1K - 23% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/cornellius-gp/gpytorch ``` -- [PyPi](https://pypi.org/project/gpytorch) (πŸ“₯ 130K / month Β· πŸ“¦ 30 Β· ⏱️ 04.12.2021): +- [PyPi](https://pypi.org/project/gpytorch) (πŸ“₯ 140K / month Β· πŸ“¦ 30 Β· ⏱️ 04.12.2021): ``` pip install gpytorch ``` -
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pgmpy (πŸ₯‡32 Β· ⭐ 2K) - Python Library for learning (Structure and Parameter), inference.. MIT - -- [GitHub](https://github.com/pgmpy/pgmpy) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 630 Β· πŸ“₯ 120 Β· πŸ“¦ 300 Β· πŸ“‹ 770 - 28% open Β· ⏱️ 12.01.2022): - - ``` - git clone https://github.com/pgmpy/pgmpy - ``` -- [PyPi](https://pypi.org/project/pgmpy) (πŸ“₯ 65K / month Β· πŸ“¦ 9 Β· ⏱️ 30.12.2021): +- [Conda](https://anaconda.org/conda-forge/gpytorch) (πŸ“₯ 25K Β· ⏱️ 14.12.2021): ``` - pip install pgmpy + conda install -c conda-forge gpytorch ```
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hmmlearn (πŸ₯ˆ31 Β· ⭐ 2.4K) - Hidden Markov Models in Python, with scikit-learn like API. BSD-3 +
hmmlearn (πŸ₯ˆ32 Β· ⭐ 2.4K) - Hidden Markov Models in Python, with scikit-learn like API. BSD-3 -- [GitHub](https://github.com/hmmlearn/hmmlearn) (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 680 Β· πŸ“¦ 1.2K Β· πŸ“‹ 370 - 15% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/hmmlearn/hmmlearn) (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 690 Β· πŸ“¦ 1.2K Β· πŸ“‹ 380 - 14% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/hmmlearn/hmmlearn ``` -- [PyPi](https://pypi.org/project/hmmlearn) (πŸ“₯ 290K / month Β· πŸ“¦ 130 Β· ⏱️ 18.07.2021): +- [PyPi](https://pypi.org/project/hmmlearn) (πŸ“₯ 330K / month Β· πŸ“¦ 130 Β· ⏱️ 10.02.2022): ``` pip install hmmlearn ``` @@ -7508,6 +8080,18 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes conda install -c conda-forge hmmlearn ```
+
pgmpy (πŸ₯ˆ32 Β· ⭐ 2K) - Python Library for learning (Structure and Parameter), inference.. MIT + +- [GitHub](https://github.com/pgmpy/pgmpy) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 630 Β· πŸ“₯ 130 Β· πŸ“¦ 320 Β· πŸ“‹ 770 - 28% open Β· ⏱️ 21.01.2022): + + ``` + git clone https://github.com/pgmpy/pgmpy + ``` +- [PyPi](https://pypi.org/project/pgmpy) (πŸ“₯ 62K / month Β· πŸ“¦ 9 Β· ⏱️ 30.12.2021): + ``` + pip install pgmpy + ``` +
filterpy (πŸ₯ˆ31 Β· ⭐ 2.1K Β· πŸ’€) - Python Kalman filtering and optimal estimation library. Implements.. MIT - [GitHub](https://github.com/rlabbe/filterpy) (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 480 Β· πŸ“¦ 1.2K Β· πŸ“‹ 200 - 23% open Β· ⏱️ 04.05.2021): @@ -7515,137 +8099,148 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes ``` git clone https://github.com/rlabbe/filterpy ``` -- [PyPi](https://pypi.org/project/filterpy) (πŸ“₯ 630K / month Β· πŸ“¦ 130 Β· ⏱️ 10.10.2018): +- [PyPi](https://pypi.org/project/filterpy) (πŸ“₯ 650K / month Β· πŸ“¦ 130 Β· ⏱️ 10.10.2018): ``` pip install filterpy ``` -- [Conda](https://anaconda.org/conda-forge/filterpy) (πŸ“₯ 71K Β· ⏱️ 05.05.2020): +- [Conda](https://anaconda.org/conda-forge/filterpy) (πŸ“₯ 72K Β· ⏱️ 05.05.2020): ``` conda install -c conda-forge filterpy ```
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pomegranate (πŸ₯ˆ30 Β· ⭐ 2.8K) - Fast, flexible and easy to use probabilistic modelling in Python. MIT +
GPflow (πŸ₯ˆ31 Β· ⭐ 1.6K) - Gaussian processes in TensorFlow. Apache-2 -- [GitHub](https://github.com/jmschrei/pomegranate) (πŸ‘¨β€πŸ’» 65 Β· πŸ”€ 510 Β· πŸ“¦ 610 Β· πŸ“‹ 670 - 8% open Β· ⏱️ 20.11.2021): +- [GitHub](https://github.com/GPflow/GPflow) (πŸ‘¨β€πŸ’» 76 Β· πŸ”€ 420 Β· πŸ“¦ 320 Β· πŸ“‹ 750 - 16% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/jmschrei/pomegranate + git clone https://github.com/GPflow/GPflow ``` -- [PyPi](https://pypi.org/project/pomegranate) (πŸ“₯ 33K / month Β· πŸ“¦ 44 Β· ⏱️ 19.11.2021): +- [PyPi](https://pypi.org/project/gpflow) (πŸ“₯ 8.5K / month Β· πŸ“¦ 28 Β· ⏱️ 20.01.2022): ``` - pip install pomegranate + pip install gpflow ``` -- [Conda](https://anaconda.org/conda-forge/pomegranate) (πŸ“₯ 78K Β· ⏱️ 16.11.2021): +- [Conda](https://anaconda.org/conda-forge/gpflow) (πŸ“₯ 10K Β· ⏱️ 06.02.2022): ``` - conda install -c conda-forge pomegranate + conda install -c conda-forge gpflow ```
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GPflow (πŸ₯ˆ30 Β· ⭐ 1.6K) - Gaussian processes in TensorFlow. Apache-2 +
pomegranate (πŸ₯ˆ30 Β· ⭐ 2.8K) - Fast, flexible and easy to use probabilistic modelling in Python. MIT -- [GitHub](https://github.com/GPflow/GPflow) (πŸ‘¨β€πŸ’» 72 Β· πŸ”€ 410 Β· πŸ“¦ 320 Β· πŸ“‹ 740 - 16% open Β· ⏱️ 05.01.2022): +- [GitHub](https://github.com/jmschrei/pomegranate) (πŸ‘¨β€πŸ’» 65 Β· πŸ”€ 510 Β· πŸ“¦ 630 Β· πŸ“‹ 670 - 8% open Β· ⏱️ 06.02.2022): ``` - git clone https://github.com/GPflow/GPflow + git clone https://github.com/jmschrei/pomegranate ``` -- [PyPi](https://pypi.org/project/gpflow) (πŸ“₯ 7.2K / month Β· πŸ“¦ 28 Β· ⏱️ 26.10.2021): +- [PyPi](https://pypi.org/project/pomegranate) (πŸ“₯ 40K / month Β· πŸ“¦ 44 Β· ⏱️ 19.11.2021): ``` - pip install gpflow + pip install pomegranate ``` -- [Conda](https://anaconda.org/conda-forge/gpflow) (πŸ“₯ 9.8K Β· ⏱️ 06.11.2018): +- [Conda](https://anaconda.org/conda-forge/pomegranate) (πŸ“₯ 79K Β· ⏱️ 16.11.2021): ``` - conda install -c conda-forge gpflow + conda install -c conda-forge pomegranate ```
patsy (πŸ₯ˆ30 Β· ⭐ 810) - Describing statistical models in Python using symbolic formulas. BSD-2 -- [GitHub](https://github.com/pydata/patsy) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 94 Β· πŸ“¦ 46K Β· πŸ“‹ 140 - 51% open Β· ⏱️ 26.09.2021): +- [GitHub](https://github.com/pydata/patsy) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 94 Β· πŸ“¦ 47K Β· πŸ“‹ 140 - 51% open Β· ⏱️ 26.09.2021): ``` git clone https://github.com/pydata/patsy ``` -- [PyPi](https://pypi.org/project/patsy) (πŸ“₯ 4.5M / month Β· πŸ“¦ 2.6K Β· ⏱️ 26.09.2021): +- [PyPi](https://pypi.org/project/patsy) (πŸ“₯ 5.5M / month Β· πŸ“¦ 2.6K Β· ⏱️ 26.09.2021): ``` pip install patsy ``` -- [Conda](https://anaconda.org/conda-forge/patsy) (πŸ“₯ 4.1M Β· ⏱️ 26.09.2021): +- [Conda](https://anaconda.org/conda-forge/patsy) (πŸ“₯ 4.2M Β· ⏱️ 26.09.2021): ``` conda install -c conda-forge patsy ```
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SALib (πŸ₯‰29 Β· ⭐ 560) - Sensitivity Analysis Library in Python. Contains Sobol, Morris, FAST, and.. MIT +
pandas-ta (πŸ₯‰28 Β· ⭐ 2.1K) - Technical Analysis Indicators - Pandas TA is an easy to use.. MIT -- [GitHub](https://github.com/SALib/SALib) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 170 Β· πŸ“‹ 270 - 18% open Β· ⏱️ 19.12.2021): +- [GitHub](https://github.com/twopirllc/pandas-ta) (πŸ‘¨β€πŸ’» 44 Β· πŸ”€ 490 Β· πŸ“¦ 430 Β· πŸ“‹ 360 - 15% open Β· ⏱️ 31.01.2022): ``` - git clone https://github.com/SALib/SALib + git clone https://github.com/twopirllc/pandas-ta ``` -- [PyPi](https://pypi.org/project/salib) (πŸ“₯ 80K / month Β· πŸ“¦ 51 Β· ⏱️ 04.09.2021): +- [PyPi](https://pypi.org/project/pandas-ta) (πŸ“₯ 83K / month Β· πŸ“¦ 10 Β· ⏱️ 28.07.2021): ``` - pip install salib + pip install pandas-ta ``` -- [Conda](https://anaconda.org/conda-forge/salib) (πŸ“₯ 75K Β· ⏱️ 04.09.2021): +- [Conda](https://anaconda.org/conda-forge/pandas-ta) (πŸ“₯ 310 Β· ⏱️ 05.10.2021): ``` - conda install -c conda-forge salib + conda install -c conda-forge pandas-ta ```
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pandas-ta (πŸ₯‰27 Β· ⭐ 2K) - Technical Analysis Indicators - Pandas TA is an easy to use Python.. MIT +
SALib (πŸ₯‰28 Β· ⭐ 560) - Sensitivity Analysis Library in Python. Contains Sobol, Morris, FAST, and.. MIT -- [GitHub](https://github.com/twopirllc/pandas-ta) (πŸ‘¨β€πŸ’» 44 Β· πŸ”€ 460 Β· πŸ“¦ 390 Β· πŸ“‹ 330 - 17% open Β· ⏱️ 16.11.2021): +- [GitHub](https://github.com/SALib/SALib) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 170 Β· πŸ“‹ 270 - 17% open Β· ⏱️ 06.02.2022): ``` - git clone https://github.com/twopirllc/pandas-ta + git clone https://github.com/SALib/SALib ``` -- [PyPi](https://pypi.org/project/pandas-ta) (πŸ“₯ 41K / month Β· πŸ“¦ 10 Β· ⏱️ 28.07.2021): +- [PyPi](https://pypi.org/project/salib) (πŸ“₯ 120K / month Β· πŸ“¦ 54 Β· ⏱️ 06.02.2022): ``` - pip install pandas-ta + pip install salib + ``` +- [Conda](https://anaconda.org/conda-forge/salib) (πŸ“₯ 75K Β· ⏱️ 04.09.2021): + ``` + conda install -c conda-forge salib ```
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bambi (πŸ₯‰25 Β· ⭐ 730) - BAyesian Model-Building Interface (Bambi) in Python. MIT +
bambi (πŸ₯‰25 Β· ⭐ 740) - BAyesian Model-Building Interface (Bambi) in Python. MIT -- [GitHub](https://github.com/bambinos/bambi) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 72 Β· πŸ“¦ 20 Β· πŸ“‹ 220 - 15% open Β· ⏱️ 11.01.2022): +- [GitHub](https://github.com/bambinos/bambi) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 76 Β· πŸ“¦ 21 Β· πŸ“‹ 220 - 17% open Β· ⏱️ 21.01.2022): ``` git clone https://github.com/bambinos/bambi ``` -- [PyPi](https://pypi.org/project/bambi) (πŸ“₯ 2K / month Β· πŸ“¦ 3 Β· ⏱️ 11.01.2022): +- [PyPi](https://pypi.org/project/bambi) (πŸ“₯ 2.5K / month Β· πŸ“¦ 3 Β· ⏱️ 15.01.2022): ``` pip install bambi ``` +- [Conda](https://anaconda.org/conda-forge/bambi) (πŸ“₯ 6.3K Β· ⏱️ 18.01.2022): + ``` + conda install -c conda-forge bambi + ```
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Orbit (πŸ₯‰23 Β· ⭐ 860) - A Python package for Bayesian forecasting with object-oriented design.. Apache-2 +
Orbit (πŸ₯‰24 Β· ⭐ 1.2K) - A Python package for Bayesian forecasting with object-oriented design.. Apache-2 -- [GitHub](https://github.com/uber/orbit) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 65 Β· πŸ“¦ 5 Β· πŸ“‹ 310 - 13% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/uber/orbit) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 83 Β· πŸ“¦ 6 Β· πŸ“‹ 330 - 15% open Β· ⏱️ 27.01.2022): ``` git clone https://github.com/uber/orbit ``` -- [PyPi](https://pypi.org/project/orbit-ml) (πŸ“₯ 3K / month Β· πŸ“¦ 1 Β· ⏱️ 12.01.2022): +- [PyPi](https://pypi.org/project/orbit-ml) (πŸ“₯ 6K / month Β· πŸ“¦ 1 Β· ⏱️ 12.01.2022): ``` pip install orbit-ml ```
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Baal (πŸ₯‰20 Β· ⭐ 520) - Library to enable Bayesian active learning in your research or labeling.. Apache-2 +
Baal (πŸ₯‰20 Β· ⭐ 540) - Library to enable Bayesian active learning in your research or labeling.. Apache-2 -- [GitHub](https://github.com/ElementAI/baal) (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 49 Β· πŸ“‹ 63 - 28% open Β· ⏱️ 10.01.2022): +- [GitHub](https://github.com/ElementAI/baal) (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 50 Β· πŸ“‹ 63 - 28% open Β· ⏱️ 10.01.2022): ``` git clone https://github.com/ElementAI/baal ``` -- [PyPi](https://pypi.org/project/baal) (πŸ“₯ 560 / month Β· πŸ“¦ 1 Β· ⏱️ 17.12.2021): +- [PyPi](https://pypi.org/project/baal) (πŸ“₯ 740 / month Β· πŸ“¦ 1 Β· ⏱️ 17.12.2021): ``` pip install baal ``` +- [Conda](https://anaconda.org/conda-forge/baal) (πŸ“₯ 1K Β· ⏱️ 06.08.2021): + ``` + conda install -c conda-forge baal + ```
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Show 8 hidden projects... +
Show 7 hidden projects... +- pingouin (πŸ₯‰29 Β· ⭐ 900) - Statistical package in Python based on Pandas. ❗️GPL-3.0 - Edward (πŸ₯‰28 Β· ⭐ 4.7K Β· πŸ’€) - A probabilistic programming language in TensorFlow. Deep.. Apache-2 -- pingouin (πŸ₯‰28 Β· ⭐ 880) - Statistical package in Python based on Pandas. ❗️GPL-3.0 -- PyStan (πŸ₯‰25 Β· ⭐ 150) - PyStan, a Python interface to Stan, a platform for statistical modeling... ISC -- scikit-posthocs (πŸ₯‰21 Β· ⭐ 220) - Multiple Pairwise Comparisons (Post Hoc) Tests in Python. MIT -- pyhsmm (πŸ₯‰20 Β· ⭐ 500 Β· πŸ’€) - Bayesian inference in HSMMs and HMMs. MIT -- Funsor (πŸ₯‰20 Β· ⭐ 190) - Functional tensors for probabilistic programming. Apache-2 +- PyStan (πŸ₯‰27 Β· ⭐ 160) - PyStan, a Python interface to Stan, a platform for statistical modeling... ISC +- pyhsmm (πŸ₯‰21 Β· ⭐ 510 Β· πŸ’€) - Bayesian inference in HSMMs and HMMs. MIT +- scikit-posthocs (πŸ₯‰20 Β· ⭐ 230) - Multiple Pairwise Comparisons (Post Hoc) Tests in Python. MIT +- Funsor (πŸ₯‰19 Β· ⭐ 190) - Functional tensors for probabilistic programming. Apache-2 - ZhuSuan (πŸ₯‰15 Β· ⭐ 2.1K Β· πŸ’€) - A probabilistic programming library for Bayesian deep learning,.. MIT -- Lea (πŸ₯‰12) - Discrete probability distributions in Python. ❗️GPL-3.0

@@ -7655,53 +8250,69 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes _Libraries for testing the robustness of machine learning models against attacks with adversarial/malicious examples._ -
ART (πŸ₯‡32 Β· ⭐ 2.7K) - Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning.. MIT +
ART (πŸ₯‡32 Β· ⭐ 2.8K) - Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning.. MIT -- [GitHub](https://github.com/Trusted-AI/adversarial-robustness-toolbox) (πŸ‘¨β€πŸ’» 90 Β· πŸ”€ 760 Β· πŸ“¦ 180 Β· πŸ“‹ 630 - 11% open Β· ⏱️ 10.01.2022): +- [GitHub](https://github.com/Trusted-AI/adversarial-robustness-toolbox) (πŸ‘¨β€πŸ’» 90 Β· πŸ”€ 760 Β· πŸ“¦ 180 Β· πŸ“‹ 630 - 11% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/Trusted-AI/adversarial-robustness-toolbox ``` -- [PyPi](https://pypi.org/project/adversarial-robustness-toolbox) (πŸ“₯ 3.8K / month Β· πŸ“¦ 6 Β· ⏱️ 07.01.2022): +- [PyPi](https://pypi.org/project/adversarial-robustness-toolbox) (πŸ“₯ 4.1K / month Β· πŸ“¦ 6 Β· ⏱️ 07.01.2022): ``` pip install adversarial-robustness-toolbox ``` +- [Conda](https://anaconda.org/conda-forge/adversarial-robustness-toolbox) (πŸ“₯ 7.7K Β· ⏱️ 10.01.2022): + ``` + conda install -c conda-forge adversarial-robustness-toolbox + ```
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TextAttack (πŸ₯ˆ30 Β· ⭐ 1.8K) - TextAttack is a Python framework for adversarial attacks, data.. MIT +
CleverHans (πŸ₯ˆ30 Β· ⭐ 5.4K) - An adversarial example library for constructing attacks,.. MIT -- [GitHub](https://github.com/QData/TextAttack) (πŸ‘¨β€πŸ’» 46 Β· πŸ”€ 220 Β· πŸ“¦ 51 Β· πŸ“‹ 190 - 20% open Β· ⏱️ 16.12.2021): +- [GitHub](https://github.com/cleverhans-lab/cleverhans) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 1.3K Β· πŸ“¦ 290 Β· πŸ“‹ 450 - 5% open Β· ⏱️ 23.09.2021): ``` - git clone https://github.com/QData/TextAttack + git clone https://github.com/cleverhans-lab/cleverhans ``` -- [PyPi](https://pypi.org/project/textattack) (πŸ“₯ 6.6K / month Β· πŸ“¦ 3 Β· ⏱️ 10.11.2021): +- [PyPi](https://pypi.org/project/cleverhans) (πŸ“₯ 1.1K / month Β· πŸ“¦ 11 Β· ⏱️ 24.07.2021): ``` - pip install textattack + pip install cleverhans + ``` +- [Conda](https://anaconda.org/conda-forge/cleverhans) (πŸ“₯ 2.5K Β· ⏱️ 29.07.2021): + ``` + conda install -c conda-forge cleverhans ```
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CleverHans (πŸ₯ˆ29 Β· ⭐ 5.4K) - An adversarial example library for constructing attacks,.. MIT +
TextAttack (πŸ₯ˆ30 Β· ⭐ 1.8K) - TextAttack is a Python framework for adversarial attacks, data.. MIT -- [GitHub](https://github.com/cleverhans-lab/cleverhans) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 1.3K Β· πŸ“¦ 280 Β· πŸ“‹ 450 - 5% open Β· ⏱️ 23.09.2021): +- [GitHub](https://github.com/QData/TextAttack) (πŸ‘¨β€πŸ’» 46 Β· πŸ”€ 220 Β· πŸ“¦ 62 Β· πŸ“‹ 190 - 20% open Β· ⏱️ 16.12.2021): ``` - git clone https://github.com/cleverhans-lab/cleverhans + git clone https://github.com/QData/TextAttack ``` -- [PyPi](https://pypi.org/project/cleverhans) (πŸ“₯ 870 / month Β· πŸ“¦ 11 Β· ⏱️ 24.07.2021): +- [PyPi](https://pypi.org/project/textattack) (πŸ“₯ 11K / month Β· πŸ“¦ 3 Β· ⏱️ 10.11.2021): ``` - pip install cleverhans + pip install textattack + ``` +- [Conda](https://anaconda.org/conda-forge/textattack) (πŸ“₯ 2.5K Β· ⏱️ 29.06.2021): + ``` + conda install -c conda-forge textattack ```
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Foolbox (πŸ₯ˆ28 Β· ⭐ 2.1K Β· πŸ’€) - A Python toolbox to create adversarial examples that fool neural.. MIT +
Foolbox (πŸ₯ˆ29 Β· ⭐ 2.1K) - A Python toolbox to create adversarial examples that fool neural networks.. MIT -- [GitHub](https://github.com/bethgelab/foolbox) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 370 Β· πŸ“¦ 260 Β· πŸ“‹ 330 - 18% open Β· ⏱️ 05.06.2021): +- [GitHub](https://github.com/bethgelab/foolbox) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 370 Β· πŸ“¦ 260 Β· πŸ“‹ 360 - 16% open Β· ⏱️ 04.02.2022): ``` git clone https://github.com/bethgelab/foolbox ``` -- [PyPi](https://pypi.org/project/foolbox) (πŸ“₯ 3.2K / month Β· πŸ“¦ 13 Β· ⏱️ 23.02.2021): +- [PyPi](https://pypi.org/project/foolbox) (πŸ“₯ 3K / month Β· πŸ“¦ 13 Β· ⏱️ 23.02.2021): ``` pip install foolbox ``` +- [Conda](https://anaconda.org/conda-forge/foolbox) (πŸ“₯ 5.3K Β· ⏱️ 30.04.2021): + ``` + conda install -c conda-forge foolbox + ```
AdvBox (πŸ₯‰19 Β· ⭐ 1.2K Β· πŸ’€) - Advbox is a toolbox to generate adversarial examples that fool.. Apache-2 @@ -7710,28 +8321,32 @@ _Libraries for testing the robustness of machine learning models against attacks ``` git clone https://github.com/advboxes/AdvBox ``` -- [PyPi](https://pypi.org/project/advbox) (πŸ“₯ 44 / month Β· ⏱️ 05.12.2018): +- [PyPi](https://pypi.org/project/advbox) (πŸ“₯ 26 / month Β· ⏱️ 05.12.2018): ``` pip install advbox ```
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robustness (πŸ₯‰17 Β· ⭐ 650) - A library for experimenting with, training and evaluating neural.. MIT +
robustness (πŸ₯‰17 Β· ⭐ 660) - A library for experimenting with, training and evaluating neural.. MIT -- [GitHub](https://github.com/MadryLab/robustness) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 120 Β· πŸ“¦ 69 Β· πŸ“‹ 68 - 20% open Β· ⏱️ 30.11.2021): +- [GitHub](https://github.com/MadryLab/robustness) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 120 Β· πŸ“¦ 69 Β· πŸ“‹ 70 - 21% open Β· ⏱️ 30.11.2021): ``` git clone https://github.com/MadryLab/robustness ``` -- [PyPi](https://pypi.org/project/robustness) (πŸ“₯ 800 / month Β· πŸ“¦ 2 Β· ⏱️ 01.12.2020): +- [PyPi](https://pypi.org/project/robustness) (πŸ“₯ 440 / month Β· πŸ“¦ 2 Β· ⏱️ 01.12.2020): ``` pip install robustness ``` +- [Conda](https://anaconda.org/conda-forge/robustness) (πŸ“₯ 3.2K Β· ⏱️ 30.04.2021): + ``` + conda install -c conda-forge robustness + ```
Show 3 hidden projects... -- advertorch (πŸ₯‰21 Β· ⭐ 990) - A Toolbox for Adversarial Robustness Research. ❗️GPL-3.0 -- textflint (πŸ₯‰16 Β· ⭐ 540) - Unified Multilingual Robustness Evaluation Toolkit for Natural.. ❗️GPL-3.0 -- Adversary (πŸ₯‰15 Β· ⭐ 360 Β· πŸ’€) - Tool to generate adversarial text examples and test machine.. MIT +- advertorch (πŸ₯‰21 Β· ⭐ 1K Β· πŸ’€) - A Toolbox for Adversarial Robustness Research. ❗️GPL-3.0 +- Adversary (πŸ₯‰16 Β· ⭐ 360 Β· πŸ’€) - Tool to generate adversarial text examples and test machine.. MIT +- textflint (πŸ₯‰14 Β· ⭐ 540) - Unified Multilingual Robustness Evaluation Toolkit for Natural.. ❗️GPL-3.0

@@ -7741,113 +8356,117 @@ _Libraries for testing the robustness of machine learning models against attacks _Libraries that require and make use of CUDA/GPU system capabilities to optimize data handling and machine learning tasks._ -
CuPy (πŸ₯‡39 Β· ⭐ 5.7K) - NumPy & SciPy for GPU. MIT +
CuPy (πŸ₯‡38 Β· ⭐ 5.8K) - NumPy & SciPy for GPU. MIT -- [GitHub](https://github.com/cupy/cupy) (πŸ‘¨β€πŸ’» 290 Β· πŸ”€ 530 Β· πŸ“₯ 24K Β· πŸ“¦ 910 Β· πŸ“‹ 1.6K - 22% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/cupy/cupy) (πŸ‘¨β€πŸ’» 290 Β· πŸ”€ 560 Β· πŸ“₯ 25K Β· πŸ“¦ 920 Β· πŸ“‹ 1.7K - 23% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/cupy/cupy ``` -- [PyPi](https://pypi.org/project/cupy) (πŸ“₯ 82K / month Β· πŸ“¦ 140 Β· ⏱️ 09.12.2021): +- [PyPi](https://pypi.org/project/cupy) (πŸ“₯ 88K / month Β· πŸ“¦ 150 Β· ⏱️ 20.01.2022): ``` pip install cupy ``` -- [Conda](https://anaconda.org/conda-forge/cupy) (πŸ“₯ 1.1M Β· ⏱️ 16.12.2021): +- [Conda](https://anaconda.org/conda-forge/cupy) (πŸ“₯ 1.2M Β· ⏱️ 03.02.2022): ``` conda install -c conda-forge cupy ``` -- [Docker Hub](https://hub.docker.com/r/cupy/cupy) (πŸ“₯ 54K Β· ⭐ 7 Β· ⏱️ 09.12.2021): +- [Docker Hub](https://hub.docker.com/r/cupy/cupy) (πŸ“₯ 54K Β· ⭐ 7 Β· ⏱️ 20.01.2022): ``` docker pull cupy/cupy ```
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cuDF (πŸ₯‡30 Β· ⭐ 4.4K) - cuDF - GPU DataFrame Library. Apache-2 +
cuDF (πŸ₯‡30 Β· ⭐ 4.5K) - cuDF - GPU DataFrame Library. Apache-2 -- [GitHub](https://github.com/rapidsai/cudf) (πŸ‘¨β€πŸ’» 230 Β· πŸ”€ 580 Β· πŸ“‹ 4.3K - 16% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/rapidsai/cudf) (πŸ‘¨β€πŸ’» 230 Β· πŸ”€ 590 Β· πŸ“‹ 4.4K - 16% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/rapidsai/cudf ``` -- [PyPi](https://pypi.org/project/cudf) (πŸ“₯ 770 / month Β· πŸ“¦ 3 Β· ⏱️ 01.06.2020): +- [PyPi](https://pypi.org/project/cudf) (πŸ“₯ 1K / month Β· πŸ“¦ 3 Β· ⏱️ 01.06.2020): ``` pip install cudf ```
PyCUDA (πŸ₯‡30 Β· ⭐ 1.3K) - CUDA integration for Python, plus shiny features. MIT -- [GitHub](https://github.com/inducer/pycuda) (πŸ‘¨β€πŸ’» 74 Β· πŸ”€ 250 Β· πŸ“¦ 1.1K Β· πŸ“‹ 220 - 29% open Β· ⏱️ 11.01.2022): +- [GitHub](https://github.com/inducer/pycuda) (πŸ‘¨β€πŸ’» 74 Β· πŸ”€ 250 Β· πŸ“¦ 1.2K Β· πŸ“‹ 220 - 29% open Β· ⏱️ 11.01.2022): ``` git clone https://github.com/inducer/pycuda ``` -- [PyPi](https://pypi.org/project/pycuda) (πŸ“₯ 33K / month Β· πŸ“¦ 190 Β· ⏱️ 03.04.2021): +- [PyPi](https://pypi.org/project/pycuda) (πŸ“₯ 32K / month Β· πŸ“¦ 190 Β· ⏱️ 03.04.2021): ``` pip install pycuda ``` +- [Conda](https://anaconda.org/conda-forge/pycuda) (πŸ“₯ 55K Β· ⏱️ 06.11.2021): + ``` + conda install -c conda-forge pycuda + ```
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gpustat (πŸ₯ˆ28 Β· ⭐ 2.7K) - A simple command-line utility for querying and monitoring GPU status. MIT +
gpustat (πŸ₯ˆ29 Β· ⭐ 2.7K) - A simple command-line utility for querying and monitoring GPU status. MIT -- [GitHub](https://github.com/wookayin/gpustat) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 210 Β· πŸ“¦ 1.5K Β· πŸ“‹ 78 - 28% open Β· ⏱️ 13.08.2021): +- [GitHub](https://github.com/wookayin/gpustat) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 210 Β· πŸ“¦ 1.6K Β· πŸ“‹ 79 - 27% open Β· ⏱️ 13.08.2021): ``` git clone https://github.com/wookayin/gpustat ``` -- [PyPi](https://pypi.org/project/gpustat) (πŸ“₯ 300K / month Β· πŸ“¦ 99 Β· ⏱️ 02.01.2021): +- [PyPi](https://pypi.org/project/gpustat) (πŸ“₯ 480K / month Β· πŸ“¦ 99 Β· ⏱️ 02.01.2021): ``` pip install gpustat ``` -- [Conda](https://anaconda.org/conda-forge/gpustat) (πŸ“₯ 110K Β· ⏱️ 24.11.2020): +- [Conda](https://anaconda.org/conda-forge/gpustat) (πŸ“₯ 120K Β· ⏱️ 24.11.2020): ``` conda install -c conda-forge gpustat ```
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cuML (πŸ₯ˆ27 Β· ⭐ 2.5K) - cuML - RAPIDS Machine Learning Library. Apache-2 +
Apex (πŸ₯ˆ27 Β· ⭐ 6.1K) - A PyTorch Extension: Tools for easy mixed precision and distributed.. BSD-3 -- [GitHub](https://github.com/rapidsai/cuml) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 370 Β· πŸ“‹ 1.9K - 33% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/NVIDIA/apex) (πŸ‘¨β€πŸ’» 91 Β· πŸ”€ 880 Β· πŸ“¦ 870 Β· πŸ“‹ 930 - 56% open Β· ⏱️ 07.02.2022): ``` - git clone https://github.com/rapidsai/cuml + git clone https://github.com/NVIDIA/apex ``` -- [PyPi](https://pypi.org/project/cuml) (πŸ“₯ 550 / month Β· πŸ“¦ 1 Β· ⏱️ 01.06.2020): +- [Conda](https://anaconda.org/conda-forge/nvidia-apex) (πŸ“₯ 73K Β· ⏱️ 22.04.2021): ``` - pip install cuml + conda install -c conda-forge nvidia-apex ```
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Apex (πŸ₯ˆ26 Β· ⭐ 6K) - A PyTorch Extension: Tools for easy mixed precision and distributed.. BSD-3 +
cuML (πŸ₯ˆ27 Β· ⭐ 2.6K) - cuML - RAPIDS Machine Learning Library. Apache-2 -- [GitHub](https://github.com/NVIDIA/apex) (πŸ‘¨β€πŸ’» 88 Β· πŸ”€ 870 Β· πŸ“¦ 850 Β· πŸ“‹ 930 - 57% open Β· ⏱️ 17.12.2021): +- [GitHub](https://github.com/rapidsai/cuml) (πŸ‘¨β€πŸ’» 150 Β· πŸ”€ 380 Β· πŸ“‹ 2K - 33% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/NVIDIA/apex + git clone https://github.com/rapidsai/cuml ``` -- [Conda](https://anaconda.org/conda-forge/nvidia-apex) (πŸ“₯ 72K Β· ⏱️ 22.04.2021): +- [PyPi](https://pypi.org/project/cuml) (πŸ“₯ 570 / month Β· πŸ“¦ 1 Β· ⏱️ 01.06.2020): ``` - conda install -c conda-forge nvidia-apex + pip install cuml ```
ArrayFire (πŸ₯ˆ26 Β· ⭐ 3.7K) - ArrayFire: a general purpose GPU library. BSD-3 -- [GitHub](https://github.com/arrayfire/arrayfire) (πŸ‘¨β€πŸ’» 81 Β· πŸ”€ 490 Β· πŸ“₯ 1.8K Β· πŸ“‹ 1.5K - 15% open Β· ⏱️ 15.10.2021): +- [GitHub](https://github.com/arrayfire/arrayfire) (πŸ‘¨β€πŸ’» 81 Β· πŸ”€ 490 Β· πŸ“₯ 2K Β· πŸ“‹ 1.5K - 15% open Β· ⏱️ 07.02.2022): ``` git clone https://github.com/arrayfire/arrayfire ``` -- [PyPi](https://pypi.org/project/arrayfire) (πŸ“₯ 530 / month Β· πŸ“¦ 5 Β· ⏱️ 05.03.2021): +- [PyPi](https://pypi.org/project/arrayfire) (πŸ“₯ 570 / month Β· πŸ“¦ 5 Β· ⏱️ 05.03.2021): ``` pip install arrayfire ```
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DALI (πŸ₯‰24 Β· ⭐ 3.7K) - A GPU-accelerated library containing highly optimized building blocks.. Apache-2 +
DALI (πŸ₯ˆ24 Β· ⭐ 3.7K) - A GPU-accelerated library containing highly optimized building blocks.. Apache-2 -- [GitHub](https://github.com/NVIDIA/DALI) (πŸ‘¨β€πŸ’» 68 Β· πŸ”€ 460 Β· πŸ“‹ 1.1K - 13% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/NVIDIA/DALI) (πŸ‘¨β€πŸ’» 69 Β· πŸ”€ 460 Β· πŸ“‹ 1.1K - 13% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/NVIDIA/DALI ```
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cuGraph (πŸ₯‰24 Β· ⭐ 890) - cuGraph - RAPIDS Graph Analytics Library. Apache-2 +
cuGraph (πŸ₯ˆ24 Β· ⭐ 920) - cuGraph - RAPIDS Graph Analytics Library. Apache-2 -- [GitHub](https://github.com/rapidsai/cugraph) (πŸ‘¨β€πŸ’» 71 Β· πŸ”€ 170 Β· πŸ“‹ 750 - 11% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/rapidsai/cugraph) (πŸ‘¨β€πŸ’» 75 Β· πŸ”€ 170 Β· πŸ“‹ 760 - 11% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/rapidsai/cugraph @@ -7856,20 +8475,24 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize ``` pip install cugraph ``` +- [Conda](https://anaconda.org/conda-forge/libcugraph) (πŸ“₯ 6.2K Β· ⏱️ 29.04.2021): + ``` + conda install -c conda-forge libcugraph + ```
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scikit-cuda (πŸ₯‰24 Β· ⭐ 870) - Python interface to GPU-powered libraries. BSD-3 +
scikit-cuda (πŸ₯ˆ24 Β· ⭐ 880 Β· πŸ’€) - Python interface to GPU-powered libraries. BSD-3 - [GitHub](https://github.com/lebedov/scikit-cuda) (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 170 Β· πŸ“¦ 160 Β· πŸ“‹ 220 - 22% open Β· ⏱️ 13.07.2021): ``` git clone https://github.com/lebedov/scikit-cuda ``` -- [PyPi](https://pypi.org/project/scikit-cuda) (πŸ“₯ 540 / month Β· πŸ“¦ 44 Β· ⏱️ 27.05.2019): +- [PyPi](https://pypi.org/project/scikit-cuda) (πŸ“₯ 870 / month Β· πŸ“¦ 44 Β· ⏱️ 27.05.2019): ``` pip install scikit-cuda ```
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BlazingSQL (πŸ₯‰23 Β· ⭐ 1.7K) - BlazingSQL is a lightweight, GPU accelerated, SQL engine for.. Apache-2 +
BlazingSQL (πŸ₯‰22 Β· ⭐ 1.7K) - BlazingSQL is a lightweight, GPU accelerated, SQL engine for.. Apache-2 - [GitHub](https://github.com/BlazingDB/blazingsql) (πŸ‘¨β€πŸ’» 47 Β· πŸ”€ 160 Β· πŸ“‹ 720 - 18% open Β· ⏱️ 30.09.2021): @@ -7881,21 +8504,33 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize conda install -c blazingsql blazingsql-protocol ```
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Vulkan Kompute (πŸ₯‰19 Β· ⭐ 710) - General purpose GPU compute framework for cross vendor.. Apache-2 +
Vulkan Kompute (πŸ₯‰20 Β· ⭐ 750) - General purpose GPU compute framework built on Vulkan to.. Apache-2 + +- [GitHub](https://github.com/KomputeProject/kompute) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 54 Β· πŸ“₯ 130 Β· πŸ“¦ 2 Β· πŸ“‹ 170 - 33% open Β· ⏱️ 30.01.2022): + + ``` + git clone https://github.com/KomputeProject/kompute + ``` +- [PyPi](https://pypi.org/project/kp) (πŸ“₯ 150 / month Β· ⏱️ 15.09.2021): + ``` + pip install kp + ``` +
+
kompute (πŸ₯‰20 Β· ⭐ 750 Β· βž•) - General purpose GPU compute framework built on Vulkan to support.. Apache-2 -- [GitHub](https://github.com/KomputeProject/kompute) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 51 Β· πŸ“₯ 110 Β· πŸ“¦ 2 Β· πŸ“‹ 160 - 32% open Β· ⏱️ 04.01.2022): +- [GitHub](https://github.com/KomputeProject/kompute) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 54 Β· πŸ“₯ 130 Β· πŸ“¦ 2 Β· πŸ“‹ 170 - 33% open Β· ⏱️ 30.01.2022): ``` - git clone https://github.com/EthicalML/vulkan-kompute + git clone https://github.com/KomputeProject/kompute ``` -- [PyPi](https://pypi.org/project/kp) (πŸ“₯ 110 / month Β· ⏱️ 15.09.2021): +- [PyPi](https://pypi.org/project/kp) (πŸ“₯ 150 / month Β· ⏱️ 15.09.2021): ``` pip install kp ```
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cuSignal (πŸ₯‰19 Β· ⭐ 560) - GPU accelerated signal processing. Apache-2 +
cuSignal (πŸ₯‰19 Β· ⭐ 570) - GPU accelerated signal processing. Apache-2 -- [GitHub](https://github.com/rapidsai/cusignal) (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 80 Β· πŸ“‹ 120 - 12% open Β· ⏱️ 08.12.2021): +- [GitHub](https://github.com/rapidsai/cusignal) (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 81 Β· πŸ“‹ 130 - 11% open Β· ⏱️ 28.01.2022): ``` git clone https://github.com/rapidsai/cusignal @@ -7903,11 +8538,11 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize
Show 5 hidden projects... -- GPUtil (πŸ₯‰22 Β· ⭐ 810 Β· πŸ’€) - A Python module for getting the GPU status from NVIDA GPUs using.. MIT +- GPUtil (πŸ₯‰23 Β· ⭐ 820 Β· πŸ’€) - A Python module for getting the GPU status from NVIDA GPUs using.. MIT - py3nvml (πŸ₯‰22 Β· ⭐ 200) - Python 3 Bindings for NVML library. Get NVIDIA GPU status inside your.. BSD-3 - nvidia-ml-py3 (πŸ₯‰20 Β· ⭐ 72 Β· πŸ’€) - Python 3 Bindings for the NVIDIA Management Library. BSD-3 +- ipyexperiments (πŸ₯‰16 Β· ⭐ 140) - jupyter/ipython experiment containers for GPU and.. Apache-2 - SpeedTorch (πŸ₯‰15 Β· ⭐ 650 Β· πŸ’€) - Library for faster pinned CPU - GPU transfer in Pytorch. MIT -- ipyexperiments (πŸ₯‰15 Β· ⭐ 140) - jupyter/ipython experiment containers for GPU and.. Apache-2

@@ -7919,48 +8554,40 @@ _Libraries that extend TensorFlow with additional capabilities._
TF Addons (πŸ₯‡37 Β· ⭐ 1.4K) - Useful extra functionality for TensorFlow 2.x maintained by.. Apache-2 -- [GitHub](https://github.com/tensorflow/addons) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 480 Β· πŸ“¦ 5.1K Β· πŸ“‹ 920 - 23% open Β· ⏱️ 03.01.2022): +- [GitHub](https://github.com/tensorflow/addons) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 490 Β· πŸ“¦ 5.3K Β· πŸ“‹ 920 - 23% open Β· ⏱️ 01.02.2022): ``` git clone https://github.com/tensorflow/addons ``` -- [PyPi](https://pypi.org/project/tensorflow-addons) (πŸ“₯ 6.9M / month Β· πŸ“¦ 140 Β· ⏱️ 10.11.2021): +- [PyPi](https://pypi.org/project/tensorflow-addons) (πŸ“₯ 6.4M / month Β· πŸ“¦ 140 Β· ⏱️ 10.11.2021): ``` pip install tensorflow-addons ```
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tensor2tensor (πŸ₯‡35 Β· ⭐ 12K) - Library of deep learning models and datasets designed to.. Apache-2 - -- [GitHub](https://github.com/tensorflow/tensor2tensor) (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 2.9K Β· πŸ“¦ 1.1K Β· πŸ“‹ 1.2K - 45% open Β· ⏱️ 12.01.2022): - - ``` - git clone https://github.com/tensorflow/tensor2tensor - ``` -- [PyPi](https://pypi.org/project/tensor2tensor) (πŸ“₯ 160K / month Β· πŸ“¦ 93 Β· ⏱️ 17.06.2020): - ``` - pip install tensor2tensor - ``` -
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TensorFlow Datasets (πŸ₯‡35 Β· ⭐ 3.1K) - TFDS is a collection of datasets ready to use with.. Apache-2 +
TensorFlow Datasets (πŸ₯‡36 Β· ⭐ 3.2K) - TFDS is a collection of datasets ready to use with.. Apache-2 -- [GitHub](https://github.com/tensorflow/datasets) (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 1.2K Β· πŸ“‹ 1.1K - 45% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/tensorflow/datasets) (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 1.2K Β· πŸ“‹ 1.1K - 46% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/tensorflow/datasets ``` -- [PyPi](https://pypi.org/project/tensorflow-datasets) (πŸ“₯ 1.4M / month Β· πŸ“¦ 140 Β· ⏱️ 28.07.2021): +- [PyPi](https://pypi.org/project/tensorflow-datasets) (πŸ“₯ 1.3M / month Β· πŸ“¦ 150 Β· ⏱️ 31.01.2022): ``` pip install tensorflow-datasets ``` +- [Conda](https://anaconda.org/conda-forge/tensorflow-datasets) (πŸ“₯ 3.1K Β· ⏱️ 17.08.2021): + ``` + conda install -c conda-forge tensorflow-datasets + ```
-
tensorflow-hub (πŸ₯ˆ34 Β· ⭐ 3K Β· πŸ“‰) - A library for transfer learning by reusing parts of.. Apache-2 +
tensorflow-hub (πŸ₯ˆ34 Β· ⭐ 3K) - A library for transfer learning by reusing parts of.. Apache-2 -- [GitHub](https://github.com/tensorflow/hub) (πŸ‘¨β€πŸ’» 83 Β· πŸ”€ 1.6K Β· πŸ“¦ 9.9K Β· πŸ“‹ 640 - 2% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/tensorflow/hub) (πŸ‘¨β€πŸ’» 83 Β· πŸ”€ 1.6K Β· πŸ“¦ 10K Β· πŸ“‹ 640 - 2% open Β· ⏱️ 06.02.2022): ``` git clone https://github.com/tensorflow/hub ``` -- [PyPi](https://pypi.org/project/tensorflow-hub) (πŸ“₯ 2.7M / month Β· πŸ“¦ 280 Β· ⏱️ 14.04.2021): +- [PyPi](https://pypi.org/project/tensorflow-hub) (πŸ“₯ 3.2M / month Β· πŸ“¦ 280 Β· ⏱️ 14.04.2021): ``` pip install tensorflow-hub ``` @@ -7969,38 +8596,50 @@ _Libraries that extend TensorFlow with additional capabilities._ conda install -c conda-forge tensorflow-hub ```
-
TensorFlow Transform (πŸ₯ˆ32 Β· ⭐ 900) - Input pipeline framework. Apache-2 +
tensor2tensor (πŸ₯ˆ33 Β· ⭐ 12K Β· πŸ“‰) - Library of deep learning models and datasets designed.. Apache-2 -- [GitHub](https://github.com/tensorflow/transform) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 180 Β· πŸ“¦ 660 Β· πŸ“‹ 170 - 12% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/tensorflow/tensor2tensor) (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 2.9K Β· πŸ“¦ 1.1K Β· πŸ“‹ 1.2K - 45% open Β· ⏱️ 12.01.2022): ``` - git clone https://github.com/tensorflow/transform + git clone https://github.com/tensorflow/tensor2tensor ``` -- [PyPi](https://pypi.org/project/tensorflow-transform) (πŸ“₯ 8M / month Β· πŸ“¦ 54 Β· ⏱️ 02.12.2021): +- [PyPi](https://pypi.org/project/tensor2tensor) (πŸ“₯ 50K / month Β· πŸ“¦ 93 Β· ⏱️ 17.06.2020): ``` - pip install tensorflow-transform + pip install tensor2tensor ```
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TF Model Optimization (πŸ₯ˆ31 Β· ⭐ 1.2K) - A toolkit to optimize ML models for deployment for.. Apache-2 +
TF Model Optimization (πŸ₯ˆ32 Β· ⭐ 1.2K) - A toolkit to optimize ML models for deployment for.. Apache-2 -- [GitHub](https://github.com/tensorflow/model-optimization) (πŸ‘¨β€πŸ’» 64 Β· πŸ”€ 250 Β· πŸ“¦ 1.4K Β· πŸ“‹ 280 - 47% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/tensorflow/model-optimization) (πŸ‘¨β€πŸ’» 65 Β· πŸ”€ 270 Β· πŸ“¦ 1.5K Β· πŸ“‹ 300 - 50% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/tensorflow/model-optimization ``` -- [PyPi](https://pypi.org/project/tensorflow-model-optimization) (πŸ“₯ 150K / month Β· πŸ“¦ 13 Β· ⏱️ 30.09.2021): +- [PyPi](https://pypi.org/project/tensorflow-model-optimization) (πŸ“₯ 180K / month Β· πŸ“¦ 19 Β· ⏱️ 09.02.2022): ``` pip install tensorflow-model-optimization ```
+
TensorFlow Transform (πŸ₯ˆ32 Β· ⭐ 900) - Input pipeline framework. Apache-2 + +- [GitHub](https://github.com/tensorflow/transform) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 180 Β· πŸ“¦ 690 Β· πŸ“‹ 180 - 13% open Β· ⏱️ 09.02.2022): + + ``` + git clone https://github.com/tensorflow/transform + ``` +- [PyPi](https://pypi.org/project/tensorflow-transform) (πŸ“₯ 8.9M / month Β· πŸ“¦ 55 Β· ⏱️ 21.01.2022): + ``` + pip install tensorflow-transform + ``` +
Keras-Preprocessing (πŸ₯‰30 Β· ⭐ 1K Β· πŸ’€) - Utilities for working with image data, text data, and.. MIT -- [GitHub](https://github.com/keras-team/keras-preprocessing) (πŸ‘¨β€πŸ’» 50 Β· πŸ”€ 430 Β· πŸ“‹ 190 - 48% open Β· ⏱️ 04.02.2021): +- [GitHub](https://github.com/keras-team/keras-preprocessing) (πŸ‘¨β€πŸ’» 50 Β· πŸ”€ 440 Β· πŸ“‹ 190 - 48% open Β· ⏱️ 04.02.2021): ``` git clone https://github.com/keras-team/keras-preprocessing ``` -- [PyPi](https://pypi.org/project/keras-preprocessing) (πŸ“₯ 8M / month Β· πŸ“¦ 1.5K Β· ⏱️ 14.05.2020): +- [PyPi](https://pypi.org/project/keras-preprocessing) (πŸ“₯ 8.8M / month Β· πŸ“¦ 1.5K Β· ⏱️ 14.05.2020): ``` pip install keras-preprocessing ``` @@ -8009,93 +8648,110 @@ _Libraries that extend TensorFlow with additional capabilities._ conda install -c conda-forge keras-preprocessing ```
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TensorFlow I/O (πŸ₯‰29 Β· ⭐ 520) - Dataset, streaming, and file system extensions.. Apache-2 +
TensorFlow I/O (πŸ₯‰30 Β· ⭐ 530) - Dataset, streaming, and file system extensions.. Apache-2 -- [GitHub](https://github.com/tensorflow/io) (πŸ‘¨β€πŸ’» 84 Β· πŸ”€ 210 Β· πŸ“‹ 490 - 32% open Β· ⏱️ 04.01.2022): +- [GitHub](https://github.com/tensorflow/io) (πŸ‘¨β€πŸ’» 88 Β· πŸ”€ 220 Β· πŸ“‹ 490 - 33% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/tensorflow/io ``` -- [PyPi](https://pypi.org/project/tensorflow-io) (πŸ“₯ 150K / month Β· πŸ“¦ 15 Β· ⏱️ 15.12.2021): +- [PyPi](https://pypi.org/project/tensorflow-io) (πŸ“₯ 170K / month Β· πŸ“¦ 18 Β· ⏱️ 04.02.2022): ``` pip install tensorflow-io ```
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efficientnet (πŸ₯‰26 Β· ⭐ 1.9K) - Implementation of EfficientNet model. Keras and.. Apache-2 +
efficientnet (πŸ₯‰27 Β· ⭐ 1.9K Β· πŸ’€) - Implementation of EfficientNet model. Keras and.. Apache-2 -- [GitHub](https://github.com/qubvel/efficientnet) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 430 Β· πŸ“₯ 200K Β· πŸ“¦ 860 Β· πŸ“‹ 120 - 51% open Β· ⏱️ 16.07.2021): +- [GitHub](https://github.com/qubvel/efficientnet) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 440 Β· πŸ“₯ 200K Β· πŸ“¦ 880 Β· πŸ“‹ 120 - 51% open Β· ⏱️ 16.07.2021): ``` git clone https://github.com/qubvel/efficientnet ``` -- [PyPi](https://pypi.org/project/efficientnet) (πŸ“₯ 70K / month Β· πŸ“¦ 7 Β· ⏱️ 15.09.2020): +- [PyPi](https://pypi.org/project/efficientnet) (πŸ“₯ 79K / month Β· πŸ“¦ 7 Β· ⏱️ 15.09.2020): ``` pip install efficientnet ``` +- [Conda](https://anaconda.org/anaconda/efficientnet) (πŸ“₯ 15 Β· ⏱️ 14.01.2022): + ``` + conda install -c anaconda efficientnet + ```
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Neural Structured Learning (πŸ₯‰26 Β· ⭐ 890) - Training neural models with structured signals. Apache-2 +
Neural Structured Learning (πŸ₯‰26 Β· ⭐ 900) - Training neural models with structured signals. Apache-2 -- [GitHub](https://github.com/tensorflow/neural-structured-learning) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 160 Β· πŸ“¦ 160 Β· πŸ“‹ 60 - 5% open Β· ⏱️ 04.01.2022): +- [GitHub](https://github.com/tensorflow/neural-structured-learning) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 170 Β· πŸ“¦ 170 Β· πŸ“‹ 61 - 4% open Β· ⏱️ 01.02.2022): ``` git clone https://github.com/tensorflow/neural-structured-learning ``` -- [PyPi](https://pypi.org/project/neural-structured-learning) (πŸ“₯ 9.6K / month Β· πŸ“¦ 2 Β· ⏱️ 18.08.2020): +- [PyPi](https://pypi.org/project/neural-structured-learning) (πŸ“₯ 11K / month Β· πŸ“¦ 2 Β· ⏱️ 18.08.2020): ``` pip install neural-structured-learning ```
TensorFlow Cloud (πŸ₯‰24 Β· ⭐ 320) - The TensorFlow Cloud repository provides APIs that.. Apache-2 -- [GitHub](https://github.com/tensorflow/cloud) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 64 Β· πŸ“¦ 120 Β· πŸ“‹ 80 - 67% open Β· ⏱️ 04.01.2022): +- [GitHub](https://github.com/tensorflow/cloud) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 66 Β· πŸ“¦ 120 Β· πŸ“‹ 81 - 67% open Β· ⏱️ 04.01.2022): ``` git clone https://github.com/tensorflow/cloud ``` -- [PyPi](https://pypi.org/project/tensorflow-cloud) (πŸ“₯ 330K / month Β· πŸ“¦ 1 Β· ⏱️ 17.06.2021): +- [PyPi](https://pypi.org/project/tensorflow-cloud) (πŸ“₯ 260K / month Β· πŸ“¦ 1 Β· ⏱️ 17.06.2021): ``` pip install tensorflow-cloud ```
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TensorNets (πŸ₯‰20 Β· ⭐ 1K Β· πŸ’€) - High level network definitions with pre-trained weights in.. MIT +
tffm (πŸ₯‰21 Β· ⭐ 780) - TensorFlow implementation of an arbitrary order Factorization Machine. MIT -- [GitHub](https://github.com/taehoonlee/tensornets) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 190 Β· πŸ“¦ 42 Β· πŸ“‹ 58 - 27% open Β· ⏱️ 02.01.2021): +- [GitHub](https://github.com/geffy/tffm) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 190 Β· πŸ“¦ 11 Β· πŸ“‹ 40 - 45% open Β· ⏱️ 17.01.2022): ``` - git clone https://github.com/taehoonlee/tensornets + git clone https://github.com/geffy/tffm ``` -- [PyPi](https://pypi.org/project/tensornets) (πŸ“₯ 76 / month Β· πŸ“¦ 4 Β· ⏱️ 31.03.2020): +- [PyPi](https://pypi.org/project/tffm) (πŸ“₯ 2.1K / month Β· πŸ“¦ 1 Β· ⏱️ 17.01.2022): ``` - pip install tensornets + pip install tffm ```
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Saliency (πŸ₯‰19 Β· ⭐ 760) - Framework-agnostic implementation for state-of-the-art saliency.. Apache-2 +
TF Compression (πŸ₯‰21 Β· ⭐ 580 Β· πŸ“ˆ) - Data compression in TensorFlow. Apache-2 -- [GitHub](https://github.com/PAIR-code/saliency) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 160 Β· πŸ“¦ 19 Β· πŸ“‹ 40 - 35% open Β· ⏱️ 28.07.2021): +- [GitHub](https://github.com/tensorflow/compression) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 210 Β· πŸ“‹ 79 - 2% open Β· ⏱️ 09.02.2022): ``` - git clone https://github.com/PAIR-code/saliency + git clone https://github.com/tensorflow/compression ``` -- [PyPi](https://pypi.org/project/saliency) (πŸ“₯ 600 / month Β· πŸ“¦ 3 Β· ⏱️ 03.05.2021): +- [PyPi](https://pypi.org/project/tensorflow-compression) (πŸ“₯ 990 / month Β· πŸ“¦ 1 Β· ⏱️ 09.02.2022): ``` - pip install saliency + pip install tensorflow-compression ```
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TF Compression (πŸ₯‰17 Β· ⭐ 570) - Data compression in TensorFlow. Apache-2 +
Saliency (πŸ₯‰20 Β· ⭐ 760 Β· πŸ’€) - Framework-agnostic implementation for state-of-the-art.. Apache-2 -- [GitHub](https://github.com/tensorflow/compression) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 200 Β· πŸ“‹ 76 - 3% open Β· ⏱️ 09.01.2022): +- [GitHub](https://github.com/PAIR-code/saliency) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 160 Β· πŸ“¦ 21 Β· πŸ“‹ 40 - 35% open Β· ⏱️ 28.07.2021): ``` - git clone https://github.com/tensorflow/compression + git clone https://github.com/PAIR-code/saliency ``` -- [PyPi](https://pypi.org/project/tensorflow-compression) (πŸ“₯ 420 / month Β· πŸ“¦ 1 Β· ⏱️ 14.05.2021): +- [PyPi](https://pypi.org/project/saliency) (πŸ“₯ 740 / month Β· πŸ“¦ 3 Β· ⏱️ 03.05.2021): ``` - pip install tensorflow-compression + pip install saliency ```
Show 1 hidden projects... -- tffm (πŸ₯‰20 Β· ⭐ 770 Β· πŸ’€) - TensorFlow implementation of an arbitrary order Factorization Machine. MIT +- TensorNets (πŸ₯‰21 Β· ⭐ 1K Β· πŸ’€) - High level network definitions with pre-trained weights in.. MIT +
+
+ +## Jax Utilities + +Back to top + +_Libraries that extend Jax with additional capabilities._ + +
Show 2 hidden projects... + +- equinox (πŸ₯‡18 Β· ⭐ 260 Β· βž•) - Callable PyTrees and filtered JIT/grad transformations =.. Apache-2 +- jaxdf (πŸ₯‰8 Β· ⭐ 43 Β· 🐣) - A JAX-based research framework for writing differentiable.. ❗️LGPL-3.0

@@ -8107,12 +8763,12 @@ _Libraries that extend scikit-learn with additional capabilities._
imbalanced-learn (πŸ₯‡36 Β· ⭐ 5.7K) - A Python Package to Tackle the Curse of Imbalanced.. MIT -- [GitHub](https://github.com/scikit-learn-contrib/imbalanced-learn) (πŸ‘¨β€πŸ’» 61 Β· πŸ”€ 1.2K Β· πŸ“¦ 8.8K Β· πŸ“‹ 500 - 12% open Β· ⏱️ 11.01.2022): +- [GitHub](https://github.com/scikit-learn-contrib/imbalanced-learn) (πŸ‘¨β€πŸ’» 62 Β· πŸ”€ 1.2K Β· πŸ“¦ 9.2K Β· πŸ“‹ 510 - 12% open Β· ⏱️ 25.01.2022): ``` git clone https://github.com/scikit-learn-contrib/imbalanced-learn ``` -- [PyPi](https://pypi.org/project/imbalanced-learn) (πŸ“₯ 2.6M / month Β· πŸ“¦ 240 Β· ⏱️ 11.01.2022): +- [PyPi](https://pypi.org/project/imbalanced-learn) (πŸ“₯ 2.9M / month Β· πŸ“¦ 240 Β· ⏱️ 11.01.2022): ``` pip install imbalanced-learn ``` @@ -8123,12 +8779,12 @@ _Libraries that extend scikit-learn with additional capabilities._
MLxtend (πŸ₯‡35 Β· ⭐ 3.8K) - A library of extension and helper modules for Pythons data.. BSD-3 -- [GitHub](https://github.com/rasbt/mlxtend) (πŸ‘¨β€πŸ’» 85 Β· πŸ”€ 730 Β· πŸ“¦ 5K Β· πŸ“‹ 400 - 24% open Β· ⏱️ 04.01.2022): +- [GitHub](https://github.com/rasbt/mlxtend) (πŸ‘¨β€πŸ’» 86 Β· πŸ”€ 730 Β· πŸ“¦ 5.1K Β· πŸ“‹ 400 - 24% open Β· ⏱️ 19.01.2022): ``` git clone https://github.com/rasbt/mlxtend ``` -- [PyPi](https://pypi.org/project/mlxtend) (πŸ“₯ 1.5M / month Β· πŸ“¦ 140 Β· ⏱️ 03.09.2021): +- [PyPi](https://pypi.org/project/mlxtend) (πŸ“₯ 2M / month Β· πŸ“¦ 140 Β· ⏱️ 03.09.2021): ``` pip install mlxtend ``` @@ -8137,14 +8793,14 @@ _Libraries that extend scikit-learn with additional capabilities._ conda install -c conda-forge mlxtend ```
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category_encoders (πŸ₯ˆ33 Β· ⭐ 1.8K Β· πŸ“‰) - A library of sklearn compatible categorical variable.. BSD-3 +
category_encoders (πŸ₯ˆ31 Β· ⭐ 1.8K Β· πŸ“‰) - A library of sklearn compatible categorical variable.. BSD-3 -- [GitHub](https://github.com/scikit-learn-contrib/category_encoders) (πŸ‘¨β€πŸ’» 48 Β· πŸ”€ 340 Β· πŸ“¦ 2.9K Β· πŸ“‹ 240 - 32% open Β· ⏱️ 16.11.2021): +- [GitHub](https://github.com/scikit-learn-contrib/category_encoders) (πŸ‘¨β€πŸ’» 48 Β· πŸ”€ 340 Β· πŸ“¦ 3K Β· πŸ“‹ 240 - 32% open Β· ⏱️ 16.11.2021): ``` git clone https://github.com/scikit-learn-contrib/category_encoders ``` -- [PyPi](https://pypi.org/project/category_encoders) (πŸ“₯ 860K / month Β· πŸ“¦ 23 Β· ⏱️ 14.10.2018): +- [PyPi](https://pypi.org/project/category_encoders) (πŸ“₯ 1.2M / month Β· πŸ“¦ 23 Β· ⏱️ 14.10.2018): ``` pip install category_encoders ``` @@ -8153,42 +8809,38 @@ _Libraries that extend scikit-learn with additional capabilities._ conda install -c conda-forge category_encoders ```
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fancyimpute (πŸ₯ˆ25 Β· ⭐ 1K) - Multivariate imputation and matrix completion algorithms.. Apache-2 +
scikit-opt (πŸ₯ˆ26 Β· ⭐ 2.9K) - Genetic Algorithm, Particle Swarm Optimization, Simulated.. MIT -- [GitHub](https://github.com/iskandr/fancyimpute) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 160 Β· πŸ“¦ 1.1K Β· πŸ“‹ 110 - 0% open Β· ⏱️ 21.10.2021): +- [GitHub](https://github.com/guofei9987/scikit-opt) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 700 Β· πŸ“¦ 59 Β· πŸ“‹ 130 - 22% open Β· ⏱️ 16.01.2022): ``` - git clone https://github.com/iskandr/fancyimpute + git clone https://github.com/guofei9987/scikit-opt ``` -- [PyPi](https://pypi.org/project/fancyimpute) (πŸ“₯ 9.6K / month Β· πŸ“¦ 28 Β· ⏱️ 21.10.2021): +- [PyPi](https://pypi.org/project/scikit-opt) (πŸ“₯ 1.2K / month Β· πŸ“¦ 6 Β· ⏱️ 14.01.2022): ``` - pip install fancyimpute + pip install scikit-opt ```
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scikit-lego (πŸ₯ˆ25 Β· ⭐ 680) - Extra blocks for scikit-learn pipelines. MIT +
fancyimpute (πŸ₯ˆ26 Β· ⭐ 1K) - Multivariate imputation and matrix completion algorithms.. Apache-2 -- [GitHub](https://github.com/koaning/scikit-lego) (πŸ‘¨β€πŸ’» 48 Β· πŸ”€ 77 Β· πŸ“¦ 39 Β· πŸ“‹ 240 - 13% open Β· ⏱️ 21.12.2021): +- [GitHub](https://github.com/iskandr/fancyimpute) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 170 Β· πŸ“¦ 1.1K Β· πŸ“‹ 110 - 0% open Β· ⏱️ 21.10.2021): ``` - git clone https://github.com/koaning/scikit-lego - ``` -- [PyPi](https://pypi.org/project/scikit-lego) (πŸ“₯ 22K / month Β· πŸ“¦ 6 Β· ⏱️ 09.12.2021): - ``` - pip install scikit-lego + git clone https://github.com/iskandr/fancyimpute ``` -- [Conda](https://anaconda.org/conda-forge/scikit-lego) (πŸ“₯ 17K Β· ⏱️ 09.12.2021): +- [PyPi](https://pypi.org/project/fancyimpute) (πŸ“₯ 12K / month Β· πŸ“¦ 29 Β· ⏱️ 21.10.2021): ``` - conda install -c conda-forge scikit-lego + pip install fancyimpute ```
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sklearn-contrib-lightning (πŸ₯ˆ24 Β· ⭐ 1.5K) - Large-scale linear classification, regression and.. BSD-3 +
sklearn-contrib-lightning (πŸ₯ˆ25 Β· ⭐ 1.5K) - Large-scale linear classification, regression and.. BSD-3 -- [GitHub](https://github.com/scikit-learn-contrib/lightning) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 190 Β· πŸ“₯ 100 Β· πŸ“¦ 97 Β· πŸ“‹ 91 - 54% open Β· ⏱️ 09.01.2022): +- [GitHub](https://github.com/scikit-learn-contrib/lightning) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 200 Β· πŸ“₯ 120 Β· πŸ“¦ 99 Β· πŸ“‹ 92 - 55% open Β· ⏱️ 30.01.2022): ``` git clone https://github.com/scikit-learn-contrib/lightning ``` -- [PyPi](https://pypi.org/project/sklearn-contrib-lightning) (πŸ“₯ 1.7K / month Β· πŸ“¦ 6 Β· ⏱️ 15.06.2021): +- [PyPi](https://pypi.org/project/sklearn-contrib-lightning) (πŸ“₯ 3.9K / month Β· πŸ“¦ 6 Β· ⏱️ 30.01.2022): ``` pip install sklearn-contrib-lightning ``` @@ -8197,74 +8849,78 @@ _Libraries that extend scikit-learn with additional capabilities._ conda install -c conda-forge sklearn-contrib-lightning ```
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scikit-opt (πŸ₯‰23 Β· ⭐ 2.8K) - Genetic Algorithm, Particle Swarm Optimization, Simulated.. MIT +
scikit-lego (πŸ₯ˆ25 Β· ⭐ 700) - Extra blocks for scikit-learn pipelines. MIT -- [GitHub](https://github.com/guofei9987/scikit-opt) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 680 Β· πŸ“¦ 59 Β· πŸ“‹ 130 - 24% open Β· ⏱️ 10.01.2022): +- [GitHub](https://github.com/koaning/scikit-lego) (πŸ‘¨β€πŸ’» 48 Β· πŸ”€ 77 Β· πŸ“¦ 40 Β· πŸ“‹ 240 - 13% open Β· ⏱️ 21.12.2021): ``` - git clone https://github.com/guofei9987/scikit-opt + git clone https://github.com/koaning/scikit-lego ``` -- [PyPi](https://pypi.org/project/scikit-opt) (πŸ“₯ 1.1K / month Β· πŸ“¦ 4 Β· ⏱️ 28.06.2021): +- [PyPi](https://pypi.org/project/scikit-lego) (πŸ“₯ 17K / month Β· πŸ“¦ 6 Β· ⏱️ 09.12.2021): ``` - pip install scikit-opt + pip install scikit-lego + ``` +- [Conda](https://anaconda.org/conda-forge/scikit-lego) (πŸ“₯ 17K Β· ⏱️ 09.12.2021): + ``` + conda install -c conda-forge scikit-lego ```
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iterative-stratification (πŸ₯‰21 Β· ⭐ 620) - scikit-learn cross validators for iterative.. BSD-3 +
iterative-stratification (πŸ₯‰22 Β· ⭐ 630) - scikit-learn cross validators for iterative.. BSD-3 - [GitHub](https://github.com/trent-b/iterative-stratification) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 57 Β· πŸ“¦ 180 Β· πŸ“‹ 19 - 21% open Β· ⏱️ 11.11.2021): ``` git clone https://github.com/trent-b/iterative-stratification ``` -- [PyPi](https://pypi.org/project/iterative-stratification) (πŸ“₯ 89K / month Β· πŸ“¦ 8 Β· ⏱️ 03.10.2021): +- [PyPi](https://pypi.org/project/iterative-stratification) (πŸ“₯ 150K / month Β· πŸ“¦ 8 Β· ⏱️ 03.10.2021): ``` pip install iterative-stratification ```
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combo (πŸ₯‰21 Β· ⭐ 560) - (AAAI 20) A Python Toolbox for Machine Learning Model Combination. BSD-2 xgboost +
combo (πŸ₯‰21 Β· ⭐ 570) - (AAAI 20) A Python Toolbox for Machine Learning Model Combination. BSD-2 xgboost - [GitHub](https://github.com/yzhao062/combo) (πŸ‘¨β€πŸ’» 1 Β· πŸ”€ 95 Β· πŸ“¦ 440 Β· πŸ“‹ 12 - 75% open Β· ⏱️ 02.10.2021): ``` git clone https://github.com/yzhao062/combo ``` -- [PyPi](https://pypi.org/project/combo) (πŸ“₯ 53K / month Β· πŸ“¦ 1 Β· ⏱️ 23.12.2020): +- [PyPi](https://pypi.org/project/combo) (πŸ“₯ 44K / month Β· πŸ“¦ 1 Β· ⏱️ 23.12.2020): ``` pip install combo ```
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DESlib (πŸ₯‰18 Β· ⭐ 370) - A Python library for dynamic classifier and ensemble selection. BSD-3 +
DESlib (πŸ₯‰20 Β· ⭐ 370) - A Python library for dynamic classifier and ensemble selection. BSD-3 - [GitHub](https://github.com/scikit-learn-contrib/DESlib) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 73 Β· πŸ“¦ 22 Β· πŸ“‹ 140 - 9% open Β· ⏱️ 10.10.2021): ``` git clone https://github.com/scikit-learn-contrib/DESlib ``` -- [PyPi](https://pypi.org/project/deslib) (πŸ“₯ 990 / month Β· πŸ“¦ 2 Β· ⏱️ 08.02.2021): +- [PyPi](https://pypi.org/project/deslib) (πŸ“₯ 14K / month Β· πŸ“¦ 2 Β· ⏱️ 08.02.2021): ``` pip install deslib ```
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scikit-tda (πŸ₯‰18 Β· ⭐ 320) - Topological Data Analysis for Python. MIT +
scikit-tda (πŸ₯‰17 Β· ⭐ 330) - Topological Data Analysis for Python. MIT -- [GitHub](https://github.com/scikit-tda/scikit-tda) (πŸ‘¨β€πŸ’» 3 Β· πŸ”€ 39 Β· πŸ“¦ 24 Β· πŸ“‹ 16 - 75% open Β· ⏱️ 03.08.2021): +- [GitHub](https://github.com/scikit-tda/scikit-tda) (πŸ‘¨β€πŸ’» 3 Β· πŸ”€ 40 Β· πŸ“¦ 25 Β· πŸ“‹ 17 - 76% open Β· ⏱️ 03.08.2021): ``` git clone https://github.com/scikit-tda/scikit-tda ``` -- [PyPi](https://pypi.org/project/scikit-tda) (πŸ“₯ 3.7K / month Β· ⏱️ 03.08.2021): +- [PyPi](https://pypi.org/project/scikit-tda) (πŸ“₯ 5K / month Β· ⏱️ 03.08.2021): ``` pip install scikit-tda ```
Show 6 hidden projects... +- scikit-multilearn (πŸ₯ˆ25 Β· ⭐ 720 Β· πŸ’€) - A scikit-learn based module for multi-label et. al... BSD-2 - sklearn-crfsuite (πŸ₯ˆ25 Β· ⭐ 390 Β· πŸ’€) - scikit-learn inspired API for CRFsuite. MIT -- scikit-multilearn (πŸ₯‰23 Β· ⭐ 710 Β· πŸ’€) - A scikit-learn based module for multi-label et. al... BSD-2 -- skope-rules (πŸ₯‰20 Β· ⭐ 430 Β· πŸ’€) - machine learning with logical rules in Python. ❗️BSD-1-Clause -- celer (πŸ₯‰19 Β· ⭐ 130) - Fast solver for L1-type problems: Lasso, sparse Logisitic regression,.. BSD-3 +- skope-rules (πŸ₯‰21 Β· ⭐ 440 Β· πŸ’€) - machine learning with logical rules in Python. ❗️BSD-1-Clause +- celer (πŸ₯‰18 Β· ⭐ 130) - Fast solver for L1-type problems: Lasso, sparse Logisitic regression,.. BSD-3 - skggm (πŸ₯‰17 Β· ⭐ 190 Β· πŸ’€) - Scikit-learn compatible estimation of general graphical models. MIT -- dabl (πŸ₯‰15 Β· ⭐ 110) - Data Analysis Baseline Library. BSD-3 +- dabl (πŸ₯‰15 Β· ⭐ 110 Β· πŸ’€) - Data Analysis Baseline Library. BSD-3

@@ -8274,176 +8930,216 @@ _Libraries that extend scikit-learn with additional capabilities._ _Libraries that extend Pytorch with additional capabilities._ -
PML (πŸ₯‡32 Β· ⭐ 4K) - The easiest way to use deep metric learning in your application. Modular,.. MIT +
PML (πŸ₯‡32 Β· ⭐ 4.1K) - The easiest way to use deep metric learning in your application. Modular,.. MIT -- [GitHub](https://github.com/KevinMusgrave/pytorch-metric-learning) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 500 Β· πŸ“¦ 180 Β· πŸ“‹ 320 - 12% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/KevinMusgrave/pytorch-metric-learning) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 500 Β· πŸ“¦ 200 Β· πŸ“‹ 320 - 13% open Β· ⏱️ 12.01.2022): ``` git clone https://github.com/KevinMusgrave/pytorch-metric-learning ``` -- [PyPi](https://pypi.org/project/pytorch-metric-learning) (πŸ“₯ 97K / month Β· πŸ“¦ 8 Β· ⏱️ 28.12.2021): +- [PyPi](https://pypi.org/project/pytorch-metric-learning) (πŸ“₯ 160K / month Β· πŸ“¦ 8 Β· ⏱️ 10.02.2022): ``` pip install pytorch-metric-learning ``` -- [Conda](https://anaconda.org/metric-learning/pytorch-metric-learning) (πŸ“₯ 5.4K Β· ⏱️ 28.12.2021): +- [Conda](https://anaconda.org/metric-learning/pytorch-metric-learning) (πŸ“₯ 5.8K Β· ⏱️ 28.12.2021): ``` conda install -c metric-learning pytorch-metric-learning ```
pytorch-optimizer (πŸ₯‡29 Β· ⭐ 2.3K) - torch-optimizer -- collection of optimizers for.. Apache-2 -- [GitHub](https://github.com/jettify/pytorch-optimizer) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 210 Β· πŸ“¦ 430 Β· πŸ“‹ 44 - 36% open Β· ⏱️ 11.11.2021): +- [GitHub](https://github.com/jettify/pytorch-optimizer) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 220 Β· πŸ“¦ 460 Β· πŸ“‹ 44 - 36% open Β· ⏱️ 11.11.2021): ``` git clone https://github.com/jettify/pytorch-optimizer ``` -- [PyPi](https://pypi.org/project/torch_optimizer) (πŸ“₯ 52K / month Β· πŸ“¦ 23 Β· ⏱️ 31.10.2021): +- [PyPi](https://pypi.org/project/torch_optimizer) (πŸ“₯ 79K / month Β· πŸ“¦ 23 Β· ⏱️ 31.10.2021): ``` pip install torch_optimizer ``` +- [Conda](https://anaconda.org/conda-forge/torch-optimizer) (πŸ“₯ 790 Β· ⏱️ 31.10.2021): + ``` + conda install -c conda-forge torch-optimizer + ```
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lightning-flash (πŸ₯‡28 Β· ⭐ 1.3K) - Your PyTorch AI Factory - Flash enables you to easily.. Apache-2 +
lightning-flash (πŸ₯‡28 Β· ⭐ 1.4K) - Your PyTorch AI Factory - Flash enables you to easily.. Apache-2 -- [GitHub](https://github.com/PyTorchLightning/lightning-flash) (πŸ‘¨β€πŸ’» 60 Β· πŸ”€ 130 Β· πŸ“¦ 41 Β· πŸ“‹ 430 - 19% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/PyTorchLightning/lightning-flash) (πŸ‘¨β€πŸ’» 61 Β· πŸ”€ 140 Β· πŸ“¦ 48 Β· πŸ“‹ 420 - 10% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/PyTorchLightning/lightning-flash ``` -- [PyPi](https://pypi.org/project/lightning-flash) (πŸ“₯ 2.3K / month Β· πŸ“¦ 2 Β· ⏱️ 13.12.2021): +- [PyPi](https://pypi.org/project/lightning-flash) (πŸ“₯ 2.4K / month Β· πŸ“¦ 2 Β· ⏱️ 04.02.2022): ``` pip install lightning-flash ``` +- [Conda](https://anaconda.org/conda-forge/lightning-flash) (πŸ“₯ 680 Β· ⏱️ 13.12.2021): + ``` + conda install -c conda-forge lightning-flash + ```
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EfficientNet-PyTorch (πŸ₯ˆ27 Β· ⭐ 6.7K Β· πŸ’€) - A PyTorch implementation of EfficientNet and.. Apache-2 +
EfficientNet-PyTorch (πŸ₯ˆ27 Β· ⭐ 6.8K Β· πŸ’€) - A PyTorch implementation of EfficientNet and.. Apache-2 -- [GitHub](https://github.com/lukemelas/EfficientNet-PyTorch) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 1.3K Β· πŸ“₯ 1.1M Β· πŸ“‹ 260 - 49% open Β· ⏱️ 15.04.2021): +- [GitHub](https://github.com/lukemelas/EfficientNet-PyTorch) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 1.3K Β· πŸ“₯ 1.2M Β· πŸ“‹ 270 - 49% open Β· ⏱️ 15.04.2021): ``` git clone https://github.com/lukemelas/EfficientNet-PyTorch ``` -- [PyPi](https://pypi.org/project/efficientnet-pytorch) (πŸ“₯ 370K / month Β· πŸ“¦ 30 Β· ⏱️ 15.04.2021): +- [PyPi](https://pypi.org/project/efficientnet-pytorch) (πŸ“₯ 790K / month Β· πŸ“¦ 30 Β· ⏱️ 15.04.2021): ``` pip install efficientnet-pytorch ```
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accelerate (πŸ₯ˆ27 Β· ⭐ 2.1K) - A simple way to train and use PyTorch models with multi-.. Apache-2 +
pytorch-summary (πŸ₯ˆ27 Β· ⭐ 3.4K Β· πŸ’€) - Model summary in PyTorch similar to `model.summary()`.. MIT -- [GitHub](https://github.com/huggingface/accelerate) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 120 Β· πŸ“¦ 280 Β· πŸ“‹ 150 - 33% open Β· ⏱️ 11.01.2022): +- [GitHub](https://github.com/sksq96/pytorch-summary) (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 380 Β· πŸ“¦ 4.2K Β· πŸ“‹ 160 - 75% open Β· ⏱️ 10.05.2021): ``` - git clone https://github.com/huggingface/accelerate + git clone https://github.com/sksq96/pytorch-summary ``` -- [PyPi](https://pypi.org/project/accelerate) (πŸ“₯ 37K / month Β· πŸ“¦ 4 Β· ⏱️ 27.09.2021): +- [PyPi](https://pypi.org/project/torchsummary) (πŸ“₯ 63K / month Β· πŸ“¦ 71 Β· ⏱️ 26.09.2018): ``` - pip install accelerate + pip install torchsummary ```
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pytorch-summary (πŸ₯ˆ26 Β· ⭐ 3.4K Β· πŸ’€) - Model summary in PyTorch similar to `model.summary()`.. MIT +
accelerate (πŸ₯ˆ27 Β· ⭐ 2.2K) - A simple way to train and use PyTorch models with multi-.. Apache-2 -- [GitHub](https://github.com/sksq96/pytorch-summary) (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 380 Β· πŸ“¦ 4.1K Β· πŸ“‹ 160 - 75% open Β· ⏱️ 10.05.2021): +- [GitHub](https://github.com/huggingface/accelerate) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 130 Β· πŸ“¦ 310 Β· πŸ“‹ 160 - 36% open Β· ⏱️ 08.02.2022): ``` - git clone https://github.com/sksq96/pytorch-summary + git clone https://github.com/huggingface/accelerate ``` -- [PyPi](https://pypi.org/project/torchsummary) (πŸ“₯ 55K / month Β· πŸ“¦ 71 Β· ⏱️ 26.09.2018): +- [PyPi](https://pypi.org/project/accelerate) (πŸ“₯ 48K / month Β· πŸ“¦ 4 Β· ⏱️ 27.09.2021): ``` - pip install torchsummary + pip install accelerate + ``` +- [Conda](https://anaconda.org/conda-forge/accelerate) (πŸ“₯ 800 Β· ⏱️ 11.10.2021): + ``` + conda install -c conda-forge accelerate ```
torchdiffeq (πŸ₯ˆ25 Β· ⭐ 3.9K) - Differentiable ODE solvers with full GPU support and.. MIT -- [GitHub](https://github.com/rtqichen/torchdiffeq) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 670 Β· πŸ“¦ 180 Β· πŸ“‹ 160 - 17% open Β· ⏱️ 22.09.2021): +- [GitHub](https://github.com/rtqichen/torchdiffeq) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 680 Β· πŸ“¦ 190 Β· πŸ“‹ 160 - 19% open Β· ⏱️ 17.01.2022): ``` git clone https://github.com/rtqichen/torchdiffeq ``` -- [PyPi](https://pypi.org/project/torchdiffeq) (πŸ“₯ 33K / month Β· πŸ“¦ 6 Β· ⏱️ 02.06.2021): +- [PyPi](https://pypi.org/project/torchdiffeq) (πŸ“₯ 19K / month Β· πŸ“¦ 6 Β· ⏱️ 02.06.2021): ``` pip install torchdiffeq ``` +- [Conda](https://anaconda.org/conda-forge/torchdiffeq) (πŸ“₯ 4.6K Β· ⏱️ 03.06.2021): + ``` + conda install -c conda-forge torchdiffeq + ```
Torchmeta (πŸ₯ˆ25 Β· ⭐ 1.5K) - A collection of extensions and data-loaders for few-shot learning.. MIT -- [GitHub](https://github.com/tristandeleu/pytorch-meta) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 190 Β· πŸ“¦ 78 Β· πŸ“‹ 120 - 27% open Β· ⏱️ 20.09.2021): +- [GitHub](https://github.com/tristandeleu/pytorch-meta) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 200 Β· πŸ“¦ 81 Β· πŸ“‹ 120 - 28% open Β· ⏱️ 20.09.2021): ``` git clone https://github.com/tristandeleu/pytorch-meta ``` -- [PyPi](https://pypi.org/project/torchmeta) (πŸ“₯ 1.2K / month Β· ⏱️ 20.09.2021): +- [PyPi](https://pypi.org/project/torchmeta) (πŸ“₯ 1.9K / month Β· ⏱️ 20.09.2021): ``` pip install torchmeta ```
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TabNet (πŸ₯ˆ25 Β· ⭐ 1.5K) - PyTorch implementation of TabNet paper :.. MIT +
SRU (πŸ₯ˆ24 Β· ⭐ 2K Β· πŸ’€) - Training RNNs as Fast as CNNs (https://arxiv.org/abs/1709.02755). MIT + +- [GitHub](https://github.com/asappresearch/sru) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 300 Β· πŸ“¦ 17 Β· πŸ“‹ 120 - 44% open Β· ⏱️ 19.05.2021): + + ``` + git clone https://github.com/asappresearch/sru + ``` +- [PyPi](https://pypi.org/project/sru) (πŸ“₯ 4.2K / month Β· πŸ“¦ 3 Β· ⏱️ 17.06.2021): + ``` + pip install sru + ``` +
+
TabNet (πŸ₯ˆ24 Β· ⭐ 1.6K) - PyTorch implementation of TabNet paper :.. MIT -- [GitHub](https://github.com/dreamquark-ai/tabnet) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 300 Β· πŸ“‹ 200 - 18% open Β· ⏱️ 27.12.2021): +- [GitHub](https://github.com/dreamquark-ai/tabnet) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 320 Β· πŸ“‹ 210 - 18% open Β· ⏱️ 27.12.2021): ``` git clone https://github.com/dreamquark-ai/tabnet ``` -- [PyPi](https://pypi.org/project/pytorch-tabnet) (πŸ“₯ 33K / month Β· πŸ“¦ 7 Β· ⏱️ 02.02.2021): +- [PyPi](https://pypi.org/project/pytorch-tabnet) (πŸ“₯ 23K / month Β· πŸ“¦ 7 Β· ⏱️ 02.02.2021): ``` pip install pytorch-tabnet ``` +- [Conda](https://anaconda.org/conda-forge/pytorch-tabnet) (πŸ“₯ 120 Β· ⏱️ 30.12.2021): + ``` + conda install -c conda-forge pytorch-tabnet + ```
-
SRU (πŸ₯ˆ24 Β· ⭐ 2K Β· πŸ’€) - Training RNNs as Fast as CNNs (https://arxiv.org/abs/1709.02755). MIT +
EfficientNets (πŸ₯ˆ23 Β· ⭐ 1.4K Β· πŸ’€) - Pretrained EfficientNet, EfficientNet-Lite, MixNet,.. Apache-2 -- [GitHub](https://github.com/asappresearch/sru) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 300 Β· πŸ“¦ 17 Β· πŸ“‹ 120 - 44% open Β· ⏱️ 19.05.2021): +- [GitHub](https://github.com/rwightman/gen-efficientnet-pytorch) (πŸ‘¨β€πŸ’» 5 Β· πŸ”€ 190 Β· πŸ“¦ 93 Β· πŸ“‹ 51 - 1% open Β· ⏱️ 08.07.2021): ``` - git clone https://github.com/asappresearch/sru + git clone https://github.com/rwightman/gen-efficientnet-pytorch ``` -- [PyPi](https://pypi.org/project/sru) (πŸ“₯ 2.6K / month Β· πŸ“¦ 3 Β· ⏱️ 17.06.2021): +- [PyPi](https://pypi.org/project/geffnet) (πŸ“₯ 9K / month Β· πŸ“¦ 1 Β· ⏱️ 08.07.2021): ``` - pip install sru + pip install geffnet ```
-
torch-scatter (πŸ₯ˆ24 Β· ⭐ 850) - PyTorch Extension Library of Optimized Scatter Operations. MIT +
Higher (πŸ₯ˆ23 Β· ⭐ 1.3K) - higher is a pytorch library allowing users to obtain higher.. Apache-2 -- [GitHub](https://github.com/rusty1s/pytorch_scatter) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 93 Β· πŸ“‹ 240 - 9% open Β· ⏱️ 13.11.2021): +- [GitHub](https://github.com/facebookresearch/higher) (πŸ‘¨β€πŸ’» 9 Β· πŸ”€ 94 Β· πŸ“¦ 110 Β· πŸ“‹ 98 - 48% open Β· ⏱️ 26.10.2021): ``` - git clone https://github.com/rusty1s/pytorch_scatter + git clone https://github.com/facebookresearch/higher ``` -- [PyPi](https://pypi.org/project/torch-scatter) (πŸ“₯ 28K / month Β· πŸ“¦ 40 Β· ⏱️ 22.10.2021): +- [PyPi](https://pypi.org/project/higher) (πŸ“₯ 10K / month Β· πŸ“¦ 2 Β· ⏱️ 14.07.2020): ``` - pip install torch-scatter + pip install higher ```
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PyTorch Sparse (πŸ₯ˆ23 Β· ⭐ 550) - PyTorch Extension Library of Optimized Autograd Sparse.. MIT +
PyTorch Sparse (πŸ₯ˆ23 Β· ⭐ 560) - PyTorch Extension Library of Optimized Autograd Sparse.. MIT -- [GitHub](https://github.com/rusty1s/pytorch_sparse) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 70 Β· πŸ“‹ 190 - 31% open Β· ⏱️ 13.11.2021): +- [GitHub](https://github.com/rusty1s/pytorch_sparse) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 77 Β· πŸ“‹ 200 - 30% open Β· ⏱️ 09.02.2022): ``` git clone https://github.com/rusty1s/pytorch_sparse ``` -- [PyPi](https://pypi.org/project/torch-sparse) (πŸ“₯ 17K / month Β· πŸ“¦ 32 Β· ⏱️ 08.09.2021): +- [PyPi](https://pypi.org/project/torch-sparse) (πŸ“₯ 20K / month Β· πŸ“¦ 32 Β· ⏱️ 08.09.2021): ``` pip install torch-sparse ``` +- [Conda](https://anaconda.org/conda-forge/pytorch_sparse) (πŸ“₯ 79K Β· ⏱️ 29.06.2021): + ``` + conda install -c conda-forge pytorch_sparse + ```
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EfficientNets (πŸ₯‰22 Β· ⭐ 1.4K) - Pretrained EfficientNet, EfficientNet-Lite, MixNet,.. Apache-2 +
Pytorch Toolbelt (πŸ₯‰22 Β· ⭐ 1.2K) - PyTorch extensions for fast R&D prototyping and Kaggle.. MIT -- [GitHub](https://github.com/rwightman/gen-efficientnet-pytorch) (πŸ‘¨β€πŸ’» 5 Β· πŸ”€ 190 Β· πŸ“¦ 88 Β· πŸ“‹ 51 - 1% open Β· ⏱️ 08.07.2021): +- [GitHub](https://github.com/BloodAxe/pytorch-toolbelt) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 88 Β· πŸ“‹ 23 - 21% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/rwightman/gen-efficientnet-pytorch + git clone https://github.com/BloodAxe/pytorch-toolbelt ``` -- [PyPi](https://pypi.org/project/geffnet) (πŸ“₯ 5.9K / month Β· πŸ“¦ 1 Β· ⏱️ 08.07.2021): +- [PyPi](https://pypi.org/project/pytorch_toolbelt) (πŸ“₯ 15K / month Β· πŸ“¦ 6 Β· ⏱️ 12.08.2021): ``` - pip install geffnet + pip install pytorch_toolbelt ```
-
Pytorch Toolbelt (πŸ₯‰22 Β· ⭐ 1.2K) - PyTorch extensions for fast R&D prototyping and Kaggle.. MIT +
torch-scatter (πŸ₯‰22 Β· ⭐ 890) - PyTorch Extension Library of Optimized Scatter Operations. MIT -- [GitHub](https://github.com/BloodAxe/pytorch-toolbelt) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 87 Β· πŸ“‹ 23 - 21% open Β· ⏱️ 29.12.2021): +- [GitHub](https://github.com/rusty1s/pytorch_scatter) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 97 Β· πŸ“‹ 240 - 9% open Β· ⏱️ 03.02.2022): ``` - git clone https://github.com/BloodAxe/pytorch-toolbelt + git clone https://github.com/rusty1s/pytorch_scatter ``` -- [PyPi](https://pypi.org/project/pytorch_toolbelt) (πŸ“₯ 6.7K / month Β· πŸ“¦ 6 Β· ⏱️ 12.08.2021): +- [PyPi](https://pypi.org/project/torch-scatter) (πŸ“₯ 32K / month Β· πŸ“¦ 40 Β· ⏱️ 22.10.2021): ``` - pip install pytorch_toolbelt + pip install torch-scatter + ``` +- [Conda](https://anaconda.org/conda-forge/pytorch_scatter) (πŸ“₯ 67K Β· ⏱️ 18.08.2021): + ``` + conda install -c conda-forge pytorch_scatter ```
reformer-pytorch (πŸ₯‰21 Β· ⭐ 1.7K) - Reformer, the efficient Transformer, in Pytorch. MIT @@ -8453,39 +9149,43 @@ _Libraries that extend Pytorch with additional capabilities._ ``` git clone https://github.com/lucidrains/reformer-pytorch ``` -- [PyPi](https://pypi.org/project/reformer-pytorch) (πŸ“₯ 5.9K / month Β· ⏱️ 06.11.2021): +- [PyPi](https://pypi.org/project/reformer-pytorch) (πŸ“₯ 5.5K / month Β· ⏱️ 06.11.2021): ``` pip install reformer-pytorch ```
-
Higher (πŸ₯‰21 Β· ⭐ 1.3K) - higher is a pytorch library allowing users to obtain higher.. Apache-2 +
torchsde (πŸ₯‰21 Β· ⭐ 910 Β· πŸ’€) - Differentiable SDE solvers with GPU support and efficient.. Apache-2 -- [GitHub](https://github.com/facebookresearch/higher) (πŸ‘¨β€πŸ’» 9 Β· πŸ”€ 93 Β· πŸ“¦ 100 Β· πŸ“‹ 95 - 47% open Β· ⏱️ 26.10.2021): +- [GitHub](https://github.com/google-research/torchsde) (πŸ‘¨β€πŸ’» 5 Β· πŸ”€ 100 Β· πŸ“¦ 11 Β· πŸ“‹ 44 - 15% open Β· ⏱️ 26.07.2021): ``` - git clone https://github.com/facebookresearch/higher + git clone https://github.com/google-research/torchsde ``` -- [PyPi](https://pypi.org/project/higher) (πŸ“₯ 7.5K / month Β· πŸ“¦ 2 Β· ⏱️ 14.07.2020): +- [PyPi](https://pypi.org/project/torchsde) (πŸ“₯ 14K / month Β· ⏱️ 20.07.2021): ``` - pip install higher + pip install torchsde + ``` +- [Conda](https://anaconda.org/conda-forge/torchsde) (πŸ“₯ 8.5K Β· ⏱️ 12.07.2021): + ``` + conda install -c conda-forge torchsde ```
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tinygrad (πŸ₯‰19 Β· ⭐ 5.1K) - You like pytorch? You like micrograd? You love tinygrad!. MIT +
tinygrad (πŸ₯‰19 Β· ⭐ 5.2K) - You like pytorch? You like micrograd? You love tinygrad!. MIT -- [GitHub](https://github.com/geohot/tinygrad) (πŸ‘¨β€πŸ’» 52 Β· πŸ”€ 570 Β· πŸ“¦ 1 Β· πŸ“‹ 110 - 19% open Β· ⏱️ 06.01.2022): +- [GitHub](https://github.com/geohot/tinygrad) (πŸ‘¨β€πŸ’» 54 Β· πŸ”€ 570 Β· πŸ“¦ 2 Β· πŸ“‹ 110 - 19% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/geohot/tinygrad ```
-
Performer Pytorch (πŸ₯‰19 Β· ⭐ 770) - An implementation of Performer, a linear attention-based.. MIT +
Performer Pytorch (πŸ₯‰19 Β· ⭐ 780) - An implementation of Performer, a linear attention-based.. MIT -- [GitHub](https://github.com/lucidrains/performer-pytorch) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 100 Β· πŸ“¦ 36 Β· πŸ“‹ 70 - 41% open Β· ⏱️ 07.11.2021): +- [GitHub](https://github.com/lucidrains/performer-pytorch) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 100 Β· πŸ“¦ 38 Β· πŸ“‹ 72 - 43% open Β· ⏱️ 02.02.2022): ``` git clone https://github.com/lucidrains/performer-pytorch ``` -- [PyPi](https://pypi.org/project/performer-pytorch) (πŸ“₯ 890 / month Β· πŸ“¦ 4 Β· ⏱️ 07.11.2021): +- [PyPi](https://pypi.org/project/performer-pytorch) (πŸ“₯ 1.5K / month Β· πŸ“¦ 4 Β· ⏱️ 02.02.2022): ``` pip install performer-pytorch ``` @@ -8497,72 +9197,80 @@ _Libraries that extend Pytorch with additional capabilities._ ``` git clone https://github.com/parrt/tensor-sensor ``` -- [PyPi](https://pypi.org/project/tensor-sensor) (πŸ“₯ 1.7K / month Β· ⏱️ 11.12.2021): +- [PyPi](https://pypi.org/project/tensor-sensor) (πŸ“₯ 2.1K / month Β· ⏱️ 11.12.2021): ``` pip install tensor-sensor ``` +- [Conda](https://anaconda.org/conda-forge/tensor-sensor) (πŸ“₯ 160 Β· ⏱️ 11.12.2021): + ``` + conda install -c conda-forge tensor-sensor + ```
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Pywick (πŸ₯‰17 Β· ⭐ 360) - High-level batteries-included neural network training library for.. MIT +
pytorchviz (πŸ₯‰18 Β· ⭐ 2.1K Β· πŸ’€) - A small package to create visualizations of PyTorch execution.. MIT -- [GitHub](https://github.com/achaiah/pywick) (πŸ‘¨β€πŸ’» 4 Β· πŸ”€ 38 Β· πŸ“¦ 5 Β· πŸ“‹ 14 - 14% open Β· ⏱️ 22.10.2021): +- [GitHub](https://github.com/szagoruyko/pytorchviz) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 220 Β· πŸ“¦ 570 Β· πŸ“‹ 52 - 36% open Β· ⏱️ 15.06.2021): ``` - git clone https://github.com/achaiah/pywick - ``` -- [PyPi](https://pypi.org/project/pywick) (πŸ“₯ 50 / month Β· ⏱️ 22.10.2021): - ``` - pip install pywick + git clone https://github.com/szagoruyko/pytorchviz ```
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torchsde (πŸ₯‰16 Β· ⭐ 890) - Differentiable SDE solvers with GPU support and efficient.. Apache-2 +
Torch-Struct (πŸ₯‰18 Β· ⭐ 1K Β· πŸ“ˆ) - Fast, general, and tested differentiable structured.. MIT -- [GitHub](https://github.com/google-research/torchsde) (πŸ‘¨β€πŸ’» 5 Β· πŸ”€ 99 Β· πŸ“¦ 9 Β· πŸ“‹ 43 - 16% open Β· ⏱️ 26.07.2021): +- [GitHub](https://github.com/harvardnlp/pytorch-struct) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 80 Β· πŸ“‹ 54 - 44% open Β· ⏱️ 30.01.2022): ``` - git clone https://github.com/google-research/torchsde + git clone https://github.com/harvardnlp/pytorch-struct + ``` +- [PyPi](https://pypi.org/project/torch-struct) (πŸ“₯ 7.2K / month Β· ⏱️ 14.02.2021): + ``` + pip install torch-struct ```
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Tez (πŸ₯‰16 Β· ⭐ 740) - Tez is a super-simple and lightweight Trainer for PyTorch. It also.. Apache-2 +
Tez (πŸ₯‰17 Β· ⭐ 770) - Tez is a super-simple and lightweight Trainer for PyTorch. It also.. Apache-2 -- [GitHub](https://github.com/abhishekkrthakur/tez) (πŸ‘¨β€πŸ’» 1 Β· πŸ”€ 110 Β· πŸ“¦ 18 Β· πŸ“‹ 28 - 64% open Β· ⏱️ 28.12.2021): +- [GitHub](https://github.com/abhishekkrthakur/tez) (πŸ‘¨β€πŸ’» 1 Β· πŸ”€ 110 Β· πŸ“¦ 19 Β· πŸ“‹ 28 - 64% open Β· ⏱️ 28.12.2021): ``` git clone https://github.com/abhishekkrthakur/tez ``` -- [PyPi](https://pypi.org/project/tez) (πŸ“₯ 980 / month Β· πŸ“¦ 2 Β· ⏱️ 28.12.2021): +- [PyPi](https://pypi.org/project/tez) (πŸ“₯ 2.4K / month Β· πŸ“¦ 2 Β· ⏱️ 28.12.2021): ``` pip install tez ```
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Torch-Struct (πŸ₯‰14 Β· ⭐ 1K) - Fast, general, and tested differentiable structured prediction.. MIT +
Pywick (πŸ₯‰17 Β· ⭐ 370) - High-level batteries-included neural network training library for.. MIT -- [GitHub](https://github.com/harvardnlp/pytorch-struct) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 80 Β· πŸ“‹ 52 - 46% open Β· ⏱️ 04.11.2021): +- [GitHub](https://github.com/achaiah/pywick) (πŸ‘¨β€πŸ’» 4 Β· πŸ”€ 38 Β· πŸ“¦ 5 Β· πŸ“‹ 14 - 14% open Β· ⏱️ 22.10.2021): ``` - git clone https://github.com/harvardnlp/pytorch-struct + git clone https://github.com/achaiah/pywick + ``` +- [PyPi](https://pypi.org/project/pywick) (πŸ“₯ 60 / month Β· ⏱️ 22.10.2021): + ``` + pip install pywick ```
madgrad (πŸ₯‰14 Β· ⭐ 750) - MADGRAD Optimization Method. MIT -- [GitHub](https://github.com/facebookresearch/madgrad) (πŸ‘¨β€πŸ’» 1 Β· πŸ”€ 52 Β· πŸ“¦ 20 Β· πŸ“‹ 9 - 22% open Β· ⏱️ 20.08.2021): +- [GitHub](https://github.com/facebookresearch/madgrad) (πŸ‘¨β€πŸ’» 1 Β· πŸ”€ 52 Β· πŸ“¦ 21 Β· πŸ“‹ 9 - 22% open Β· ⏱️ 20.08.2021): ``` git clone https://github.com/facebookresearch/madgrad ``` -- [PyPi](https://pypi.org/project/madgrad) (πŸ“₯ 3.6K / month Β· ⏱️ 01.04.2021): +- [PyPi](https://pypi.org/project/madgrad) (πŸ“₯ 5.5K / month Β· ⏱️ 01.04.2021): ``` pip install madgrad ```
Show 7 hidden projects... -- pretrainedmodels (πŸ₯‡30 Β· ⭐ 8.4K Β· πŸ’€) - Pretrained ConvNets for pytorch: NASNet, ResNeXt,.. BSD-3 +- pretrainedmodels (πŸ₯‡31 Β· ⭐ 8.4K Β· πŸ’€) - Pretrained ConvNets for pytorch: NASNet, ResNeXt,.. BSD-3 - Poutyne (πŸ₯‰21 Β· ⭐ 510) - A simplified framework and utilities for PyTorch. ❗️LGPL-3.0 - AdaBound (πŸ₯‰20 Β· ⭐ 2.9K Β· πŸ’€) - An optimizer that trains as fast as Adam and as good as SGD. Apache-2 -- Antialiased CNNs (πŸ₯‰19 Β· ⭐ 1.5K) - pip install antialiased-cnns to improve stability and.. ❗️CC BY-NC-SA 4.0 -- Lambda Networks (πŸ₯‰17 Β· ⭐ 1.5K Β· πŸ’€) - Implementation of LambdaNetworks, a new approach to.. MIT -- micrograd (πŸ₯‰14 Β· ⭐ 1.9K Β· πŸ’€) - A tiny scalar-valued autograd engine and a neural net library.. MIT -- TorchDrift (πŸ₯‰12 Β· ⭐ 190 Β· πŸ’€) - Drift Detection for your PyTorch Models. Apache-2 +- Antialiased CNNs (πŸ₯‰20 Β· ⭐ 1.5K) - pip install antialiased-cnns to improve stability and.. ❗️CC BY-NC-SA 4.0 +- Lambda Networks (πŸ₯‰18 Β· ⭐ 1.5K Β· πŸ’€) - Implementation of LambdaNetworks, a new approach to.. MIT +- micrograd (πŸ₯‰15 Β· ⭐ 1.9K Β· πŸ’€) - A tiny scalar-valued autograd engine and a neural net library.. MIT +- TorchDrift (πŸ₯‰14 Β· ⭐ 200 Β· πŸ’€) - Drift Detection for your PyTorch Models. Apache-2

@@ -8572,7 +9280,7 @@ _Libraries that extend Pytorch with additional capabilities._ _Libraries for connecting to, operating, and querying databases._ -πŸ”— best-of-python - DB Clients ( ⭐ 1.9K) - Collection of database clients for python. +πŸ”— best-of-python - DB Clients ( ⭐ 2K) - Collection of database clients for python.
@@ -8580,130 +9288,130 @@ _Libraries for connecting to, operating, and querying databases._ Back to top -
scipy (πŸ₯‡49 Β· ⭐ 9.1K) - Ecosystem of open-source software for mathematics, science, and engineering. BSD-3 +
scipy (πŸ₯‡49 Β· ⭐ 9.2K) - Ecosystem of open-source software for mathematics, science, and engineering. BSD-3 -- [GitHub](https://github.com/scipy/scipy) (πŸ‘¨β€πŸ’» 1.2K Β· πŸ”€ 4K Β· πŸ“₯ 330K Β· πŸ“¦ 450K Β· πŸ“‹ 8.2K - 22% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/scipy/scipy) (πŸ‘¨β€πŸ’» 1.2K Β· πŸ”€ 4.1K Β· πŸ“₯ 340K Β· πŸ“¦ 460K Β· πŸ“‹ 8.3K - 22% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/scipy/scipy ``` -- [PyPi](https://pypi.org/project/scipy) (πŸ“₯ 29M / month Β· πŸ“¦ 56K Β· ⏱️ 21.12.2021): +- [PyPi](https://pypi.org/project/scipy) (πŸ“₯ 36M / month Β· πŸ“¦ 56K Β· ⏱️ 05.02.2022): ``` pip install scipy ``` -- [Conda](https://anaconda.org/conda-forge/scipy) (πŸ“₯ 20M Β· ⏱️ 25.11.2021): +- [Conda](https://anaconda.org/conda-forge/scipy) (πŸ“₯ 21M Β· ⏱️ 09.02.2022): ``` conda install -c conda-forge scipy ```
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SymPy (πŸ₯‡45 Β· ⭐ 8.8K) - A computer algebra system written in pure Python. BSD-3 +
SymPy (πŸ₯‡44 Β· ⭐ 8.8K) - A computer algebra system written in pure Python. BSD-3 -- [GitHub](https://github.com/sympy/sympy) (πŸ‘¨β€πŸ’» 1.1K Β· πŸ”€ 3.5K Β· πŸ“₯ 440K Β· πŸ“¦ 38K Β· πŸ“‹ 12K - 35% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/sympy/sympy) (πŸ‘¨β€πŸ’» 1.1K Β· πŸ”€ 3.5K Β· πŸ“₯ 440K Β· πŸ“¦ 39K Β· πŸ“‹ 12K - 35% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/sympy/sympy ``` -- [PyPi](https://pypi.org/project/sympy) (πŸ“₯ 1.8M / month Β· πŸ“¦ 4K Β· ⏱️ 08.10.2021): +- [PyPi](https://pypi.org/project/sympy) (πŸ“₯ 2M / month Β· πŸ“¦ 4K Β· ⏱️ 08.10.2021): ``` pip install sympy ``` -- [Conda](https://anaconda.org/conda-forge/sympy) (πŸ“₯ 1.8M Β· ⏱️ 06.11.2021): +- [Conda](https://anaconda.org/conda-forge/sympy) (πŸ“₯ 1.9M Β· ⏱️ 06.11.2021): ``` conda install -c conda-forge sympy ```
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Streamlit (πŸ₯‡38 Β· ⭐ 17K) - Streamlit The fastest way to build data apps in Python. Apache-2 +
Streamlit (πŸ₯‡38 Β· ⭐ 18K) - Streamlit The fastest way to build data apps in Python. Apache-2 -- [GitHub](https://github.com/streamlit/streamlit) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 1.6K Β· πŸ“¦ 200 Β· πŸ“‹ 2.2K - 24% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/streamlit/streamlit) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 1.6K Β· πŸ“¦ 220 Β· πŸ“‹ 2.3K - 24% open Β· ⏱️ 08.02.2022): ``` git clone https://github.com/streamlit/streamlit ``` -- [PyPi](https://pypi.org/project/streamlit) (πŸ“₯ 640K / month Β· πŸ“¦ 280 Β· ⏱️ 28.12.2021): +- [PyPi](https://pypi.org/project/streamlit) (πŸ“₯ 860K / month Β· πŸ“¦ 300 Β· ⏱️ 09.02.2022): ``` pip install streamlit ```
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Gradio (πŸ₯‡34 Β· ⭐ 4.7K) - Wrap UIs around any model, share with anyone. Apache-2 +
PyOD (πŸ₯‡34 Β· ⭐ 5.2K) - (JMLR 19) A Python Toolbox for Scalable Outlier Detection (Anomaly.. BSD-2 -- [GitHub](https://github.com/gradio-app/gradio) (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 290 Β· πŸ“¦ 490 Β· πŸ“‹ 260 - 16% open Β· ⏱️ 10.01.2022): +- [GitHub](https://github.com/yzhao062/pyod) (πŸ‘¨β€πŸ’» 33 Β· πŸ”€ 1K Β· πŸ“¦ 1.1K Β· πŸ“‹ 240 - 50% open Β· ⏱️ 04.01.2022): ``` - git clone https://github.com/gradio-app/gradio - ``` -- [PyPi](https://pypi.org/project/gradio) (πŸ“₯ 72K / month Β· πŸ“¦ 12 Β· ⏱️ 04.01.2022): - ``` - pip install gradio + git clone https://github.com/yzhao062/pyod ``` -
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carla (πŸ₯‡33 Β· ⭐ 7.1K) - Open-source simulator for autonomous driving research. MIT - -- [GitHub](https://github.com/carla-simulator/carla) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 2K Β· πŸ“¦ 120 Β· πŸ“‹ 3.7K - 13% open Β· ⏱️ 19.11.2021): - +- [PyPi](https://pypi.org/project/pyod) (πŸ“₯ 470K / month Β· πŸ“¦ 28 Β· ⏱️ 04.01.2022): ``` - git clone https://github.com/carla-simulator/carla + pip install pyod ``` -- [PyPi](https://pypi.org/project/carla) (πŸ“₯ 2.2K / month Β· πŸ“¦ 3 Β· ⏱️ 17.11.2021): +- [Conda](https://anaconda.org/conda-forge/pyod) (πŸ“₯ 16K Β· ⏱️ 04.01.2022): ``` - pip install carla + conda install -c conda-forge pyod ```
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Datasette (πŸ₯‡33 Β· ⭐ 5.7K) - An open source multi-tool for exploring and publishing data. Apache-2 +
Gradio (πŸ₯‡34 Β· ⭐ 5.1K) - Wrap UIs around any model, share with anyone. Apache-2 -- [GitHub](https://github.com/simonw/datasette) (πŸ‘¨β€πŸ’» 60 Β· πŸ”€ 380 Β· πŸ“₯ 34 Β· πŸ“¦ 570 Β· πŸ“‹ 1.2K - 27% open Β· ⏱️ 23.12.2021): +- [GitHub](https://github.com/gradio-app/gradio) (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 320 Β· πŸ“¦ 520 Β· πŸ“‹ 330 - 17% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/simonw/datasette + git clone https://github.com/gradio-app/gradio ``` -- [PyPi](https://pypi.org/project/datasette) (πŸ“₯ 140K / month Β· πŸ“¦ 140 Β· ⏱️ 19.12.2021): +- [PyPi](https://pypi.org/project/gradio) (πŸ“₯ 81K / month Β· πŸ“¦ 16 Β· ⏱️ 08.02.2022): ``` - pip install datasette + pip install gradio ```
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PyOD (πŸ₯‡33 Β· ⭐ 5.2K) - (JMLR 19) A Python Toolbox for Scalable Outlier Detection (Anomaly.. BSD-2 +
DeepChem (πŸ₯‡34 Β· ⭐ 3.4K) - Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry,.. MIT -- [GitHub](https://github.com/yzhao062/pyod) (πŸ‘¨β€πŸ’» 33 Β· πŸ”€ 1K Β· πŸ“¦ 1.1K Β· πŸ“‹ 230 - 50% open Β· ⏱️ 04.01.2022): +- [GitHub](https://github.com/deepchem/deepchem) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 1.3K Β· πŸ“¦ 70 Β· πŸ“‹ 1.4K - 31% open Β· ⏱️ 08.02.2022): ``` - git clone https://github.com/yzhao062/pyod + git clone https://github.com/deepchem/deepchem ``` -- [PyPi](https://pypi.org/project/pyod) (πŸ“₯ 440K / month Β· πŸ“¦ 28 Β· ⏱️ 04.01.2022): +- [PyPi](https://pypi.org/project/deepchem) (πŸ“₯ 9.2K / month Β· πŸ“¦ 4 Β· ⏱️ 08.02.2022): ``` - pip install pyod + pip install deepchem + ``` +- [Conda](https://anaconda.org/conda-forge/deepchem) (πŸ“₯ 8.1K Β· ⏱️ 19.01.2022): + ``` + conda install -c conda-forge deepchem ```
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DeepChem (πŸ₯‡33 Β· ⭐ 3.4K) - Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry,.. MIT +
Datasette (πŸ₯ˆ33 Β· ⭐ 5.8K) - An open source multi-tool for exploring and publishing data. Apache-2 -- [GitHub](https://github.com/deepchem/deepchem) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 1.2K Β· πŸ“¦ 66 Β· πŸ“‹ 1.4K - 30% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/simonw/datasette) (πŸ‘¨β€πŸ’» 61 Β· πŸ”€ 390 Β· πŸ“₯ 34 Β· πŸ“¦ 580 Β· πŸ“‹ 1.3K - 27% open Β· ⏱️ 09.02.2022): ``` - git clone https://github.com/deepchem/deepchem + git clone https://github.com/simonw/datasette ``` -- [PyPi](https://pypi.org/project/deepchem) (πŸ“₯ 4.6K / month Β· πŸ“¦ 4 Β· ⏱️ 12.01.2022): +- [PyPi](https://pypi.org/project/datasette) (πŸ“₯ 260K / month Β· πŸ“¦ 140 Β· ⏱️ 07.02.2022): ``` - pip install deepchem + pip install datasette + ``` +- [Conda](https://anaconda.org/conda-forge/datasette) (πŸ“₯ 2.7K Β· ⏱️ 08.02.2022): + ``` + conda install -c conda-forge datasette ```
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PaddleHub (πŸ₯ˆ32 Β· ⭐ 7.4K) - Awesome pre-trained models toolkit based on.. Apache-2 +
PaddleHub (πŸ₯ˆ32 Β· ⭐ 7.5K) - Awesome pre-trained models toolkit based on.. Apache-2 -- [GitHub](https://github.com/PaddlePaddle/PaddleHub) (πŸ‘¨β€πŸ’» 53 Β· πŸ”€ 1.5K Β· πŸ“₯ 560 Β· πŸ“¦ 640 Β· πŸ“‹ 1K - 37% open Β· ⏱️ 28.12.2021): +- [GitHub](https://github.com/PaddlePaddle/PaddleHub) (πŸ‘¨β€πŸ’» 54 Β· πŸ”€ 1.5K Β· πŸ“₯ 560 Β· πŸ“¦ 690 Β· πŸ“‹ 1K - 37% open Β· ⏱️ 21.01.2022): ``` git clone https://github.com/PaddlePaddle/PaddleHub ``` -- [PyPi](https://pypi.org/project/paddlehub) (πŸ“₯ 7.9K / month Β· πŸ“¦ 4 Β· ⏱️ 28.12.2021): +- [PyPi](https://pypi.org/project/paddlehub) (πŸ“₯ 9.6K / month Β· πŸ“¦ 4 Β· ⏱️ 28.12.2021): ``` pip install paddlehub ```
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Autograd (πŸ₯ˆ32 Β· ⭐ 5.6K Β· πŸ’€) - Efficiently computes derivatives of numpy code. MIT +
Autograd (πŸ₯ˆ32 Β· ⭐ 5.7K Β· πŸ’€) - Efficiently computes derivatives of numpy code. MIT -- [GitHub](https://github.com/HIPS/autograd) (πŸ‘¨β€πŸ’» 51 Β· πŸ”€ 780 Β· πŸ“¦ 2.8K Β· πŸ“‹ 380 - 42% open Β· ⏱️ 03.03.2021): +- [GitHub](https://github.com/HIPS/autograd) (πŸ‘¨β€πŸ’» 51 Β· πŸ”€ 780 Β· πŸ“¦ 2.9K Β· πŸ“‹ 390 - 42% open Β· ⏱️ 03.03.2021): ``` git clone https://github.com/HIPS/autograd ``` -- [PyPi](https://pypi.org/project/autograd) (πŸ“₯ 1.1M / month Β· πŸ“¦ 270 Β· ⏱️ 25.07.2019): +- [PyPi](https://pypi.org/project/autograd) (πŸ“₯ 1.2M / month Β· πŸ“¦ 270 Β· ⏱️ 25.07.2019): ``` pip install autograd ``` @@ -8712,46 +9420,74 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge autograd ```
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carla (πŸ₯ˆ31 Β· ⭐ 7.2K Β· πŸ“‰) - Open-source simulator for autonomous driving research. MIT + +- [GitHub](https://github.com/carla-simulator/carla) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 2.1K Β· πŸ“¦ 120 Β· πŸ“‹ 3.7K - 13% open Β· ⏱️ 19.11.2021): + + ``` + git clone https://github.com/carla-simulator/carla + ``` +- [PyPi](https://pypi.org/project/carla) (πŸ“₯ 2.5K / month Β· πŸ“¦ 3 Β· ⏱️ 17.11.2021): + ``` + pip install carla + ``` +
hdbscan (πŸ₯ˆ31 Β· ⭐ 2.1K) - A high performance implementation of HDBSCAN clustering. BSD-3 -- [GitHub](https://github.com/scikit-learn-contrib/hdbscan) (πŸ‘¨β€πŸ’» 76 Β· πŸ”€ 370 Β· πŸ“¦ 1.2K Β· πŸ“‹ 410 - 62% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/scikit-learn-contrib/hdbscan) (πŸ‘¨β€πŸ’» 76 Β· πŸ”€ 400 Β· πŸ“¦ 1.2K Β· πŸ“‹ 420 - 63% open Β· ⏱️ 08.02.2022): ``` git clone https://github.com/scikit-learn-contrib/hdbscan ``` -- [PyPi](https://pypi.org/project/hdbscan) (πŸ“₯ 300K / month Β· πŸ“¦ 140 Β· ⏱️ 03.02.2021): +- [PyPi](https://pypi.org/project/hdbscan) (πŸ“₯ 360K / month Β· πŸ“¦ 150 Β· ⏱️ 08.02.2022): ``` pip install hdbscan ``` -- [Conda](https://anaconda.org/conda-forge/hdbscan) (πŸ“₯ 1M Β· ⏱️ 14.02.2021): +- [Conda](https://anaconda.org/conda-forge/hdbscan) (πŸ“₯ 1M Β· ⏱️ 10.02.2022): ``` conda install -c conda-forge hdbscan ```
Pythran (πŸ₯ˆ31 Β· ⭐ 1.7K) - Ahead of Time compiler for numeric kernels. BSD-3 -- [GitHub](https://github.com/serge-sans-paille/pythran) (πŸ‘¨β€πŸ’» 64 Β· πŸ”€ 170 Β· πŸ“¦ 93 Β· πŸ“‹ 740 - 15% open Β· ⏱️ 11.01.2022): +- [GitHub](https://github.com/serge-sans-paille/pythran) (πŸ‘¨β€πŸ’» 64 Β· πŸ”€ 170 Β· πŸ“¦ 100 Β· πŸ“‹ 740 - 15% open Β· ⏱️ 01.02.2022): ``` git clone https://github.com/serge-sans-paille/pythran ``` -- [PyPi](https://pypi.org/project/pythran) (πŸ“₯ 250K / month Β· πŸ“¦ 14 Β· ⏱️ 14.12.2021): +- [PyPi](https://pypi.org/project/pythran) (πŸ“₯ 350K / month Β· πŸ“¦ 14 Β· ⏱️ 14.12.2021): ``` pip install pythran ``` -- [Conda](https://anaconda.org/conda-forge/pythran) (πŸ“₯ 210K Β· ⏱️ 14.12.2021): +- [Conda](https://anaconda.org/conda-forge/pythran) (πŸ“₯ 220K Β· ⏱️ 14.12.2021): ``` conda install -c conda-forge pythran ```
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tensorly (πŸ₯ˆ31 Β· ⭐ 1.2K) - TensorLy: Tensor Learning in Python. BSD-2 +
River (πŸ₯ˆ30 Β· ⭐ 3.2K Β· πŸ“ˆ) - Online machine learning in Python. BSD-3 + +- [GitHub](https://github.com/online-ml/river) (πŸ‘¨β€πŸ’» 72 Β· πŸ”€ 340 Β· πŸ“¦ 73 Β· πŸ“‹ 340 - 1% open Β· ⏱️ 09.02.2022): + + ``` + git clone https://github.com/online-ml/river + ``` +- [PyPi](https://pypi.org/project/river) (πŸ“₯ 5.8K / month Β· πŸ“¦ 6 Β· ⏱️ 04.02.2022): + ``` + pip install river + ``` +- [Conda](https://anaconda.org/conda-forge/river) (πŸ“₯ 6.6K Β· ⏱️ 09.12.2021): + ``` + conda install -c conda-forge river + ``` +
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tensorly (πŸ₯ˆ30 Β· ⭐ 1.2K) - TensorLy: Tensor Learning in Python. BSD-2 -- [GitHub](https://github.com/tensorly/tensorly) (πŸ‘¨β€πŸ’» 49 Β· πŸ”€ 220 Β· πŸ“¦ 200 Β· πŸ“‹ 180 - 25% open Β· ⏱️ 22.12.2021): +- [GitHub](https://github.com/tensorly/tensorly) (πŸ‘¨β€πŸ’» 49 Β· πŸ”€ 220 Β· πŸ“¦ 220 Β· πŸ“‹ 180 - 25% open Β· ⏱️ 24.01.2022): ``` git clone https://github.com/tensorly/tensorly ``` -- [PyPi](https://pypi.org/project/tensorly) (πŸ“₯ 5.1K / month Β· πŸ“¦ 30 Β· ⏱️ 08.11.2021): +- [PyPi](https://pypi.org/project/tensorly) (πŸ“₯ 5.6K / month Β· πŸ“¦ 30 Β· ⏱️ 08.11.2021): ``` pip install tensorly ``` @@ -8760,275 +9496,259 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge tensorly ```
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PennyLane (πŸ₯ˆ30 Β· ⭐ 1.1K) - PennyLane is a cross-platform Python library for differentiable.. Apache-2 +
PennyLane (πŸ₯ˆ30 Β· ⭐ 1.2K) - PennyLane is a cross-platform Python library for differentiable.. Apache-2 -- [GitHub](https://github.com/PennyLaneAI/pennylane) (πŸ‘¨β€πŸ’» 86 Β· πŸ”€ 330 Β· πŸ“₯ 59 Β· πŸ“‹ 600 - 25% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/PennyLaneAI/pennylane) (πŸ‘¨β€πŸ’» 89 Β· πŸ”€ 340 Β· πŸ“₯ 59 Β· πŸ“‹ 620 - 24% open Β· ⏱️ 10.02.2022): ``` git clone https://github.com/PennyLaneAI/PennyLane ``` -- [PyPi](https://pypi.org/project/pennylane) (πŸ“₯ 8.6K / month Β· πŸ“¦ 28 Β· ⏱️ 14.12.2021): +- [PyPi](https://pypi.org/project/pennylane) (πŸ“₯ 11K / month Β· πŸ“¦ 28 Β· ⏱️ 08.02.2022): ``` pip install pennylane ``` +- [Conda](https://anaconda.org/conda-forge/pennylane) (πŸ“₯ 340 Β· ⏱️ 14.12.2021): + ``` + conda install -c conda-forge pennylane + ```
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agate (πŸ₯ˆ30 Β· ⭐ 1.1K) - A Python data analysis library that is optimized for humans instead of.. MIT +
agate (πŸ₯ˆ30 Β· ⭐ 1.1K Β· πŸ’€) - A Python data analysis library that is optimized for humans instead of.. MIT -- [GitHub](https://github.com/wireservice/agate) (πŸ‘¨β€πŸ’» 49 Β· πŸ”€ 130 Β· πŸ“¦ 720 Β· πŸ“‹ 680 - 7% open Β· ⏱️ 15.07.2021): +- [GitHub](https://github.com/wireservice/agate) (πŸ‘¨β€πŸ’» 49 Β· πŸ”€ 130 Β· πŸ“¦ 760 Β· πŸ“‹ 680 - 7% open Β· ⏱️ 15.07.2021): ``` git clone https://github.com/wireservice/agate ``` -- [PyPi](https://pypi.org/project/agate) (πŸ“₯ 680K / month Β· πŸ“¦ 130 Β· ⏱️ 15.07.2021): +- [PyPi](https://pypi.org/project/agate) (πŸ“₯ 1.1M / month Β· πŸ“¦ 130 Β· ⏱️ 15.07.2021): ``` pip install agate ``` -- [Conda](https://anaconda.org/conda-forge/agate) (πŸ“₯ 75K Β· ⏱️ 16.07.2021): +- [Conda](https://anaconda.org/conda-forge/agate) (πŸ“₯ 76K Β· ⏱️ 16.07.2021): ``` conda install -c conda-forge agate ```
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pyopencl (πŸ₯ˆ30 Β· ⭐ 860) - OpenCL integration for Python, plus shiny features. MIT +
pyopencl (πŸ₯ˆ30 Β· ⭐ 870) - OpenCL integration for Python, plus shiny features. MIT -- [GitHub](https://github.com/inducer/pyopencl) (πŸ‘¨β€πŸ’» 90 Β· πŸ”€ 220 Β· πŸ“¦ 610 Β· πŸ“‹ 300 - 22% open Β· ⏱️ 30.12.2021): +- [GitHub](https://github.com/inducer/pyopencl) (πŸ‘¨β€πŸ’» 90 Β· πŸ”€ 220 Β· πŸ“¦ 630 Β· πŸ“‹ 300 - 22% open Β· ⏱️ 17.01.2022): ``` git clone https://github.com/inducer/pyopencl ``` -- [PyPi](https://pypi.org/project/pyopencl) (πŸ“₯ 22K / month Β· πŸ“¦ 180 Β· ⏱️ 30.12.2021): +- [PyPi](https://pypi.org/project/pyopencl) (πŸ“₯ 26K / month Β· πŸ“¦ 180 Β· ⏱️ 17.01.2022): ``` pip install pyopencl ``` -- [Conda](https://anaconda.org/conda-forge/pyopencl) (πŸ“₯ 550K Β· ⏱️ 30.12.2021): +- [Conda](https://anaconda.org/conda-forge/pyopencl) (πŸ“₯ 560K Β· ⏱️ 19.01.2022): ``` conda install -c conda-forge pyopencl ```
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causalml (πŸ₯ˆ29 Β· ⭐ 2.6K) - Uplift modeling and causal inference with machine learning.. Apache-2 +
causalml (πŸ₯ˆ29 Β· ⭐ 2.8K) - Uplift modeling and causal inference with machine learning.. Apache-2 -- [GitHub](https://github.com/uber/causalml) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 390 Β· πŸ“¦ 33 Β· πŸ“‹ 240 - 19% open Β· ⏱️ 10.01.2022): +- [GitHub](https://github.com/uber/causalml) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 420 Β· πŸ“¦ 37 Β· πŸ“‹ 240 - 18% open Β· ⏱️ 05.02.2022): ``` git clone https://github.com/uber/causalml ``` -- [PyPi](https://pypi.org/project/causalml) (πŸ“₯ 44K / month Β· πŸ“¦ 1 Β· ⏱️ 02.08.2021): +- [PyPi](https://pypi.org/project/causalml) (πŸ“₯ 43K / month Β· πŸ“¦ 1 Β· ⏱️ 05.02.2022): ``` pip install causalml ```
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TabPy (πŸ₯ˆ28 Β· ⭐ 1.2K) - Execute Python code on the fly and display results in Tableau visualizations:. MIT +
TabPy (πŸ₯ˆ29 Β· ⭐ 1.2K) - Execute Python code on the fly and display results in Tableau visualizations:. MIT -- [GitHub](https://github.com/tableau/TabPy) (πŸ‘¨β€πŸ’» 44 Β· πŸ”€ 440 Β· πŸ“¦ 79 Β· πŸ“‹ 290 - 5% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/tableau/TabPy) (πŸ‘¨β€πŸ’» 46 Β· πŸ”€ 450 Β· πŸ“¦ 81 Β· πŸ“‹ 290 - 3% open Β· ⏱️ 20.01.2022): ``` git clone https://github.com/tableau/TabPy ``` -- [PyPi](https://pypi.org/project/tabpy) (πŸ“₯ 18K / month Β· πŸ“¦ 2 Β· ⏱️ 20.08.2021): +- [PyPi](https://pypi.org/project/tabpy) (πŸ“₯ 17K / month Β· πŸ“¦ 2 Β· ⏱️ 20.01.2022): ``` pip install tabpy ``` +- [Conda](https://anaconda.org/anaconda/tabpy-client) (πŸ“₯ 2.4K Β· ⏱️ 20.01.2022): + ``` + conda install -c anaconda tabpy-client + ```
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pyjanitor (πŸ₯ˆ28 Β· ⭐ 800) - Clean APIs for data cleaning. Python implementation of R package Janitor. MIT +
pycm (πŸ₯ˆ28 Β· ⭐ 1.2K) - Multi-class confusion matrix library in Python. MIT -- [GitHub](https://github.com/pyjanitor-devs/pyjanitor) (πŸ‘¨β€πŸ’» 96 Β· πŸ”€ 130 Β· πŸ“¦ 140 Β· πŸ“‹ 430 - 21% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/sepandhaghighi/pycm) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 100 Β· πŸ“¦ 130 Β· πŸ“‹ 180 - 6% open Β· ⏱️ 26.01.2022): ``` - git clone https://github.com/pyjanitor-devs/pyjanitor - ``` -- [PyPi](https://pypi.org/project/pyjanitor) (πŸ“₯ 14K / month Β· πŸ“¦ 10 Β· ⏱️ 21.11.2021): - ``` - pip install pyjanitor + git clone https://github.com/sepandhaghighi/pycm ``` -- [Conda](https://anaconda.org/conda-forge/pyjanitor) (πŸ“₯ 110K Β· ⏱️ 22.11.2021): +- [PyPi](https://pypi.org/project/pycm) (πŸ“₯ 35K / month Β· πŸ“¦ 12 Β· ⏱️ 26.01.2022): ``` - conda install -c conda-forge pyjanitor + pip install pycm ```
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Trax (πŸ₯ˆ27 Β· ⭐ 6.7K) - Trax Deep Learning with Clear Code and Speed. Apache-2 +
pyjanitor (πŸ₯ˆ28 Β· ⭐ 820) - Clean APIs for data cleaning. Python implementation of R package Janitor. MIT -- [GitHub](https://github.com/google/trax) (πŸ‘¨β€πŸ’» 74 Β· πŸ”€ 670 Β· πŸ“¦ 40 Β· πŸ“‹ 200 - 40% open Β· ⏱️ 23.12.2021): +- [GitHub](https://github.com/pyjanitor-devs/pyjanitor) (πŸ‘¨β€πŸ’» 96 Β· πŸ”€ 140 Β· πŸ“¦ 150 Β· πŸ“‹ 440 - 21% open Β· ⏱️ 08.02.2022): ``` - git clone https://github.com/google/trax + git clone https://github.com/pyjanitor-devs/pyjanitor ``` -- [PyPi](https://pypi.org/project/trax) (πŸ“₯ 4K / month Β· ⏱️ 26.10.2021): +- [PyPi](https://pypi.org/project/pyjanitor) (πŸ“₯ 18K / month Β· πŸ“¦ 10 Β· ⏱️ 21.11.2021): ``` - pip install trax + pip install pyjanitor + ``` +- [Conda](https://anaconda.org/conda-forge/pyjanitor) (πŸ“₯ 110K Β· ⏱️ 22.11.2021): + ``` + conda install -c conda-forge pyjanitor ```
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metric-learn (πŸ₯ˆ27 Β· ⭐ 1.2K) - Metric learning algorithms in Python. MIT +
adapter-transformers (πŸ₯ˆ28 Β· ⭐ 660 Β· βž•) - Huggingface Transformers + Adapters =. Apache-2 huggingface -- [GitHub](https://github.com/scikit-learn-contrib/metric-learn) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 220 Β· πŸ“¦ 180 Β· πŸ“‹ 170 - 30% open Β· ⏱️ 17.11.2021): +- [GitHub](https://github.com/Adapter-Hub/adapter-transformers) (πŸ‘¨β€πŸ’» 1.1K Β· πŸ”€ 110 Β· πŸ“¦ 43 Β· πŸ“‹ 140 - 24% open Β· ⏱️ 09.02.2022): ``` - git clone https://github.com/scikit-learn-contrib/metric-learn + git clone https://github.com/Adapter-Hub/adapter-transformers ``` -- [PyPi](https://pypi.org/project/metric-learn) (πŸ“₯ 8.2K / month Β· πŸ“¦ 11 Β· ⏱️ 02.07.2020): +- [PyPi](https://pypi.org/project/adapter-transformers) (πŸ“₯ 50K / month Β· πŸ“¦ 4 Β· ⏱️ 09.02.2022): ``` - pip install metric-learn + pip install adapter-transformers ```
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pycm (πŸ₯ˆ27 Β· ⭐ 1.2K) - Multi-class confusion matrix library in Python. MIT +
Trax (πŸ₯‰27 Β· ⭐ 6.8K) - Trax Deep Learning with Clear Code and Speed. Apache-2 -- [GitHub](https://github.com/sepandhaghighi/pycm) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 100 Β· πŸ“¦ 120 Β· πŸ“‹ 180 - 10% open Β· ⏱️ 27.10.2021): +- [GitHub](https://github.com/google/trax) (πŸ‘¨β€πŸ’» 75 Β· πŸ”€ 680 Β· πŸ“¦ 42 Β· πŸ“‹ 200 - 41% open Β· ⏱️ 02.02.2022): ``` - git clone https://github.com/sepandhaghighi/pycm + git clone https://github.com/google/trax ``` -- [PyPi](https://pypi.org/project/pycm) (πŸ“₯ 32K / month Β· πŸ“¦ 12 Β· ⏱️ 27.10.2021): +- [PyPi](https://pypi.org/project/trax) (πŸ“₯ 3.8K / month Β· ⏱️ 26.10.2021): ``` - pip install pycm + pip install trax ```
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kmodes (πŸ₯ˆ27 Β· ⭐ 950) - Python implementations of the k-modes and k-prototypes clustering.. MIT +
kmodes (πŸ₯‰27 Β· ⭐ 970) - Python implementations of the k-modes and k-prototypes clustering.. MIT -- [GitHub](https://github.com/nicodv/kmodes) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 360 Β· πŸ“¦ 940 Β· πŸ“‹ 140 - 13% open Β· ⏱️ 15.12.2021): +- [GitHub](https://github.com/nicodv/kmodes) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 360 Β· πŸ“¦ 990 Β· πŸ“‹ 140 - 11% open Β· ⏱️ 15.12.2021): ``` git clone https://github.com/nicodv/kmodes ``` -- [PyPi](https://pypi.org/project/kmodes) (πŸ“₯ 240K / month Β· πŸ“¦ 24 Β· ⏱️ 08.10.2021): +- [PyPi](https://pypi.org/project/kmodes) (πŸ“₯ 310K / month Β· πŸ“¦ 26 Β· ⏱️ 08.10.2021): ``` pip install kmodes ``` +- [Conda](https://anaconda.org/conda-forge/kmodes) (πŸ“₯ 5.9K Β· ⏱️ 26.01.2022): + ``` + conda install -c conda-forge kmodes + ```
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pyclustering (πŸ₯ˆ27 Β· ⭐ 910 Β· πŸ’€) - pyclustring is a Python, C++ data mining library. BSD-3 +
pyclustering (πŸ₯‰27 Β· ⭐ 920 Β· πŸ’€) - pyclustring is a Python, C++ data mining library. BSD-3 -- [GitHub](https://github.com/annoviko/pyclustering) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 210 Β· πŸ“₯ 380 Β· πŸ“¦ 260 Β· πŸ“‹ 650 - 8% open Β· ⏱️ 12.02.2021): +- [GitHub](https://github.com/annoviko/pyclustering) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 220 Β· πŸ“₯ 390 Β· πŸ“¦ 270 Β· πŸ“‹ 650 - 8% open Β· ⏱️ 12.02.2021): ``` git clone https://github.com/annoviko/pyclustering ``` -- [PyPi](https://pypi.org/project/pyclustering) (πŸ“₯ 42K / month Β· πŸ“¦ 28 Β· ⏱️ 25.11.2020): +- [PyPi](https://pypi.org/project/pyclustering) (πŸ“₯ 43K / month Β· πŸ“¦ 28 Β· ⏱️ 25.11.2020): ``` pip install pyclustering ``` -- [Conda](https://anaconda.org/conda-forge/pyclustering) (πŸ“₯ 33K Β· ⏱️ 13.09.2021): +- [Conda](https://anaconda.org/conda-forge/pyclustering) (πŸ“₯ 34K Β· ⏱️ 13.09.2021): ``` conda install -c conda-forge pyclustering ```
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Mars (πŸ₯‰26 Β· ⭐ 2.3K) - Mars is a tensor-based unified framework for large-scale data.. Apache-2 +
AugLy (πŸ₯‰26 Β· ⭐ 4.3K) - A data augmentations library for audio, image, text, and video. MIT -- [GitHub](https://github.com/mars-project/mars) (πŸ‘¨β€πŸ’» 39 Β· πŸ”€ 290 Β· πŸ“‹ 940 - 16% open Β· ⏱️ 12.01.2022): +- [GitHub](https://github.com/facebookresearch/AugLy) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 220 Β· πŸ“¦ 25 Β· πŸ“‹ 56 - 25% open Β· ⏱️ 01.02.2022): ``` - git clone https://github.com/mars-project/mars + git clone https://github.com/facebookresearch/AugLy ``` -- [PyPi](https://pypi.org/project/pymars) (πŸ“₯ 2.2K / month Β· πŸ“¦ 1 Β· ⏱️ 16.12.2021): +- [PyPi](https://pypi.org/project/augly) (πŸ“₯ 1.9K / month Β· πŸ“¦ 3 Β· ⏱️ 17.12.2021): ``` - pip install pymars + pip install augly ```
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PySwarms (πŸ₯‰26 Β· ⭐ 870 Β· πŸ’€) - A research toolkit for particle swarm optimization in Python. MIT +
metric-learn (πŸ₯‰26 Β· ⭐ 1.2K) - Metric learning algorithms in Python. MIT -- [GitHub](https://github.com/ljvmiranda921/pyswarms) (πŸ‘¨β€πŸ’» 43 Β· πŸ”€ 280 Β· πŸ“¦ 150 Β· πŸ“‹ 200 - 8% open Β· ⏱️ 23.06.2021): +- [GitHub](https://github.com/scikit-learn-contrib/metric-learn) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 220 Β· πŸ“¦ 190 Β· πŸ“‹ 170 - 30% open Β· ⏱️ 17.11.2021): ``` - git clone https://github.com/ljvmiranda921/pyswarms + git clone https://github.com/scikit-learn-contrib/metric-learn ``` -- [PyPi](https://pypi.org/project/pyswarms) (πŸ“₯ 30K / month Β· πŸ“¦ 6 Β· ⏱️ 03.01.2021): +- [PyPi](https://pypi.org/project/metric-learn) (πŸ“₯ 9.9K / month Β· πŸ“¦ 11 Β· ⏱️ 02.07.2020): ``` - pip install pyswarms + pip install metric-learn ``` -
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River (πŸ₯‰25 Β· ⭐ 3K) - Online machine learning in Python. BSD-3 - -- [GitHub](https://github.com/online-ml/river) (πŸ‘¨β€πŸ’» 70 Β· πŸ”€ 320 Β· πŸ“¦ 66 Β· πŸ“‹ 340 - 1% open Β· ⏱️ 05.01.2022): - +- [Conda](https://anaconda.org/conda-forge/metric-learn) (πŸ“₯ 5.3K Β· ⏱️ 02.07.2020): ``` - git clone https://github.com/online-ml/river + conda install -c conda-forge metric-learn ```
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alibi-detect (πŸ₯‰25 Β· ⭐ 1.1K) - Algorithms for outlier, adversarial and drift detection. Apache-2 +
alibi-detect (πŸ₯‰26 Β· ⭐ 1.1K) - Algorithms for outlier, adversarial and drift detection. Apache-2 -- [GitHub](https://github.com/SeldonIO/alibi-detect) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 110 Β· πŸ“¦ 48 Β· πŸ“‹ 200 - 40% open Β· ⏱️ 13.01.2022): +- [GitHub](https://github.com/SeldonIO/alibi-detect) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 120 Β· πŸ“¦ 58 Β· πŸ“‹ 220 - 39% open Β· ⏱️ 04.02.2022): ``` git clone https://github.com/SeldonIO/alibi-detect ``` -- [PyPi](https://pypi.org/project/alibi-detect) (πŸ“₯ 11K / month Β· πŸ“¦ 5 Β· ⏱️ 09.12.2021): +- [PyPi](https://pypi.org/project/alibi-detect) (πŸ“₯ 11K / month Β· πŸ“¦ 5 Β· ⏱️ 18.01.2022): ``` pip install alibi-detect ```
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AugLy (πŸ₯‰24 Β· ⭐ 4.2K) - A data augmentations library for audio, image, text, and video. MIT - -- [GitHub](https://github.com/facebookresearch/AugLy) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 220 Β· πŸ“¦ 25 Β· πŸ“‹ 56 - 25% open Β· ⏱️ 28.12.2021): - - ``` - git clone https://github.com/facebookresearch/AugLy - ``` -- [PyPi](https://pypi.org/project/augly) (πŸ“₯ 1.7K / month Β· πŸ“¦ 3 Β· ⏱️ 17.12.2021): - ``` - pip install augly - ``` -
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modAL (πŸ₯‰24 Β· ⭐ 1.5K Β· πŸ’€) - A modular active learning framework for Python. MIT +
PySwarms (πŸ₯‰26 Β· ⭐ 880 Β· πŸ’€) - A research toolkit for particle swarm optimization in Python. MIT -- [GitHub](https://github.com/modAL-python/modAL) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 230 Β· πŸ“₯ 20 Β· πŸ“¦ 110 Β· πŸ“‹ 120 - 54% open Β· ⏱️ 07.01.2021): +- [GitHub](https://github.com/ljvmiranda921/pyswarms) (πŸ‘¨β€πŸ’» 43 Β· πŸ”€ 290 Β· πŸ“¦ 150 Β· πŸ“‹ 200 - 8% open Β· ⏱️ 23.06.2021): ``` - git clone https://github.com/modAL-python/modAL + git clone https://github.com/ljvmiranda921/pyswarms ``` -- [PyPi](https://pypi.org/project/modAL) (πŸ“₯ 2.7K / month Β· πŸ“¦ 7 Β· ⏱️ 07.01.2021): +- [PyPi](https://pypi.org/project/pyswarms) (πŸ“₯ 32K / month Β· πŸ“¦ 6 Β· ⏱️ 03.01.2021): ``` - pip install modAL + pip install pyswarms ```
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AstroML (πŸ₯‰23 Β· ⭐ 790 Β· πŸ’€) - Machine learning, statistics, and data mining for astronomy and.. BSD-2 +
Mars (πŸ₯‰25 Β· ⭐ 2.3K) - Mars is a tensor-based unified framework for large-scale data.. Apache-2 -- [GitHub](https://github.com/astroML/astroML) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 270 Β· πŸ“‹ 140 - 38% open Β· ⏱️ 07.04.2021): +- [GitHub](https://github.com/mars-project/mars) (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 300 Β· πŸ“‹ 960 - 16% open Β· ⏱️ 10.02.2022): ``` - git clone https://github.com/astroML/astroML - ``` -- [PyPi](https://pypi.org/project/astroML) (πŸ“₯ 1.5K / month Β· πŸ“¦ 33 Β· ⏱️ 04.01.2022): - ``` - pip install astroML + git clone https://github.com/mars-project/mars ``` -- [Conda](https://anaconda.org/conda-forge/astroml) (πŸ“₯ 27K Β· ⏱️ 16.02.2020): +- [PyPi](https://pypi.org/project/pymars) (πŸ“₯ 4.2K / month Β· πŸ“¦ 1 Β· ⏱️ 03.02.2022): ``` - conda install -c conda-forge astroml + pip install pymars ```
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Prince (πŸ₯‰23 Β· ⭐ 750) - Python factor analysis library (PCA, CA, MCA, MFA, FAMD). MIT +
avalanche (πŸ₯‰24 Β· ⭐ 730) - Avalanche: an End-to-End Library for Continual Learning. MIT -- [GitHub](https://github.com/MaxHalford/prince) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 130 Β· πŸ“¦ 170 Β· πŸ“‹ 100 - 33% open Β· ⏱️ 28.12.2021): +- [GitHub](https://github.com/ContinualAI/avalanche) (πŸ‘¨β€πŸ’» 49 Β· πŸ”€ 110 Β· πŸ“‹ 460 - 15% open Β· ⏱️ 09.02.2022): ``` - git clone https://github.com/MaxHalford/prince + git clone https://github.com/ContinualAI/avalanche ``` -- [PyPi](https://pypi.org/project/prince) (πŸ“₯ 13K / month Β· πŸ“¦ 5 Β· ⏱️ 06.10.2020): +- [PyPi](https://pypi.org/project/avalanche-lib) (πŸ“₯ 240 / month Β· ⏱️ 16.12.2021): ``` - pip install prince + pip install avalanche-lib ```
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findspark (πŸ₯‰23 Β· ⭐ 430 Β· πŸ’€) - Find pyspark to make it importable. BSD-3 +
findspark (πŸ₯‰24 Β· ⭐ 430) - Find pyspark to make it importable. BSD-3 -- [GitHub](https://github.com/minrk/findspark) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 66 Β· πŸ“¦ 2.2K Β· πŸ“‹ 21 - 52% open Β· ⏱️ 14.06.2021): +- [GitHub](https://github.com/minrk/findspark) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 66 Β· πŸ“¦ 2.2K Β· πŸ“‹ 22 - 54% open Β· ⏱️ 17.01.2022): ``` git clone https://github.com/minrk/findspark ``` -- [PyPi](https://pypi.org/project/findspark) (πŸ“₯ 1.9M / month Β· πŸ“¦ 140 Β· ⏱️ 08.06.2020): +- [PyPi](https://pypi.org/project/findspark) (πŸ“₯ 2.2M / month Β· πŸ“¦ 140 Β· ⏱️ 17.01.2022): ``` pip install findspark ``` -- [Conda](https://anaconda.org/conda-forge/findspark) (πŸ“₯ 600K Β· ⏱️ 06.07.2018): +- [Conda](https://anaconda.org/conda-forge/findspark) (πŸ“₯ 610K Β· ⏱️ 19.01.2022): ``` conda install -c conda-forge findspark ```
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StreamAlert (πŸ₯‰22 Β· ⭐ 2.6K) - StreamAlert is a serverless, realtime data analysis framework.. Apache-2 - -- [GitHub](https://github.com/airbnb/streamalert) (πŸ‘¨β€πŸ’» 33 Β· πŸ”€ 320 Β· πŸ“‹ 340 - 24% open Β· ⏱️ 04.11.2021): - - ``` - git clone https://github.com/airbnb/streamalert - ``` -
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gplearn (πŸ₯‰22 Β· ⭐ 1.1K) - Genetic Programming in Python, with a scikit-learn inspired API. BSD-3 +
gplearn (πŸ₯‰23 Β· ⭐ 1.1K) - Genetic Programming in Python, with a scikit-learn inspired API. BSD-3 - [GitHub](https://github.com/trevorstephens/gplearn) (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 190 Β· πŸ“¦ 220 Β· πŸ“‹ 180 - 26% open Β· ⏱️ 18.10.2021): @@ -9039,38 +9759,66 @@ _Libraries for connecting to, operating, and querying databases._ ``` pip install gplearn ``` +- [Conda](https://anaconda.org/conda-forge/gplearn) (πŸ“₯ 1.8K Β· ⏱️ 18.06.2020): + ``` + conda install -c conda-forge gplearn + ```
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avalanche (πŸ₯‰22 Β· ⭐ 700) - Avalanche: an End-to-End Library for Continual Learning. MIT +
AstroML (πŸ₯‰23 Β· ⭐ 800) - Machine learning, statistics, and data mining for astronomy and.. BSD-2 -- [GitHub](https://github.com/ContinualAI/avalanche) (πŸ‘¨β€πŸ’» 48 Β· πŸ”€ 110 Β· πŸ“‹ 450 - 15% open Β· ⏱️ 11.01.2022): +- [GitHub](https://github.com/astroML/astroML) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 280 Β· πŸ“‹ 140 - 40% open Β· ⏱️ 25.01.2022): ``` - git clone https://github.com/ContinualAI/avalanche + git clone https://github.com/astroML/astroML + ``` +- [PyPi](https://pypi.org/project/astroML) (πŸ“₯ 2.7K / month Β· πŸ“¦ 33 Β· ⏱️ 25.01.2022): + ``` + pip install astroML + ``` +- [Conda](https://anaconda.org/conda-forge/astroml) (πŸ“₯ 27K Β· ⏱️ 26.01.2022): + ``` + conda install -c conda-forge astroml ```
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impyute (πŸ₯‰21 Β· ⭐ 300) - Data imputations library to preprocess datasets with missing data. MIT +
Prince (πŸ₯‰23 Β· ⭐ 760) - Python factor analysis library (PCA, CA, MCA, MFA, FAMD). MIT -- [GitHub](https://github.com/eltonlaw/impyute) (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 43 Β· πŸ“¦ 120 Β· πŸ“‹ 64 - 42% open Β· ⏱️ 06.11.2021): +- [GitHub](https://github.com/MaxHalford/prince) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 130 Β· πŸ“¦ 180 Β· πŸ“‹ 100 - 33% open Β· ⏱️ 28.12.2021): ``` - git clone https://github.com/eltonlaw/impyute + git clone https://github.com/MaxHalford/prince ``` -- [PyPi](https://pypi.org/project/impyute) (πŸ“₯ 1.6K / month Β· πŸ“¦ 3 Β· ⏱️ 29.04.2019): +- [PyPi](https://pypi.org/project/prince) (πŸ“₯ 18K / month Β· πŸ“¦ 5 Β· ⏱️ 06.10.2020): ``` - pip install impyute + pip install prince + ``` +- [Conda](https://anaconda.org/conda-forge/prince-factor-analysis) (πŸ“₯ 9.3K Β· ⏱️ 30.04.2021): + ``` + conda install -c conda-forge prince-factor-analysis + ``` +
+
StreamAlert (πŸ₯‰22 Β· ⭐ 2.7K) - StreamAlert is a serverless, realtime data analysis framework.. Apache-2 + +- [GitHub](https://github.com/airbnb/streamalert) (πŸ‘¨β€πŸ’» 33 Β· πŸ”€ 320 Β· πŸ“‹ 340 - 24% open Β· ⏱️ 04.11.2021): + + ``` + git clone https://github.com/airbnb/streamalert ```
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opyrator (πŸ₯‰20 Β· ⭐ 2.5K Β· πŸ’€) - Turns your machine learning code into microservices with web API,.. MIT +
opyrator (πŸ₯‰20 Β· ⭐ 2.6K Β· πŸ’€) - Turns your machine learning code into microservices with web API,.. MIT - [GitHub](https://github.com/ml-tooling/opyrator) (πŸ‘¨β€πŸ’» 4 Β· πŸ”€ 110 Β· πŸ“¦ 31 Β· πŸ“‹ 24 - 8% open Β· ⏱️ 06.05.2021): ``` git clone https://github.com/ml-tooling/opyrator ``` -- [PyPi](https://pypi.org/project/opyrator) (πŸ“₯ 270 / month Β· ⏱️ 04.05.2021): +- [PyPi](https://pypi.org/project/opyrator) (πŸ“₯ 140 / month Β· ⏱️ 04.05.2021): ``` pip install opyrator ``` +- [Conda](https://anaconda.org/conda-forge/opyrator) (πŸ“₯ 35 Β· ⏱️ 08.01.2022): + ``` + conda install -c conda-forge opyrator + ```
scikit-rebate (πŸ₯‰20 Β· ⭐ 340 Β· πŸ’€) - A scikit-learn-compatible Python implementation of.. MIT @@ -9079,47 +9827,47 @@ _Libraries for connecting to, operating, and querying databases._ ``` git clone https://github.com/EpistasisLab/scikit-rebate ``` -- [PyPi](https://pypi.org/project/skrebate) (πŸ“₯ 3.8K / month Β· πŸ“¦ 40 Β· ⏱️ 20.03.2021): +- [PyPi](https://pypi.org/project/skrebate) (πŸ“₯ 2.5K / month Β· πŸ“¦ 40 Β· ⏱️ 20.03.2021): ``` pip install skrebate ``` +- [Conda](https://anaconda.org/conda-forge/skrebate) (πŸ“₯ 24K Β· ⏱️ 16.02.2021): + ``` + conda install -c conda-forge skrebate + ```
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SUOD (πŸ₯‰20 Β· ⭐ 300) - (MLSys 21) An Acceleration System for Large-scare Unsupervised Heterogeneous.. BSD-2 +
impyute (πŸ₯‰20 Β· ⭐ 310) - Data imputations library to preprocess datasets with missing data. MIT -- [GitHub](https://github.com/yzhao062/SUOD) (πŸ‘¨β€πŸ’» 1 Β· πŸ”€ 39 Β· πŸ“¦ 400 Β· πŸ“‹ 8 - 75% open Β· ⏱️ 02.10.2021): +- [GitHub](https://github.com/eltonlaw/impyute) (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 43 Β· πŸ“¦ 130 Β· πŸ“‹ 64 - 42% open Β· ⏱️ 06.11.2021): ``` - git clone https://github.com/yzhao062/SUOD + git clone https://github.com/eltonlaw/impyute ``` -- [PyPi](https://pypi.org/project/suod) (πŸ“₯ 39K / month Β· ⏱️ 01.10.2021): +- [PyPi](https://pypi.org/project/impyute) (πŸ“₯ 2.1K / month Β· πŸ“¦ 3 Β· ⏱️ 29.04.2019): ``` - pip install suod + pip install impyute ```
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BioPandas (πŸ₯‰19 Β· ⭐ 400) - Working with molecular structures in pandas DataFrames. BSD-3 +
SUOD (πŸ₯‰20 Β· ⭐ 310) - (MLSys 21) An Acceleration System for Large-scare Unsupervised Heterogeneous.. BSD-2 -- [GitHub](https://github.com/rasbt/biopandas) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 89 Β· πŸ“‹ 39 - 38% open Β· ⏱️ 04.01.2022): +- [GitHub](https://github.com/yzhao062/SUOD) (πŸ‘¨β€πŸ’» 1 Β· πŸ”€ 40 Β· πŸ“¦ 410 Β· πŸ“‹ 8 - 75% open Β· ⏱️ 02.10.2021): ``` - git clone https://github.com/rasbt/biopandas - ``` -- [PyPi](https://pypi.org/project/biopandas) (πŸ“₯ 2.1K / month Β· πŸ“¦ 9 Β· ⏱️ 24.09.2021): - ``` - pip install biopandas + git clone https://github.com/yzhao062/SUOD ``` -- [Conda](https://anaconda.org/conda-forge/biopandas) (πŸ“₯ 94K Β· ⏱️ 31.08.2021): +- [PyPi](https://pypi.org/project/suod) (πŸ“₯ 35K / month Β· ⏱️ 01.10.2021): ``` - conda install -c conda-forge biopandas + pip install suod ```
pykale (πŸ₯‰19 Β· ⭐ 320) - Knowledge-Aware machine LEarning (KALE): accessible machine learning.. MIT -- [GitHub](https://github.com/pykale/pykale) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 38 Β· πŸ“‹ 74 - 13% open Β· ⏱️ 22.12.2021): +- [GitHub](https://github.com/pykale/pykale) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 39 Β· πŸ“‹ 80 - 12% open Β· ⏱️ 20.01.2022): ``` git clone https://github.com/pykale/pykale ``` -- [PyPi](https://pypi.org/project/pykale) (πŸ“₯ 35 / month Β· ⏱️ 13.10.2021): +- [PyPi](https://pypi.org/project/pykale) (πŸ“₯ 46 / month Β· ⏱️ 13.10.2021): ``` pip install pykale ``` @@ -9131,7 +9879,7 @@ _Libraries for connecting to, operating, and querying databases._ ``` git clone https://github.com/alegonz/baikal ``` -- [PyPi](https://pypi.org/project/baikal) (πŸ“₯ 380 / month Β· πŸ“¦ 1 Β· ⏱️ 15.11.2020): +- [PyPi](https://pypi.org/project/baikal) (πŸ“₯ 660 / month Β· πŸ“¦ 1 Β· ⏱️ 15.11.2020): ``` pip install baikal ``` @@ -9140,14 +9888,30 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge cython-blis ```
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apricot (πŸ₯‰18 Β· ⭐ 400) - apricot implements submodular optimization for the purpose of selecting.. MIT +
BioPandas (πŸ₯‰18 Β· ⭐ 410) - Working with molecular structures in pandas DataFrames. BSD-3 + +- [GitHub](https://github.com/rasbt/biopandas) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 90 Β· πŸ“‹ 39 - 38% open Β· ⏱️ 04.01.2022): + + ``` + git clone https://github.com/rasbt/biopandas + ``` +- [PyPi](https://pypi.org/project/biopandas) (πŸ“₯ 2.5K / month Β· πŸ“¦ 9 Β· ⏱️ 24.09.2021): + ``` + pip install biopandas + ``` +- [Conda](https://anaconda.org/conda-forge/biopandas) (πŸ“₯ 96K Β· ⏱️ 31.08.2021): + ``` + conda install -c conda-forge biopandas + ``` +
+
apricot (πŸ₯‰16 Β· ⭐ 400) - apricot implements submodular optimization for the purpose of selecting.. MIT - [GitHub](https://github.com/jmschrei/apricot) (πŸ‘¨β€πŸ’» 4 Β· πŸ”€ 40 Β· πŸ“₯ 10 Β· πŸ“¦ 22 Β· πŸ“‹ 24 - 25% open Β· ⏱️ 18.11.2021): ``` git clone https://github.com/jmschrei/apricot ``` -- [PyPi](https://pypi.org/project/apricot-select) (πŸ“₯ 380 / month Β· πŸ“¦ 3 Β· ⏱️ 28.09.2020): +- [PyPi](https://pypi.org/project/apricot-select) (πŸ“₯ 300 / month Β· πŸ“¦ 3 Β· ⏱️ 28.09.2020): ``` pip install apricot-select ``` @@ -9160,20 +9924,23 @@ _Libraries for connecting to, operating, and querying databases._ git clone https://github.com/jrieke/traingenerator ```
-
Show 12 hidden projects... +
Show 15 hidden projects... -- datalad (πŸ₯ˆ31 Β· ⭐ 270) - Keep code, data, containers under control with git and git-annex. MIT -- Cython BLIS (πŸ₯ˆ29 Β· ⭐ 180) - Fast matrix-multiplication as a self-contained Python library no.. BSD-3 -- pysc2 (πŸ₯ˆ28 Β· ⭐ 7.4K Β· πŸ’€) - StarCraft II Learning Environment. Apache-2 -- minisom (πŸ₯‰23 Β· ⭐ 990) - MiniSom is a minimalistic implementation of the Self Organizing.. ❗️CC-BY-3.0 -- cleanlab (πŸ₯‰22 Β· ⭐ 2.6K) - The standard package for machine learning with noisy labels,.. ❗️AGPL-3.0 +- datalad (πŸ₯ˆ32 Β· ⭐ 280) - Keep code, data, containers under control with git and git-annex. MIT +- pysc2 (πŸ₯ˆ29 Β· ⭐ 7.4K Β· πŸ’€) - StarCraft II Learning Environment. Apache-2 +- Cython BLIS (πŸ₯ˆ28 Β· ⭐ 180) - Fast matrix-multiplication as a self-contained Python library no.. BSD-3 +- modAL (πŸ₯‰24 Β· ⭐ 1.6K Β· πŸ’€) - A modular active learning framework for Python. MIT +- minisom (πŸ₯‰23 Β· ⭐ 1K) - MiniSom is a minimalistic implementation of the Self Organizing Maps. ❗️CC-BY-3.0 +- MONAILabel (πŸ₯‰23 Β· ⭐ 200 Β· βž•) - MONAI Label is an intelligent open source image labeling and.. Apache-2 +- cleanlab (πŸ₯‰22 Β· ⭐ 2.6K) - The standard package for machine learning with label errors,.. ❗️AGPL-3.0 - mlens (πŸ₯‰21 Β· ⭐ 710 Β· πŸ’€) - ML-Ensemble high performance ensemble learning. MIT -- vecstack (πŸ₯‰21 Β· ⭐ 640 Β· πŸ’€) - Python package for stacking (machine learning technique). MIT +- vecstack (πŸ₯‰21 Β· ⭐ 650 Β· πŸ’€) - Python package for stacking (machine learning technique). MIT - rrcf (πŸ₯‰19 Β· ⭐ 350 Β· πŸ’€) - Implementation of the Robust Random Cut Forest algorithm for anomaly.. MIT - pandas-ml (πŸ₯‰18 Β· ⭐ 280 Β· πŸ’€) - pandas, scikit-learn, xgboost and seaborn integration. BSD-3 -- Feature Engine (πŸ₯‰17 Β· ⭐ 11) - Feature engineering package with sklearn like functionality. BSD-3 +- Feature Engine (πŸ₯‰18 Β· ⭐ 12) - Feature engineering package with sklearn like functionality. BSD-3 +- NeuralCompression (πŸ₯‰16 Β· ⭐ 240 Β· βž•) - A collection of tools for neural compression enthusiasts. MIT - dstack (πŸ₯‰12 Β· ⭐ 180) - An open-source tool to rapidly develop data applications with Python. Apache-2 -- nylon (πŸ₯‰11 Β· ⭐ 76) - An intelligent, flexible grammar of machine learning. MIT +- nylon (πŸ₯‰12 Β· ⭐ 78 Β· πŸ’€) - An intelligent, flexible grammar of machine learning. MIT
--- diff --git a/history/2022-02-10_changes.md b/history/2022-02-10_changes.md new file mode 100644 index 00000000..6dcb5e45 --- /dev/null +++ b/history/2022-02-10_changes.md @@ -0,0 +1,72 @@ +## πŸ“ˆ Trending Up + +_Projects that have a higher project-quality score compared to the last update. There might be a variety of reasons, such as increased downloads or code activity._ + +- MMDetection (πŸ₯‡37 Β· ⭐ 18K Β· πŸ“ˆ) - OpenMMLab Detection Toolbox and Benchmark. Apache-2 +- DeepSpeech (πŸ₯‡33 Β· ⭐ 19K Β· πŸ“ˆ) - DeepSpeech is an open source embedded (offline, on-.. MPL-2.0 +- Recommenders (πŸ₯‡32 Β· ⭐ 12K Β· πŸ“ˆ) - Best Practices on Recommendation Systems. MIT +- Ludwig (πŸ₯‰32 Β· ⭐ 8.1K Β· πŸ“ˆ) - Data-centric declarative deep learning framework. Apache-2 +- River (πŸ₯ˆ30 Β· ⭐ 3.2K Β· πŸ“ˆ) - Online machine learning in Python. BSD-3 +- Haiku (πŸ₯‰29 Β· ⭐ 1.7K Β· πŸ“ˆ) - JAX-based neural network library. Apache-2 +- Talos (πŸ₯ˆ26 Β· ⭐ 1.5K Β· πŸ“ˆ) - Hyperparameter Optimization for TensorFlow, Keras and PyTorch. MIT +- torchsde (πŸ₯‰21 Β· ⭐ 910 Β· πŸ’€) - Differentiable SDE solvers with GPU support and efficient.. Apache-2 +- TF Compression (πŸ₯‰21 Β· ⭐ 580 Β· πŸ“ˆ) - Data compression in TensorFlow. Apache-2 +- Torch-Struct (πŸ₯‰18 Β· ⭐ 1K Β· πŸ“ˆ) - Fast, general, and tested differentiable structured.. MIT + +## πŸ“‰ Trending Down + +_Projects that have a lower project-quality score compared to the last update. There might be a variety of reasons such as decreased downloads or code activity._ + +- tensor2tensor (πŸ₯ˆ33 Β· ⭐ 12K Β· πŸ“‰) - Library of deep learning models and datasets designed.. Apache-2 +- carla (πŸ₯ˆ31 Β· ⭐ 7.2K Β· πŸ“‰) - Open-source simulator for autonomous driving research. MIT +- category_encoders (πŸ₯ˆ31 Β· ⭐ 1.8K Β· πŸ“‰) - A library of sklearn compatible categorical variable.. BSD-3 +- snowballstemmer (πŸ₯ˆ30 Β· ⭐ 540 Β· πŸ“‰) - Snowball compiler and stemming algorithms. BSD-3 +- BentoML (πŸ₯ˆ27 Β· ⭐ 3.2K Β· πŸ“‰) - The Unified Model Serving Framework. Apache-2 +- TensorForce (πŸ₯‰27 Β· ⭐ 3.1K Β· πŸ“‰) - Tensorforce: a TensorFlow library for applied.. Apache-2 +- FATE (πŸ₯‰25 Β· ⭐ 3.9K Β· πŸ“‰) - An Industrial Grade Federated Learning Framework. Apache-2 +- fastNLP (πŸ₯‰25 Β· ⭐ 2.5K Β· πŸ“‰) - fastNLP: A Modularized and Extensible NLP Framework. Currently.. Apache-2 +- Elephas (πŸ₯‰25 Β· ⭐ 1.5K Β· πŸ“‰) - Distributed Deep learning with Keras & Spark. MIT keras +- openTSNE (πŸ₯‰24 Β· ⭐ 940 Β· πŸ“‰) - Extensible, parallel implementations of t-SNE. BSD-3 + +## βž• Added Projects + +_Projects that were recently added to this best-of list._ + +- triton (πŸ₯ˆ28 Β· ⭐ 3.5K Β· βž•) - Development repository for the Triton language and compiler. MIT +- adapter-transformers (πŸ₯ˆ28 Β· ⭐ 660 Β· βž•) - Huggingface Transformers + Adapters =. Apache-2 huggingface +- pandera (πŸ₯‰27 Β· ⭐ 1K Β· βž•) - A light-weight, flexible, and expressive data validation library.. MIT +- SynapseML (πŸ₯‰26 Β· ⭐ 3.1K Β· βž•) - Simple and Distributed Machine Learning. MIT +- icevision (πŸ₯‰25 Β· ⭐ 580 Β· βž•) - An Agnostic Computer Vision Framework - Pluggable to any.. Apache-2 +- sahi (πŸ₯‰24 Β· ⭐ 540 Β· βž•) - A lightweight vision library for performing large scale object detection/.. MIT +- rubrix (πŸ₯‰23 Β· ⭐ 840 Β· βž•) - Python framework for data-centric NLP. Apache-2 +- docarray (πŸ₯‰23 Β· ⭐ 520 Β· 🐣) - The data structure for unstructured data. Apache-2 +- MONAILabel (πŸ₯‰23 Β· ⭐ 200 Β· βž•) - MONAI Label is an intelligent open source image labeling and.. Apache-2 +- whoosh (πŸ₯‰23 Β· ⭐ 190 Β· βž•) - Pure-Python full-text search library. ❗️BSD-1-Clause +- happy-transformer (πŸ₯‰22 Β· ⭐ 260 Β· βž•) - A package built on top of Hugging Faces transformers.. Apache-2 huggingface +- OpenPrompt (πŸ₯‰21 Β· ⭐ 1.1K Β· 🐣) - An Open-Source Framework for Prompt-Learning. Apache-2 +- detoxify (πŸ₯‰21 Β· ⭐ 380 Β· βž•) - Trained models & code to predict toxic comments on all 3 Jigsaw.. Apache-2 +- TimeSide (πŸ₯‰21 Β· ⭐ 310 Β· πŸ’€) - Scalable audio processing framework written in Python with a.. ❗️AGPL-3.0 +- qdrant (πŸ₯‰20 Β· ⭐ 1.1K Β· βž•) - Qdrant - vector similarity search engine with extended filtering.. Apache-2 +- jraph (πŸ₯‰20 Β· ⭐ 820 Β· βž•) - A Graph Neural Network Library in Jax. Apache-2 +- kompute (πŸ₯‰20 Β· ⭐ 750 Β· βž•) - General purpose GPU compute framework built on Vulkan to support.. Apache-2 +- deepsnap (πŸ₯‰20 Β· ⭐ 390 Β· βž•) - Python library assists deep learning on graphs. MIT +- SerpentAI (πŸ₯‰19 Β· ⭐ 6.2K Β· πŸ’€) - Game Agent Framework. Helping you create AIs / Bots that learn to.. MIT +- chitra (πŸ₯‰19 Β· ⭐ 180 Β· βž•) - A multi-functional library for full-stack Deep Learning... Apache-2 +- prettymaps (πŸ₯‰18 Β· ⭐ 7.7K Β· βž•) - A small set of Python functions to draw pretty maps from.. ❗️AGPL-3.0 +- pytorchviz (πŸ₯‰18 Β· ⭐ 2.1K Β· πŸ’€) - A small package to create visualizations of PyTorch execution.. MIT +- FinQuant (πŸ₯‰18 Β· ⭐ 720 Β· πŸ’€) - A program for financial portfolio management, analysis and.. MIT +- parallelformers (πŸ₯‰18 Β· ⭐ 440 Β· βž•) - Parallelformers: An Efficient Model Parallelization.. Apache-2 +- equinox (πŸ₯‡18 Β· ⭐ 260 Β· βž•) - Callable PyTrees and filtered JIT/grad transformations =.. Apache-2 +- scenic (πŸ₯‰17 Β· ⭐ 720 Β· βž•) - Scenic: A Jax Library for Computer Vision Research and Beyond. Apache-2 +- mesh-transformer-jax (πŸ₯‰16 Β· ⭐ 3.8K Β· βž•) - Model parallel transformers in JAX and Haiku. Apache-2 +- ptgnn (πŸ₯‰16 Β· ⭐ 300 Β· βž•) - A PyTorch Graph Neural Network Library. MIT +- NeuralCompression (πŸ₯‰16 Β· ⭐ 240 Β· βž•) - A collection of tools for neural compression enthusiasts. MIT +- upgini (πŸ₯‰15 Β· ⭐ 21 Β· 🐣) - Automated feature discovery & enrichment library automatically find.. BSD-3 +- GraphGym (πŸ₯‰14 Β· ⭐ 880 Β· βž•) - Platform for designing and evaluating Graph Neural Networks (GNN). MIT +- caliban (πŸ₯‰14 Β· ⭐ 410 Β· πŸ’€) - Research workflows made easy, locally and in the Cloud. Apache-2 +- HugsVision (πŸ₯‰14 Β· ⭐ 140 Β· 🐣) - HugsVision is a easy to use huggingface wrapper for state-of-.. MIT huggingface +- datajob (πŸ₯‰14 Β· ⭐ 83 Β· βž•) - Build and deploy a serverless data pipeline on AWS with no effort. Apache-2 +- rliable (πŸ₯‰11 Β· ⭐ 310 Β· 🐣) - Library for reliable evaluation on RL and ML benchmarks, as.. Apache-2 +- jaxdf (πŸ₯‰8 Β· ⭐ 43 Β· 🐣) - A JAX-based research framework for writing differentiable.. ❗️LGPL-3.0 +- pyrtfolio (πŸ₯‰7 Β· ⭐ 100 Β· πŸ’€) - Python package to generate stock portfolios. ❗️GPL-3.0 + diff --git a/history/2022-02-10_projects.csv b/history/2022-02-10_projects.csv new file mode 100644 index 00000000..ffc18bbe --- /dev/null +++ b/history/2022-02-10_projects.csv @@ -0,0 +1,923 @@ +,name,github_id,category,resource,github_url,homepage,license,created_at,updated_at,last_commit_pushed_at,commit_count,recent_commit_count,fork_count,watchers_count,pr_count,open_issue_count,closed_issue_count,star_count,description,contributor_count,projectrank,show,latest_stable_release_published_at,latest_stable_release_number,release_count,pypi_id,conda_id,dockerhub_id,docs_url,labels,dependent_project_count,github_dependent_project_count,pypi_url,pypi_latest_release_published_at,pypi_dependent_project_count,pypi_monthly_downloads,monthly_downloads,conda_url,conda_latest_release_published_at,conda_total_downloads,dockerhub_url,dockerhub_latest_release_published_at,dockerhub_stars,dockerhub_pulls,projectrank_placing,github_release_downloads,helm_id,npm_id,npm_url,npm_latest_release_published_at,npm_dependent_project_count,npm_monthly_downloads,conda_dependent_project_count,trending,brew_id,apt_id,yum_id,snap_id,maven_id,maven_url,maven_latest_release_published_at,maven_dependent_project_count,dnf_id,yay_id,new_addition,updated_github_id +0,ANN Benchmarks,erikbern/ann-benchmarks,nn-search,True,https://github.com/erikbern/ann-benchmarks,https://github.com/erikbern/ann-benchmarks,MIT,2015-05-28 13:21:43.000,2022-02-09 07:27:50.000000,2021-12-30 20:02:39,1265.0,18.0,418,97.0,179.0,38.0,76.0,2754,Benchmarks of approximate nearest neighbor libraries in Python.,67.0,0,True,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, +1,best-of-web-python - Web Scraping,ml-tooling/best-of-web-python,web-scraping,True,https://github.com/ml-tooling/best-of-web-python,https://github.com/ml-tooling/best-of-web-python#web-scraping--crawling,CC-BY-SA-4.0,2021-01-05 13:09:27.000,2022-02-05 08:24:00.000000,2022-02-05 08:24:00,112.0,30.0,94,49.0,70.0,4.0,2.0,1428,Collection of web-scraping and crawling libraries.,8.0,0,True,2022-02-02 14:26:59.000,2022.01.27,32.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, +2,best-of-python - Data 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14:17:24,28964.0,818.0,13803,1105.0,23881.0,3396.0,18716.0,32672,"Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R..",2921.0,52,True,2022-01-22 14:47:00.000,1.4.0,101.0,pandas,conda-forge/pandas,,,['pandas'],689956.0,632823.0,https://pypi.org/project/pandas,2022-01-22 14:47:00.000,57133.0,75701256.0,76031313.0,https://anaconda.org/conda-forge/pandas,2022-01-22 19:10:32.784,22677902.0,,,,,1.0,135099.0,,,,,,,,,,,,,,,,,,,, +6,scikit-learn,scikit-learn/scikit-learn,ml-frameworks,,https://github.com/scikit-learn/scikit-learn,https://github.com/scikit-learn/scikit-learn,BSD-3-Clause,2010-08-17 09:43:38.000,2022-02-10 13:53:14.000000,2022-02-10 13:40:59,27861.0,345.0,22434,2207.0,12836.0,2478.0,7478.0,48978,scikit-learn: machine learning in Python.,2477.0,50,True,2021-12-25 20:30:08.000,1.0.2,60.0,scikit-learn,conda-forge/scikit-learn,,,['sklearn'],335434.0,310958.0,https://pypi.org/project/scikit-learn,2021-12-25 20:30:08.000,24476.0,26548100.0,26709980.0,https://anaconda.org/conda-forge/scikit-learn,2021-12-26 01:02:52.879,11169057.0,,,,,1.0,769.0,,,,,,,,,,,,,,,,,,,, +7,numpy,numpy/numpy,data-containers,,https://github.com/numpy/numpy,https://github.com/numpy/numpy,BSD-3-Clause,2010-09-13 23:02:39.000,2022-02-10 12:11:25.000000,2022-02-10 12:11:24,29120.0,746.0,6495,560.0,10678.0,2337.0,8252.0,19594,The fundamental package for scientific computing with Python.,1398.0,50,True,2022-02-04 01:26:51.000,1.22.2,122.0,numpy,conda-forge/numpy,,,,1080279.0,963276.0,https://pypi.org/project/numpy,2022-02-04 00:30:48.000,117003.0,95648807.0,96068928.0,https://anaconda.org/conda-forge/numpy,2022-02-04 08:10:36.589,28486304.0,,,,,1.0,458467.0,,,,,,,,,,,,,,,,,,,, +8,PyTorch,pytorch/pytorch,ml-frameworks,,https://github.com/pytorch/pytorch,https://github.com/pytorch/pytorch,BSD-3-Clause,2016-08-13 05:26:41.000,2022-02-10 14:01:51.000000,2022-02-10 08:39:24,43692.0,1974.0,14865,1594.0,48087.0,11204.0,16802.0,53900,Tensors and Dynamic neural networks in Python with strong GPU acceleration.,3091.0,49,True,2022-01-27 21:51:23.000,1.10.2,38.0,torch,pytorch/pytorch,,https://pytorch.org/docs/stable/index.html,['pytorch'],6775.0,,https://pypi.org/project/torch,2022-01-27 19:29:53.000,6775.0,6034501.0,6329123.0,https://anaconda.org/pytorch/pytorch,2022-01-27 19:20:29.419,15024456.0,,,,,1.0,1688.0,,,,,,,,,,,,,,,,,,,, +9,Matplotlib,matplotlib/matplotlib,data-viz,,https://github.com/matplotlib/matplotlib,https://github.com/matplotlib/matplotlib,Python-2.0,2011-02-19 03:17:12.000,2022-02-10 13:01:57.000000,2022-02-09 20:47:23,42109.0,813.0,6167,572.0,14107.0,1738.0,6841.0,15010,matplotlib: plotting with Python.,1333.0,49,True,2021-12-11 08:22:08.000,3.5.1,90.0,matplotlib,conda-forge/matplotlib,,,,551443.0,499005.0,https://pypi.org/project/matplotlib,2021-12-11 08:22:08.000,52438.0,27070238.0,27212358.0,https://anaconda.org/conda-forge/matplotlib,2021-12-13 20:23:04.086,10943284.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +10,scipy,scipy/scipy,others,,https://github.com/scipy/scipy,https://github.com/scipy/scipy,BSD-3-Clause,2011-03-09 18:52:03.000,2022-02-10 13:32:28.000000,2022-02-10 11:23:54,27265.0,570.0,4086,331.0,7670.0,1852.0,6407.0,9202,"Ecosystem of open-source software for mathematics, science, and engineering.",1230.0,49,True,2022-02-05 23:29:16.000,1.8.0,77.0,scipy,conda-forge/scipy,,,,513901.0,457543.0,https://pypi.org/project/scipy,2022-02-05 22:53:25.000,56358.0,35658903.0,35962297.0,https://anaconda.org/conda-forge/scipy,2022-02-09 01:10:04.440,20638614.0,,,,,1.0,338480.0,,,,,,,,,,,,,,,,,,,, +11,transformers,huggingface/transformers,nlp,,https://github.com/huggingface/transformers,https://github.com/huggingface/transformers,Apache-2.0,2018-10-29 13:56:00.000,2022-02-10 14:06:29.000000,2022-02-10 13:52:07,8944.0,630.0,13604,793.0,6883.0,439.0,8313.0,57945,"Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.",1144.0,48,True,2022-01-31 16:54:26.000,4.16.2,87.0,transformers,conda-forge/transformers,,,"['pytorch', 'tensorflow']",22857.0,22102.0,https://pypi.org/project/transformers,2022-01-31 16:52:49.000,755.0,3533043.0,3536467.0,https://anaconda.org/conda-forge/transformers,2022-01-31 21:40:31.059,94868.0,,,,,1.0,1427.0,,,,,,,,,,,,,,,,,,,, +12,Celery,celery/celery,data-pipelines,,https://github.com/celery/celery,https://github.com/celery/celery,BSD-3-Clause,2009-04-24 11:31:24.000,2022-02-10 08:37:34.000000,2022-02-09 13:17:17,11829.0,61.0,4207,475.0,2488.0,517.0,4161.0,18630,Asynchronous task queue/job queue based on distributed message passing.,1177.0,46,True,2021-12-29 05:52:09.000,5.2.3,187.0,celery,conda-forge/celery,,,,79224.0,64391.0,https://pypi.org/project/celery,2021-12-29 05:52:09.000,14833.0,5166992.0,5177979.0,https://anaconda.org/conda-forge/celery,2022-02-07 19:32:02.369,780088.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +13,nltk,nltk/nltk,nlp,,https://github.com/nltk/nltk,https://github.com/nltk/nltk,Apache-2.0,2009-09-07 10:53:58.000,2022-02-09 12:51:23.000000,2022-02-09 12:51:15,14220.0,52.0,2545,472.0,1335.0,211.0,1378.0,10435,Suite of libraries and programs for symbolic and statistical natural language processing for English.,412.0,45,True,2021-12-28 23:28:57.000,3.6.7,50.0,nltk,conda-forge/nltk,,,,141444.0,129650.0,https://pypi.org/project/nltk,2022-02-09 12:40:48.000,11794.0,11061653.0,11078592.0,https://anaconda.org/conda-forge/nltk,2021-12-29 03:25:44.981,1117979.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +14,Pillow,python-pillow/Pillow,image,,https://github.com/python-pillow/Pillow,https://github.com/python-pillow/Pillow,PIL,2012-07-24 21:38:39.000,2022-02-10 14:02:40.964000,2022-02-10 07:40:17,12590.0,299.0,1788,212.0,3597.0,152.0,2286.0,9433,The friendly PIL fork (Python Imaging Library).,385.0,45,True,2022-02-03 03:49:29.000,9.0.1,86.0,Pillow,conda-forge/pillow,,,,62222.0,,https://pypi.org/project/Pillow,2022-02-03 03:41:36.000,62222.0,36573980.0,36753891.0,https://anaconda.org/conda-forge/pillow,2022-02-10 14:02:40.964,12593798.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +15,Keras,keras-team/keras,ml-frameworks,,https://github.com/keras-team/keras,https://github.com/keras-team/keras,Apache-2.0,2015-03-28 00:35:42.000,2022-02-10 10:45:33.000000,2022-02-10 00:42:47,6465.0,275.0,18986,1978.0,4936.0,266.0,10856.0,53928,Deep Learning for humans.,1026.0,44,True,2022-02-03 05:13:44.000,2.8.0,61.0,keras,conda-forge/keras,,https://keras.io,['tensorflow'],224.0,,https://pypi.org/project/keras,2022-01-31 19:00:05.000,224.0,8052276.0,8083133.0,https://anaconda.org/conda-forge/keras,2022-02-04 15:14:03.939,2036568.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +16,Airflow,apache/airflow,data-pipelines,,https://github.com/apache/airflow,https://github.com/apache/airflow,Apache-2.0,2015-04-13 18:04:58.000,2022-02-10 14:39:54.000000,2022-02-10 14:38:53,14997.0,918.0,9976,732.0,15350.0,940.0,4111.0,25007,"Platform to programmatically author, schedule, and monitor workflows.",2261.0,44,True,2022-01-10 18:26:40.000,helm-chart/1.4.0,100.0,apache-airflow,conda-forge/airflow,apache/airflow,,,445.0,,https://pypi.org/project/apache-airflow,2021-12-21 16:23:13.000,445.0,4158017.0,4933774.0,https://anaconda.org/conda-forge/airflow,2021-12-22 16:00:13.998,536033.0,https://hub.docker.com/r/apache/airflow,2022-01-25 18:25:05.854481,317.0,62582840.0,1.0,245618.0,stable/airflow,,,,,,,,,,,,,,,,,,, +17,spaCy,explosion/spaCy,nlp,,https://github.com/explosion/spaCy,https://github.com/explosion/spaCy,MIT,2014-07-03 15:15:40.000,2022-02-10 12:45:46.000000,2022-02-10 12:45:46,15268.0,94.0,3654,563.0,2923.0,102.0,4934.0,22386,Industrial-strength Natural Language Processing (NLP) in Python.,648.0,44,True,2021-12-07 16:30:56.000,3.2.1,189.0,spacy,conda-forge/spacy,,,,36866.0,34660.0,https://pypi.org/project/spacy,2021-12-15 15:54:05.638,2206.0,3912953.0,3955410.0,https://anaconda.org/conda-forge/spacy,2022-01-14 17:00:05.760,2544596.0,,,,,1.0,3122.0,,,,,,,,,,,,,,,,,,,, +18,XGBoost,dmlc/xgboost,ml-frameworks,,https://github.com/dmlc/xgboost,https://github.com/dmlc/xgboost,Apache-2.0,2014-02-06 17:28:03.000,2022-02-10 12:40:57.000000,2022-02-10 08:58:02,5652.0,103.0,8297,942.0,3356.0,300.0,4025.0,22186,"Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and..",547.0,44,True,2022-01-17 16:17:38.000,1.5.2,61.0,xgboost,conda-forge/xgboost,,https://xgboost.readthedocs.io/en/latest/,,28087.0,26814.0,https://pypi.org/project/xgboost,2022-01-17 16:17:38.000,1273.0,8497475.0,8536219.0,https://anaconda.org/conda-forge/xgboost,2022-01-26 21:02:30.362,2283700.0,,,,,1.0,3698.0,,,,,,,,,,,,,,,,,,,, +19,networkx,networkx/networkx,graph,,https://github.com/networkx/networkx,https://github.com/networkx/networkx,BSD-3-Clause,2010-09-06 00:53:44.000,2022-02-10 13:32:52.000000,2022-02-09 19:08:51,6689.0,57.0,2466,277.0,2469.0,336.0,2464.0,10282,Network Analysis in Python.,566.0,44,True,2021-09-09 22:09:39.000,2.6.3,70.0,networkx,conda-forge/networkx,,,,110558.0,97502.0,https://pypi.org/project/networkx,2021-12-15 13:42:18.312,13056.0,16028326.0,16113788.0,https://anaconda.org/conda-forge/networkx,2021-10-26 12:59:30.009,5469623.0,,,,,1.0,57.0,,,,,,,,,,,,,,,,,,,, +20,SymPy,sympy/sympy,others,,https://github.com/sympy/sympy,https://github.com/sympy/sympy,BSD-3-Clause,2010-04-30 20:37:14.000,2022-02-10 12:35:52.000000,2022-02-10 05:42:14,50056.0,821.0,3508,289.0,11274.0,4242.0,7795.0,8849,A computer algebra system written in pure Python.,1124.0,44,True,2021-10-08 23:27:06.000,sympy-1.9,40.0,sympy,conda-forge/sympy,,,,43187.0,39140.0,https://pypi.org/project/sympy,2021-10-08 23:29:29.000,4047.0,1968011.0,1999277.0,https://anaconda.org/conda-forge/sympy,2021-11-06 22:30:34.086,1860163.0,,,,,1.0,443734.0,,,,,,,,,,,,,,,,,,,, +21,StatsModels,statsmodels/statsmodels,ml-frameworks,,https://github.com/statsmodels/statsmodels,https://github.com/statsmodels/statsmodels,BSD-3-Clause,2011-06-12 17:04:50.000,2022-02-10 07:38:44.000000,2022-02-09 07:36:38,14485.0,230.0,2430,258.0,3503.0,2263.0,2488.0,7095,Statsmodels: statistical modeling and econometrics in Python.,358.0,44,True,2022-02-08 18:11:09.000,0.13.2,30.0,statsmodels,conda-forge/statsmodels,,,,61864.0,57354.0,https://pypi.org/project/statsmodels,2022-02-08 18:11:09.000,4510.0,7515480.0,7597269.0,https://anaconda.org/conda-forge/statsmodels,2021-11-13 01:23:06.115,5561708.0,,,,,1.0,26.0,,,,,,,,,,,,,,,,,,,, +22,scikit-image,scikit-image/scikit-image,image,,https://github.com/scikit-image/scikit-image,https://github.com/scikit-image/scikit-image,BSD-2-Clause,2011-07-07 22:07:20.000,2022-02-10 05:05:39.000000,2022-02-10 05:05:39,13090.0,133.0,1929,184.0,3664.0,314.0,2047.0,4763,Image processing in Python.,542.0,44,True,2021-12-15 17:06:01.000,0.19.1,43.0,scikit-image,conda-forge/scikit-image,,,,101832.0,92823.0,https://pypi.org/project/scikit-image,2021-12-15 17:04:53.000,9009.0,4975111.0,5020858.0,https://anaconda.org/conda-forge/scikit-image,2021-12-17 22:08:09.599,3156559.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +23,Ray,ray-project/ray,distributed-ml,,https://github.com/ray-project/ray,https://github.com/ray-project/ray,Apache-2.0,2016-10-25 19:38:30.000,2022-02-10 14:15:29.000000,2022-02-10 12:44:22,11251.0,910.0,3238,417.0,12922.0,2321.0,7136.0,19140,"An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged..",629.0,43,True,2022-02-04 19:23:01.000,ray-1.10.0,65.0,ray,conda-forge/ray-tune,,,,4136.0,3904.0,https://pypi.org/project/ray,2022-02-04 18:58:12.000,232.0,853976.0,855581.0,https://anaconda.org/conda-forge/ray-tune,2022-02-07 13:21:59.855,22476.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +24,Bokeh,bokeh/bokeh,data-viz,,https://github.com/bokeh/bokeh,https://github.com/bokeh/bokeh,BSD-3-Clause,2012-03-26 15:40:01.000,2022-02-10 12:08:13.000000,2022-02-09 15:17:37,19487.0,118.0,3866,461.0,5088.0,703.0,6132.0,15952,"Interactive Data Visualization in the browser, from Python.",596.0,43,True,2021-11-22 17:49:14.000,2.4.2,118.0,bokeh,conda-forge/bokeh,,,,48331.0,44848.0,https://pypi.org/project/bokeh,2022-01-27 18:33:32.000,3483.0,2823540.0,2935353.0,https://anaconda.org/conda-forge/bokeh,2021-11-22 21:24:20.205,6485197.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +25,dask,dask/dask,distributed-ml,,https://github.com/dask/dask,https://github.com/dask/dask,BSD-3-Clause,2015-01-04 18:50:00.000,2022-02-10 14:27:38.000000,2022-02-10 14:27:38,6977.0,135.0,1430,228.0,4433.0,777.0,3429.0,9517,Parallel computing with task scheduling.,506.0,43,True,2022-01-28 20:32:36.000,2022.1.1,135.0,dask,conda-forge/dask,,,,36247.0,33696.0,https://pypi.org/project/dask,2022-01-28 20:32:36.000,2551.0,7577830.0,7649569.0,https://anaconda.org/conda-forge/dask,2022-01-29 02:27:03.372,4950007.0,,,,,1.0,,stable/dask,,,,,,,,,,,,,,,,,,, +26,Arrow,apache/arrow,data-containers,,https://github.com/apache/arrow,https://github.com/apache/arrow,Apache-2.0,2016-02-17 08:00:23.000,2022-02-10 14:36:42.000000,2022-02-10 13:11:06,10921.0,586.0,2200,334.0,11678.0,201.0,698.0,9070,Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing.,802.0,43,True,2021-11-18 03:54:39.000,6.0.1,36.0,pyarrow,conda-forge/arrow,,,,1477.0,64.0,https://pypi.org/project/pyarrow,2022-02-03 19:25:09.000,1413.0,50583485.0,50596141.0,https://anaconda.org/conda-forge/arrow,2022-01-27 20:04:47.163,873311.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +27,PySpark,apache/spark,ml-frameworks,,https://github.com/apache/spark,https://github.com/apache/spark,Apache-2.0,2014-02-25 08:00:08.000,2022-02-10 13:59:19.000000,2022-02-10 13:32:18,32329.0,668.0,25125,2088.0,35453.0,232.0,,32027,Apache Spark Python API.,2612.0,42,True,2022-01-26 05:20:58.000,3.2.1,28.0,pyspark,conda-forge/pyspark,,,['spark'],759.0,,https://pypi.org/project/pyspark,2022-01-26 05:20:58.000,759.0,17116541.0,17141118.0,https://anaconda.org/conda-forge/pyspark,2022-01-26 09:34:57.784,1450101.0,,,,,2.0,,stable/spark,,,,,,,,,,,,,,,,,,, +28,OpenAI Gym,openai/gym,reinforcement-learning,,https://github.com/openai/gym,https://github.com/openai/gym,MIT,2016-04-27 14:59:16.000,2022-02-09 10:19:07.000000,2022-02-08 16:20:18,1496.0,74.0,7337,991.0,1126.0,118.0,1380.0,26382,A toolkit for developing and comparing reinforcement learning algorithms.,343.0,42,True,2021-10-06 22:04:25.000,0.21.0,96.0,gym,conda-forge/gym,,,,28626.0,26284.0,https://pypi.org/project/gym,2021-10-06 22:04:25.000,2342.0,565948.0,570008.0,https://anaconda.org/conda-forge/gym,2022-02-08 14:22:06.829,89321.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +29,pytorch-lightning,PyTorchLightning/pytorch-lightning,ml-frameworks,,https://github.com/PyTorchLightning/pytorch-lightning,https://github.com/PyTorchLightning/pytorch-lightning,Apache-2.0,2019-03-31 00:45:57.000,2022-02-10 13:58:57.000000,2022-02-10 13:10:38,6520.0,493.0,2151,221.0,5631.0,490.0,4152.0,17301,"The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.",619.0,42,True,2022-02-09 20:53:39.000,1.5.10,203.0,pytorch-lightning,conda-forge/pytorch-lightning,,,['pytorch'],7107.0,6797.0,https://pypi.org/project/pytorch-lightning,2022-02-09 20:53:39.000,310.0,1118366.0,1138226.0,https://anaconda.org/conda-forge/pytorch-lightning,2022-01-21 10:04:45.400,393754.0,,,,,2.0,5381.0,,,,,,,,,,,,,,,,,,,, +30,LightGBM,microsoft/LightGBM,ml-frameworks,,https://github.com/microsoft/LightGBM,https://github.com/microsoft/LightGBM,MIT,2016-08-05 05:45:50.000,2022-02-06 22:52:22.000000,2022-02-01 02:45:53,2856.0,92.0,3459,446.0,2452.0,168.0,2381.0,13442,"A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision..",250.0,42,True,2022-01-07 15:20:18.000,3.3.2,28.0,lightgbm,conda-forge/lightgbm,,,,11743.0,11167.0,https://pypi.org/project/lightgbm,2022-01-07 15:20:18.000,576.0,9734667.0,9753142.0,https://anaconda.org/conda-forge/lightgbm,2022-01-08 00:29:45.463,886158.0,,,,,2.0,137137.0,,,,,,,,,,,,,,,,,,,, +31,Plotly,plotly/plotly.py,data-viz,,https://github.com/plotly/plotly.py,https://github.com/plotly/plotly.py,MIT,2013-11-21 05:53:08.000,2022-02-09 19:41:03.000000,2022-02-09 18:45:14,5379.0,69.0,2110,268.0,1301.0,1094.0,1162.0,10968,The interactive graphing library for Python (includes Plotly Express).,191.0,42,True,2022-02-09 18:43:08.000,5.6.0,277.0,plotly,conda-forge/plotly,,,,3852.0,9.0,https://pypi.org/project/plotly,2022-02-09 18:28:55.000,3839.0,7172374.0,7257364.0,https://anaconda.org/conda-forge/plotly,2021-12-21 05:39:52.763,2196223.0,,,,,1.0,,,plotlywidget,https://www.npmjs.com/package/plotlywidget,2021-01-12 16:09:46.133,4.0,51714.0,,,,,,,,,,,,,, +32,pydeck,visgl/deck.gl,geospatial-data,,https://github.com/visgl/deck.gl,https://github.com/visgl/deck.gl,MIT,2015-12-15 08:38:29.000,2022-02-10 14:13:46.000000,2022-02-10 14:13:42,3943.0,115.0,1720,1753.0,3705.0,139.0,2220.0,9441,WebGL2 powered visualization framework.,187.0,42,True,2022-02-02 00:06:12.571,8.6.8,517.0,pydeck,conda-forge/pydeck,,,['jupyter'],3953.0,3552.0,https://pypi.org/project/pydeck,2021-10-25 17:38:40.000,16.0,828851.0,1119988.0,https://anaconda.org/conda-forge/pydeck,2021-10-26 00:42:05.329,67883.0,,,,,1.0,,,deck.gl,https://www.npmjs.com/package/deck.gl,2022-02-10 08:30:10.984,385.0,288309.0,,,,,,,,,,,,,, +33,Tensorboard,tensorflow/tensorboard,ml-experiments,,https://github.com/tensorflow/tensorboard,https://github.com/tensorflow/tensorboard,Apache-2.0,2017-05-15 20:08:07.000,2022-02-10 00:27:14.000000,2022-02-10 00:27:13,4947.0,97.0,1469,190.0,3952.0,545.0,1089.0,5762,TensorFlows Visualization Toolkit.,275.0,42,True,2022-01-20 21:11:31.000,2.8.0,40.0,tensorboard,conda-forge/tensorboard,,,['tensorflow'],96092.0,93799.0,https://pypi.org/project/tensorboard,2022-01-20 21:11:31.000,2293.0,12839922.0,12893618.0,https://anaconda.org/conda-forge/tensorboard,2022-02-04 23:08:31.070,2738498.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +34,PaddlePaddle,PaddlePaddle/Paddle,ml-frameworks,,https://github.com/PaddlePaddle/Paddle,https://github.com/PaddlePaddle/Paddle,Apache-2.0,2016-08-15 06:59:08.000,2022-02-10 13:28:24.000000,2022-02-10 13:16:14,33858.0,1265.0,4253,733.0,25261.0,2773.0,12102.0,17572,PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice &.,701.0,41,True,2022-01-26 02:13:57.000,2.2.2,52.0,paddlepaddle,,,,['paddle'],135.0,91.0,https://pypi.org/project/paddlepaddle,2022-01-20 03:02:58.000,44.0,104732.0,104963.0,,,,,,,,2.0,15308.0,,,,,,,,,,,,,,,,,,,, +35,gensim,RaRe-Technologies/gensim,nlp,,https://github.com/RaRe-Technologies/gensim,https://github.com/RaRe-Technologies/gensim,LGPL-2.1,2011-02-10 07:43:04.000,2022-02-07 15:11:17.000000,2022-01-25 16:55:35,4302.0,15.0,4094,432.0,1577.0,380.0,1362.0,12898,Topic Modelling for Humans.,417.0,41,True,2021-09-18 14:21:47.000,4.1.2,89.0,gensim,conda-forge/gensim,,,,33079.0,30258.0,https://pypi.org/project/gensim,2021-09-17 00:24:57.000,2821.0,9557432.0,9571926.0,https://anaconda.org/conda-forge/gensim,2021-11-09 13:39:50.380,765770.0,,,,,1.0,3505.0,,,,,,,,,,,,,,,,,,,, +36,onnx,onnx/onnx,model-serialisation,,https://github.com/onnx/onnx,https://github.com/onnx/onnx,Apache-2.0,2017-09-07 04:53:45.000,2022-02-10 01:30:04.000000,2022-02-07 18:35:52,1895.0,43.0,2321,430.0,2134.0,481.0,1363.0,12033,Open standard for machine learning interoperability.,221.0,41,True,2021-10-26 19:14:09.000,1.10.2,24.0,onnx,conda-forge/onnx,,,,5827.0,5509.0,https://pypi.org/project/onnx,2021-10-26 19:14:09.000,318.0,1428310.0,1435515.0,https://anaconda.org/conda-forge/onnx,2021-12-14 07:56:56.053,350377.0,,,,,1.0,17421.0,,,,,,,,,,,,,,,,,,,, +37,torchvision,pytorch/vision,image,,https://github.com/pytorch/vision,https://github.com/pytorch/vision,BSD-3-Clause,2016-11-09 23:11:43.000,2022-02-10 12:48:02.000000,2022-02-10 10:34:02,2458.0,229.0,5588,361.0,3276.0,650.0,1608.0,10832,"Datasets, Transforms and Models specific to Computer Vision.",461.0,41,True,2022-01-27 22:31:01.000,0.11.3,29.0,torchvision,conda-forge/torchvision,,,['pytorch'],3482.0,,https://pypi.org/project/torchvision,2022-01-27 20:36:45.000,3482.0,2949258.0,2952673.0,https://anaconda.org/conda-forge/torchvision,2022-02-06 13:13:27.836,170765.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +38,Seaborn,mwaskom/seaborn,data-viz,,https://github.com/mwaskom/seaborn,https://github.com/mwaskom/seaborn,BSD-3-Clause,2012-06-18 18:41:19.000,2022-02-04 02:19:36.000000,2022-01-18 12:50:58,2814.0,6.0,1494,246.0,773.0,99.0,1864.0,9146,Statistical data visualization in Python.,162.0,41,True,2021-08-16 00:42:18.000,0.11.2,25.0,seaborn,conda-forge/seaborn,,,,147131.0,138289.0,https://pypi.org/project/seaborn,2021-08-16 00:42:18.000,8842.0,6902516.0,6952640.0,https://anaconda.org/conda-forge/seaborn,2021-08-16 06:42:17.619,3308070.0,,,,,1.0,211.0,,,,,,,,,,,,,,,,,,,, +39,Catboost,catboost/catboost,ml-frameworks,,https://github.com/catboost/catboost,https://github.com/catboost/catboost,Apache-2.0,2017-07-18 05:29:04.000,2022-02-10 13:08:26.000000,2022-02-10 13:08:24,21373.0,2191.0,954,192.0,280.0,348.0,1384.0,6343,"A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification,..",952.0,41,True,2022-01-14 11:45:18.000,1.0.4,101.0,catboost,conda-forge/catboost,,,,212.0,,https://pypi.org/project/catboost,2022-01-14 00:21:12.000,212.0,3321556.0,3343276.0,https://anaconda.org/conda-forge/catboost,2022-02-04 07:12:46.792,915024.0,,,,,2.0,73523.0,,,,,,,,,,,,,,,,,,,, +40,MXNet,apache/incubator-mxnet,ml-frameworks,,https://github.com/apache/incubator-mxnet,https://github.com/apache/incubator-mxnet,Apache-2.0,2015-04-30 16:21:15.000,2022-02-10 11:43:35.000000,2022-02-09 07:07:19,11784.0,57.0,6882,1098.0,10927.0,1953.0,7706.0,19851,"Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler;..",972.0,40,True,2021-12-18 21:55:54.000,1.9.0,981.0,mxnet,mxnet,,,['mxnet'],286.0,,https://pypi.org/project/mxnet,2021-12-18 21:55:54.000,281.0,286379.0,286873.0,https://anaconda.org/anaconda/mxnet,2020-02-29 00:58:31.007,6962.0,,,,,2.0,24547.0,,,,,,,5.0,,,,,,,,,,,,, +41,jax,google/jax,ml-frameworks,,https://github.com/google/jax,https://github.com/google/jax,Apache-2.0,2018-10-25 21:25:02.000,2022-02-10 14:03:12.000000,2022-02-10 00:50:00,10453.0,803.0,1478,256.0,5749.0,969.0,2082.0,16254,"Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more.",364.0,40,True,2022-02-04 04:56:35.000,test-jaxlib,106.0,jax,conda-forge/jaxlib,,,,3666.0,3411.0,https://pypi.org/project/jax,2022-01-18 19:35:52.000,255.0,286581.0,295379.0,https://anaconda.org/conda-forge/jaxlib,2021-12-10 12:52:23.006,272747.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +42,mlflow,mlflow/mlflow,ml-experiments,,https://github.com/mlflow/mlflow,https://github.com/mlflow/mlflow,Apache-2.0,2018-06-05 16:05:58.000,2022-02-10 13:19:33.000000,2022-02-09 21:01:25,2489.0,146.0,2485,278.0,3323.0,984.0,1197.0,11255,Open source platform for the machine learning lifecycle.,353.0,40,True,2022-01-27 05:28:31.000,1.23.1,54.0,mlflow,conda-forge/mlflow,,,,278.0,,https://pypi.org/project/mlflow,2022-01-27 05:11:35.000,278.0,14229259.0,14243255.0,https://anaconda.org/conda-forge/mlflow,2022-01-27 09:59:52.670,475869.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +43,h5py,h5py/h5py,data-containers,,https://github.com/h5py/h5py,https://github.com/h5py/h5py,BSD-3-Clause,2012-09-21 00:40:02.000,2022-02-10 14:27:25.000000,2022-02-10 14:27:25,3880.0,50.0,431,51.0,774.0,221.0,1063.0,1669,HDF5 for Python -- The h5py package is a Pythonic interface to the HDF5 binary data format.,176.0,40,True,2021-11-16 13:35:22.000,3.6.0,31.0,h5py,conda-forge/h5py,,,,162002.0,148472.0,https://pypi.org/project/h5py,2021-11-16 13:35:22.000,13530.0,11829194.0,11927727.0,https://anaconda.org/conda-forge/h5py,2021-11-26 22:25:41.747,6993901.0,,,,,1.0,1689.0,,,,,,,,,,,,,,,,,,,, +44,dask.distributed,dask/distributed,distributed-ml,,https://github.com/dask/distributed,https://github.com/dask/distributed,BSD-3-Clause,2015-09-13 18:42:29.000,2022-02-10 14:00:39.000000,2022-02-09 19:06:50,4348.0,135.0,586,67.0,3310.0,919.0,1685.0,1298,A distributed task scheduler for Dask.,262.0,40,True,2022-01-14 20:40:27.000,2022.1.0,166.0,distributed,conda-forge/distributed,,,,23168.0,22018.0,https://pypi.org/project/distributed,2022-01-28 20:32:37.000,1150.0,6606109.0,6695991.0,https://anaconda.org/conda-forge/distributed,2022-01-29 01:07:45.900,6201893.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +45,shap,slundberg/shap,interpretability,,https://github.com/slundberg/shap,https://github.com/slundberg/shap,MIT,2016-11-22 19:17:08.000,2022-02-04 00:16:48.000000,2021-12-04 17:24:08,2011.0,3.0,2277,247.0,418.0,1251.0,571.0,15424,A game theoretic approach to explain the output of any machine learning model.,162.0,39,True,2021-10-20 18:36:57.000,0.40.0,94.0,shap,conda-forge/shap,,,,4676.0,4455.0,https://pypi.org/project/shap,2021-10-20 19:13:31.000,221.0,4555836.0,4575791.0,https://anaconda.org/conda-forge/shap,2022-01-23 08:45:26.945,838127.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +46,Rasa,RasaHQ/rasa,nlp,,https://github.com/RasaHQ/rasa,https://github.com/RasaHQ/rasa,Apache-2.0,2016-10-14 12:27:49.000,2022-02-10 13:56:39.000000,2022-02-10 11:51:20,29848.0,566.0,3851,338.0,4393.0,979.0,5558.0,13538,"Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management,..",527.0,39,True,2022-02-01 18:02:21.000,2.8.23,242.0,rasa,,,,['tensorflow'],57.0,,https://pypi.org/project/rasa,2022-01-28 18:20:51.000,57.0,233306.0,233306.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +47,flair,flairNLP/flair,nlp,,https://github.com/flairNLP/flair,https://github.com/flairNLP/flair,MIT,2018-06-11 11:04:18.000,2022-02-09 20:47:53.000000,2022-02-09 20:38:26,4310.0,439.0,1769,201.0,877.0,88.0,1671.0,11233,A very simple framework for state-of-the-art Natural Language Processing (NLP).,218.0,39,True,2021-11-18 08:33:59.000,0.10,23.0,flair,conda-forge/python-flair,,,['pytorch'],1218.0,1152.0,https://pypi.org/project/flair,2021-11-18 08:22:02.000,66.0,75906.0,76257.0,https://anaconda.org/conda-forge/python-flair,2021-11-18 16:11:16.757,6672.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +48,dlib,davisking/dlib,ml-frameworks,,https://github.com/davisking/dlib,https://github.com/davisking/dlib,BSL-1.0,2014-01-29 00:45:33.000,2022-02-07 14:49:20.000000,2022-02-07 03:26:31,8027.0,43.0,3024,479.0,519.0,37.0,1946.0,10909,A toolkit for making real world machine learning and data analysis applications in C++.,172.0,39,False,2022-01-25 03:42:43.000,19.23.0,30.0,dlib,conda-forge/dlib,,,,13699.0,12934.0,https://pypi.org/project/dlib,2022-01-25 03:42:43.000,765.0,108027.0,114244.0,https://anaconda.org/conda-forge/dlib,2021-04-03 09:47:47.788,383986.0,,,,,2.0,24869.0,,,,,,,,,,,,,,,,,,,, +49,Milvus,milvus-io/milvus,nn-search,,https://github.com/milvus-io/milvus,https://github.com/milvus-io/milvus,Apache-2.0,2019-09-16 06:43:43.000,2022-02-10 12:00:52.000000,2022-02-10 12:00:51,14152.0,2902.0,1322,190.0,10637.0,237.0,4218.0,9397,An open-source vector database for scalable similarity search and AI applications.,185.0,39,True,2022-01-25 12:14:19.000,2.0.0,100.0,pymilvus,,milvusdb/milvus,,,15.0,,https://pypi.org/project/pymilvus,2022-01-25 10:52:10.000,15.0,32188.0,61369.0,,,,https://hub.docker.com/r/milvusdb/milvus,2022-01-25 10:07:04.034621,18.0,797109.0,1.0,6781.0,,,,,,,,,,,,,,,,,,,, +50,Altair,altair-viz/altair,data-viz,,https://github.com/altair-viz/altair,https://github.com/altair-viz/altair,BSD-3-Clause,2015-09-19 03:14:04.000,2022-02-09 00:47:44.000000,2022-02-07 13:53:02,3111.0,16.0,630,150.0,960.0,240.0,1355.0,7257,Declarative statistical visualization library for Python.,134.0,39,True,2021-12-29 13:30:58.000,4.2.0,28.0,altair,conda-forge/altair,,,,22127.0,21783.0,https://pypi.org/project/altair,2021-12-29 13:25:37.000,344.0,4698891.0,4714821.0,https://anaconda.org/conda-forge/altair,2021-12-29 17:47:26.885,1067325.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +51,Beam,apache/beam,data-pipelines,,https://github.com/apache/beam,https://github.com/apache/beam,Apache-2.0,2016-02-02 08:00:06.000,2022-02-10 14:44:51.000000,2022-02-10 02:54:03,34601.0,1022.0,3359,254.0,16790.0,191.0,,5275,"Unified programming model to define and execute data processing pipelines, including ETL, batch and stream processing.",1217.0,39,True,2022-02-10 06:49:13.000,2.29.0,55.0,apache-beam,conda-forge/apache-beam-with-aws,,,,146.0,,https://pypi.org/project/apache-beam,2022-02-07 22:48:13.000,146.0,15058673.0,15059445.0,https://anaconda.org/conda-forge/apache-beam-with-aws,2022-02-08 20:12:09.852,3860.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +52,joblib,joblib/joblib,data-pipelines,,https://github.com/joblib/joblib,https://github.com/joblib/joblib,BSD-3-Clause,2010-05-07 06:48:26.000,2022-02-10 08:09:19.000000,2022-02-08 08:20:22,1396.0,11.0,315,63.0,593.0,332.0,383.0,2672,Computing with Python functions.,108.0,39,True,2021-10-07 14:42:42.000,1.1.0,102.0,joblib,conda-forge/joblib,,,,164341.0,159450.0,https://pypi.org/project/joblib,2021-10-07 14:42:42.000,4891.0,27374932.0,27480235.0,https://anaconda.org/conda-forge/joblib,2021-10-07 20:15:36.705,7055328.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +53,Streamlit,streamlit/streamlit,others,,https://github.com/streamlit/streamlit,https://github.com/streamlit/streamlit,Apache-2.0,2019-08-24 00:14:52.000,2022-02-10 06:34:58.000000,2022-02-08 20:19:15,4573.0,106.0,1575,256.0,2076.0,553.0,1722.0,17650,Streamlit The fastest way to build data apps in Python.,134.0,38,True,2022-02-09 16:13:01.000,1.5.1,149.0,streamlit,,,,,524.0,221.0,https://pypi.org/project/streamlit,2022-02-09 16:09:41.000,303.0,856793.0,856793.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +54,dash,plotly/dash,data-viz,,https://github.com/plotly/dash,https://github.com/plotly/dash,MIT,2015-04-10 01:53:08.000,2022-02-10 14:50:00.000000,2022-01-31 20:23:12,5653.0,92.0,1635,395.0,658.0,570.0,624.0,15896,"Analytical Web Apps for Python, R, Julia, and Jupyter. No JavaScript Required.",105.0,38,True,2022-01-28 23:52:55.000,2.1.0,144.0,dash,conda-forge/dash,,,,1324.0,176.0,https://pypi.org/project/dash,2022-01-28 23:39:18.000,1148.0,930025.0,937865.0,https://anaconda.org/conda-forge/dash,2022-01-29 09:06:55.006,352801.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +55,luigi,spotify/luigi,data-pipelines,,https://github.com/spotify/luigi,https://github.com/spotify/luigi,Apache-2.0,2012-09-20 15:06:38.000,2022-02-04 10:21:49.000000,2022-01-16 15:01:41,4022.0,13.0,2314,489.0,2211.0,103.0,864.0,15373,"Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution,..",580.0,38,True,2021-11-06 14:59:15.000,3.0.3,73.0,luigi,luigi,,,,2040.0,1641.0,https://pypi.org/project/luigi,2020-09-23 11:57:12.000,397.0,618136.0,618259.0,https://anaconda.org/anaconda/luigi,2022-01-20 12:21:28.388,8911.0,,,,,1.0,,stable/luigi,,,,,,2.0,,,,,,,,,,,,, +56,Jina,jina-ai/jina,ml-frameworks,,https://github.com/jina-ai/jina,https://github.com/jina-ai/jina,Apache-2.0,2020-02-13 17:04:44.000,2022-02-10 12:24:34.000000,2022-02-09 23:08:35,7003.0,333.0,1765,171.0,2941.0,79.0,1252.0,13396,Cloud-native neural search framework for kind of data.,136.0,38,True,2022-01-04 08:43:20.000,2.6.4,1570.0,jina,conda-forge/jina-core,jinaai/jina,,,223.0,223.0,https://pypi.org/project/jina,2022-02-07 08:30:01.000,,36423.0,79391.0,https://anaconda.org/conda-forge/jina-core,2021-11-01 13:29:05.596,2230.0,https://hub.docker.com/r/jinaai/jina,2022-02-07 08:54:42.362537,6.0,1020529.0,2.0,,,,,,,,,,,,,,,,,,,,, +57,AllenNLP,allenai/allennlp,nlp,,https://github.com/allenai/allennlp,https://github.com/allenai/allennlp,Apache-2.0,2017-05-15 15:52:41.000,2022-02-10 02:33:16.000000,2022-02-10 02:33:14,2651.0,43.0,2156,281.0,3016.0,108.0,2396.0,10794,"An open-source NLP research library, built on PyTorch.",255.0,38,True,2022-01-27 18:12:46.000,2.9.0,260.0,allennlp,conda-forge/allennlp,,,['pytorch'],2390.0,2214.0,https://pypi.org/project/allennlp,2022-01-27 18:12:46.000,176.0,37392.0,38436.0,https://anaconda.org/conda-forge/allennlp,2022-02-06 21:44:10.661,39694.0,,,,,1.0,44.0,,,,,,,,,,,,,,,,,,,, +58,rq,rq/rq,data-pipelines,,https://github.com/rq/rq,https://github.com/rq/rq,BSD-3-Clause,2011-11-14 10:53:48.000,2022-02-07 13:14:34.000000,2022-02-07 13:00:11,1621.0,9.0,1261,218.0,667.0,169.0,774.0,8135,Simple job queues for Python.,250.0,38,True,2021-12-07 12:48:17.000,1.10.1,68.0,rq,conda-forge/rq,,,,11321.0,9586.0,https://pypi.org/project/rq,2021-12-07 12:46:58.000,1735.0,541653.0,542665.0,https://anaconda.org/conda-forge/rq,2021-06-30 09:49:43.099,67812.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +59,PyMC3,pymc-devs/pymc,probabilistics,,https://github.com/pymc-devs/pymc,https://github.com/pymc-devs/pymc,Apache-2.0,2009-05-05 09:43:50.000,2022-02-10 06:07:56.000000,2022-02-09 16:36:06,8401.0,208.0,1505,230.0,2880.0,217.0,2346.0,6346,Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Aesara.,361.0,38,True,2021-08-24 01:17:21.000,3.11.4,35.0,pymc3,conda-forge/pymc3,,,,814.0,584.0,https://pypi.org/project/pymc3,2021-08-24 01:17:21.000,230.0,316008.0,322015.0,https://anaconda.org/conda-forge/pymc3,2021-10-12 16:32:39.553,383244.0,,,,,1.0,1727.0,,,,,,,,,,,,,,,,,,,, +60,Optuna,optuna/optuna,hyperopt,,https://github.com/optuna/optuna,https://github.com/optuna/optuna,MIT,2018-02-21 06:12:56.000,2022-02-10 14:07:05.000000,2022-02-10 04:45:25,11541.0,509.0,650,130.0,2250.0,142.0,947.0,5926,A hyperparameter optimization framework.,175.0,38,True,2021-10-04 06:37:16.000,2.10.0,43.0,optuna,conda-forge/optuna,,,,2809.0,2631.0,https://pypi.org/project/optuna,2022-02-07 06:51:49.000,178.0,832820.0,836372.0,https://anaconda.org/conda-forge/optuna,2021-10-04 08:58:48.864,95930.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +61,CuPy,cupy/cupy,gpu-utilities,,https://github.com/cupy/cupy,https://github.com/cupy/cupy,MIT,2016-11-01 09:54:45.000,2022-02-10 08:31:59.000000,2022-02-10 04:57:32,24611.0,754.0,558,121.0,4835.0,387.0,1292.0,5753,NumPy & SciPy for GPU.,294.0,38,True,2022-01-20 08:11:40.000,10.1.0,107.0,cupy,conda-forge/cupy,cupy/cupy,,,1065.0,917.0,https://pypi.org/project/cupy,2022-01-20 07:46:45.000,148.0,88455.0,130946.0,https://anaconda.org/conda-forge/cupy,2022-02-03 02:22:51.812,1152751.0,https://hub.docker.com/r/cupy/cupy,2022-01-20 08:15:25.232919,7.0,54245.0,1.0,24910.0,,,,,,,,,,,,,,,,,,,, +62,xarray,pydata/xarray,data-containers,,https://github.com/pydata/xarray,https://github.com/pydata/xarray,Apache-2.0,2013-09-30 17:21:10.000,2022-02-10 14:22:42.000000,2022-02-09 15:12:31,4017.0,107.0,763,106.0,2815.0,927.0,2240.0,2398,N-D labeled arrays and datasets in Python.,360.0,38,True,2022-02-01 05:41:40.000,0.21.1,65.0,xarray,conda-forge/xarray,,,,10323.0,9013.0,https://pypi.org/project/xarray,2022-02-01 05:41:40.000,1310.0,1044267.0,1108685.0,https://anaconda.org/conda-forge/xarray,2022-02-01 14:46:25.966,4573713.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +63,Fastai,fastai/fastai,ml-frameworks,,https://github.com/fastai/fastai,https://github.com/fastai/fastai,Apache-2.0,2017-09-09 17:43:36.000,2022-02-10 05:36:37.000000,2022-02-09 22:21:18,1864.0,14.0,7126,630.0,2013.0,96.0,1453.0,21917,The fastai deep learning library.,605.0,37,True,2021-10-23 07:16:08.000,2.5.3,126.0,fastai,,,,['pytorch'],288.0,,https://pypi.org/project/fastai,2021-10-23 07:16:08.000,288.0,233472.0,233472.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +64,MMDetection,open-mmlab/mmdetection,image,,https://github.com/open-mmlab/mmdetection,https://github.com/open-mmlab/mmdetection,Apache-2.0,2018-08-22 07:06:06.000,2022-02-10 13:14:40.000000,2022-02-08 10:54:03,1920.0,115.0,6635,350.0,1967.0,509.0,4688.0,18248,OpenMMLab Detection Toolbox and Benchmark.,305.0,37,True,2022-02-08 14:05:27.000,2.21.0,29.0,mmdet,,,,['pytorch'],254.0,248.0,https://pypi.org/project/mmdet,2022-02-08 14:05:27.000,6.0,33370.0,33370.0,,,,,,,,1.0,,,,,,,,,4.0,,,,,,,,,,,, +65,PyTorch Image Models,rwightman/pytorch-image-models,image,,https://github.com/rwightman/pytorch-image-models,https://github.com/rwightman/pytorch-image-models,Apache-2.0,2019-02-02 05:51:12.000,2022-02-02 17:15:20.000000,2022-02-02 17:15:20,1266.0,95.0,2617,266.0,208.0,68.0,396.0,16368,"PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision..",65.0,37,True,2022-01-31 23:25:04.000,0.1-mit-weights,29.0,timm,conda-forge/timm,,,['pytorch'],1984.0,1917.0,https://pypi.org/project/timm,2022-01-17 04:57:50.000,67.0,532978.0,560735.0,https://anaconda.org/conda-forge/timm,2021-06-30 20:44:15.682,12018.0,,,,,1.0,895144.0,,,,,,,,,,,,,,,,,,,, +66,Theano,Theano/Theano,ml-frameworks,,https://github.com/Theano/Theano,https://github.com/Theano/Theano,BSD-3-Clause,2011-08-10 03:48:06.000,2021-12-01 00:24:43.000000,2021-11-23 08:52:10,28127.0,1.0,2509,561.0,4114.0,679.0,2086.0,9523,"Theano was a Python library that allows you to define, optimize, and evaluate mathematical expressions involving..",384.0,37,True,2020-07-27 16:13:54.000,1.0.5,45.0,theano,conda-forge/theano,,,,14904.0,12066.0,https://pypi.org/project/theano,2020-07-27 16:13:54.000,2838.0,270634.0,298031.0,https://anaconda.org/conda-forge/theano,2021-11-10 16:59:17.809,1835654.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +67,Prefect,PrefectHQ/prefect,data-pipelines,,https://github.com/PrefectHQ/prefect,https://github.com/PrefectHQ/prefect,Apache-2.0,2018-06-29 21:59:26.000,2022-02-10 14:46:59.000000,2022-02-09 23:34:10,14366.0,167.0,801,142.0,2988.0,422.0,1633.0,8256,The easiest way to automate your data.,292.0,37,True,2022-01-25 17:46:53.000,0.15.13,119.0,prefect,conda-forge/prefect,,,,631.0,591.0,https://pypi.org/project/prefect,2022-02-09 00:08:32.000,40.0,174109.0,180924.0,https://anaconda.org/conda-forge/prefect,2022-01-25 22:44:23.145,238558.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +68,PyCaret,pycaret/pycaret,ml-experiments,,https://github.com/pycaret/pycaret,https://github.com/pycaret/pycaret,MIT,2019-11-23 18:40:48.000,2022-02-10 07:36:23.000000,2022-02-03 13:23:40,2171.0,198.0,1145,105.0,582.0,205.0,1101.0,5105,"An open-source, low-code machine learning library in Python.",72.0,37,True,2022-01-12 14:42:28.000,2.3.6,75.0,pycaret,conda-forge/pycaret,,,,1795.0,1783.0,https://pypi.org/project/pycaret,2022-01-12 14:42:28.000,12.0,324166.0,324595.0,https://anaconda.org/conda-forge/pycaret,2022-01-12 19:29:46.287,7238.0,,,,,1.0,521.0,,,,,,,,,,,,,,,,,,,, +69,Dagster,dagster-io/dagster,data-pipelines,,https://github.com/dagster-io/dagster,https://github.com/dagster-io/dagster,Apache-2.0,2018-04-30 16:30:04.000,2022-02-10 06:48:53.000000,2022-02-10 06:22:46,9622.0,573.0,528,79.0,2750.0,910.0,2760.0,4330,"An orchestration platform for the development, production, and observation of data assets.",186.0,37,True,2022-02-07 15:53:25.000,0.13.18,422.0,dagster,conda-forge/dagster,,,,389.0,305.0,https://pypi.org/project/dagster,2022-02-03 20:56:00.000,84.0,179572.0,196093.0,https://anaconda.org/conda-forge/dagster,2022-02-04 01:49:39.103,446091.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +70,tensorflow-probability,tensorflow/probability,probabilistics,,https://github.com/tensorflow/probability,https://github.com/tensorflow/probability,Apache-2.0,2017-10-23 23:50:54.000,2022-02-09 21:48:10.000000,2022-02-09 21:48:06,11286.0,134.0,961,173.0,387.0,543.0,639.0,3589,Probabilistic reasoning and statistical analysis in TensorFlow.,435.0,37,True,2021-11-18 15:49:59.000,0.15.0,41.0,tensorflow-probability,conda-forge/tensorflow-probability,,,['tensorflow'],306.0,,https://pypi.org/project/tensorflow-probability,2021-11-17 17:40:22.000,306.0,706176.0,707544.0,https://anaconda.org/conda-forge/tensorflow-probability,2022-01-26 19:31:32.633,49265.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +71,Shapely,shapely/shapely,geospatial-data,,https://github.com/shapely/shapely,https://github.com/shapely/shapely,BSD-3-Clause,2011-12-31 19:43:11.000,2022-02-10 05:01:34.000000,2022-02-07 11:25:47,1990.0,39.0,440,89.0,482.0,152.0,672.0,2633,Manipulation and analysis of geometric objects.,131.0,37,True,2021-10-25 16:52:16.000,1.8.0,105.0,shapely,conda-forge/shapely,,,,29689.0,26054.0,https://pypi.org/project/shapely,2021-10-25 16:26:07.000,3635.0,6550273.0,6592236.0,https://anaconda.org/conda-forge/shapely,2022-01-19 02:15:44.771,3189237.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +72,MNE,mne-tools/mne-python,medical-data,,https://github.com/mne-tools/mne-python,https://github.com/mne-tools/mne-python,BSD-3-Clause,2011-01-28 03:31:13.000,2022-02-10 14:39:59.000000,2022-02-10 14:39:59,16648.0,213.0,973,77.0,6387.0,354.0,3573.0,1804,MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python.,279.0,37,True,2021-12-01 22:27:11.000,0.24.1,58.0,mne,conda-forge/mne,,,,1577.0,1385.0,https://pypi.org/project/mne,2021-12-01 22:27:11.000,192.0,30114.0,33154.0,https://anaconda.org/conda-forge/mne,2021-12-18 15:46:02.719,182448.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +73,TF Addons,tensorflow/addons,tensorflow-utils,,https://github.com/tensorflow/addons,https://github.com/tensorflow/addons,Apache-2.0,2018-11-26 23:57:17.000,2022-02-10 03:51:02.000000,2022-02-01 21:38:31,1434.0,21.0,489,58.0,1775.0,218.0,702.0,1443,Useful extra functionality for TensorFlow 2.x maintained by SIG-addons.,185.0,37,True,2021-11-10 21:09:55.000,0.15.0,28.0,tensorflow-addons,,,,['tensorflow'],5464.0,5325.0,https://pypi.org/project/tensorflow-addons,2021-11-10 21:40:18.000,139.0,6402024.0,6402024.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +74,Graphviz,xflr6/graphviz,data-viz,,https://github.com/xflr6/graphviz,https://github.com/xflr6/graphviz,MIT,2014-01-12 17:49:29.000,2022-01-29 02:59:16.000000,2022-01-20 10:23:04,1132.0,275.0,172,30.0,33.0,7.0,119.0,1135,Simple Python interface for Graphviz.,18.0,37,True,2021-12-12 11:06:31.000,0.19.1,53.0,graphviz,anaconda/python-graphviz,,,,30720.0,27818.0,https://pypi.org/project/graphviz,2021-12-12 11:06:31.000,2902.0,8978981.0,8979278.0,https://anaconda.org/anaconda/python-graphviz,2021-02-04 16:09:32.067,17266.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +75,imageio,imageio/imageio,image,,https://github.com/imageio/imageio,https://github.com/imageio/imageio,BSD-2-Clause,2013-05-04 22:56:45.000,2022-02-10 12:38:57.000000,2022-02-10 10:39:17,1337.0,49.0,198,30.0,331.0,75.0,353.0,982,Python library for reading and writing image data.,85.0,37,True,2022-02-07 12:40:56.000,2.15.0,48.0,imageio,conda-forge/imageio,,,,58137.0,55568.0,https://pypi.org/project/imageio,2022-02-07 12:40:53.000,2569.0,12862586.0,12903786.0,https://anaconda.org/conda-forge/imageio,2022-01-26 16:25:32.716,2513056.0,,,,,1.0,137.0,,,,,,,,,,,,,,,,,,,, +76,PaddleOCR,PaddlePaddle/PaddleOCR,ocr,,https://github.com/PaddlePaddle/PaddleOCR,https://github.com/PaddlePaddle/PaddleOCR,Apache-2.0,2020-05-08 10:38:16.000,2022-02-10 13:32:06.000000,2022-02-10 13:32:06,3904.0,442.0,3860,335.0,1598.0,1014.0,2918.0,18846,"Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages..",85.0,36,True,2021-05-26 11:43:06.000,2.1.1,20.0,paddleocr,,,,['paddle'],540.0,536.0,https://pypi.org/project/paddleocr,2022-01-10 07:14:20.000,4.0,38531.0,38531.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +77,PyFlink,apache/flink,ml-frameworks,,https://github.com/apache/flink,https://github.com/apache/flink,Apache-2.0,2014-06-07 07:00:10.000,2022-02-10 14:04:10.000000,2022-02-10 12:19:48,29833.0,971.0,10017,926.0,18693.0,690.0,,18145,Apache Flink Python API.,1461.0,36,True,2022-01-17 18:51:51.000,1.14.3,28.0,apache-flink,,,,,9.0,,https://pypi.org/project/apache-flink,2022-01-17 18:51:51.000,9.0,9041.0,9041.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +78,fairseq,pytorch/fairseq,nlp,,https://github.com/pytorch/fairseq,https://github.com/pytorch/fairseq,MIT,2017-08-29 16:26:12.000,2022-02-10 09:39:16.000000,2022-02-09 18:47:56,2121.0,73.0,4001,340.0,995.0,1158.0,2043.0,15920,Facebook AI Research Sequence-to-Sequence Toolkit written in Python.,374.0,36,True,2021-01-05 20:26:45.000,0.10.2,13.0,fairseq,conda-forge/fairseq,,,['pytorch'],681.0,653.0,https://pypi.org/project/fairseq,2021-01-05 20:26:45.000,28.0,34640.0,35325.0,https://anaconda.org/conda-forge/fairseq,2021-04-28 18:08:39.753,12971.0,,,,,1.0,172.0,,,,,,,,,,,,,,,,,,,, +79,horovod,horovod/horovod,distributed-ml,,https://github.com/horovod/horovod,https://github.com/horovod/horovod,Apache-2.0,2017-08-09 19:39:59.000,2022-02-07 22:32:07.000000,2022-02-04 12:11:02,1139.0,45.0,1957,334.0,1321.0,274.0,1673.0,12121,"Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.",140.0,36,True,2021-10-06 18:03:55.000,0.23.0,67.0,horovod,,,,,526.0,497.0,https://pypi.org/project/horovod,2021-10-06 18:03:55.000,29.0,48433.0,48433.0,,,,,,,,1.0,,stable/horovod,,,,,,,,,,,,,,,,,,, +80,NNI,microsoft/nni,hyperopt,,https://github.com/microsoft/nni,https://github.com/microsoft/nni,MIT,2018-06-01 05:51:44.000,2022-02-10 10:20:53.000000,2022-02-10 06:48:42,2487.0,102.0,1534,270.0,2893.0,258.0,1244.0,10980,"An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural..",156.0,36,True,2022-01-19 08:30:20.000,2.6,47.0,nni,,,,,213.0,185.0,https://pypi.org/project/nni,2022-01-19 08:21:54.000,28.0,8590.0,8590.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +81,DVC,iterative/dvc,ml-experiments,,https://github.com/iterative/dvc,https://github.com/iterative/dvc,Apache-2.0,2017-03-04 08:16:33.000,2022-02-10 11:01:33.000000,2022-02-10 11:01:32,7291.0,248.0,882,130.0,3675.0,609.0,2899.0,9244,Data Version Control | Git for Data & Models | ML Experiments Management.,259.0,36,True,2021-12-22 15:13:37.000,2.9.3,344.0,dvc,conda-forge/dvc,,,,46.0,,https://pypi.org/project/dvc,2021-12-22 15:13:37.000,46.0,342931.0,377992.0,https://anaconda.org/conda-forge/dvc,2021-12-25 11:03:28.304,983989.0,,,,,1.0,59762.0,,,,,,,,,dvc,dvc,dvc,,,,,,,,, +82,pandas-profiling,pandas-profiling/pandas-profiling,data-viz,,https://github.com/pandas-profiling/pandas-profiling,https://github.com/pandas-profiling/pandas-profiling,MIT,2016-01-09 23:47:55.000,2022-02-04 11:20:00.000000,2022-01-26 14:54:26,936.0,20.0,1206,146.0,377.0,105.0,438.0,8484,Create HTML profiling reports from pandas DataFrame objects.,85.0,36,True,2021-09-27 23:12:22.000,3.1.0,31.0,pandas-profiling,conda-forge/pandas-profiling,,,"['jupyter', 'pandas']",6773.0,6629.0,https://pypi.org/project/pandas-profiling,2021-09-27 23:12:22.000,144.0,926429.0,929246.0,https://anaconda.org/conda-forge/pandas-profiling,2021-09-28 13:50:05.966,185931.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +83,imbalanced-learn,scikit-learn-contrib/imbalanced-learn,sklearn-utils,,https://github.com/scikit-learn-contrib/imbalanced-learn,https://github.com/scikit-learn-contrib/imbalanced-learn,MIT,2014-08-16 05:08:26.000,2022-01-25 09:34:30.000000,2022-01-25 09:34:29,765.0,20.0,1161,149.0,405.0,62.0,449.0,5694,A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning.,62.0,36,True,2022-01-16 15:04:04.000,0.9.0,29.0,imbalanced-learn,conda-forge/imbalanced-learn,,,['sklearn'],9438.0,9195.0,https://pypi.org/project/imbalanced-learn,2022-01-11 18:09:58.000,243.0,2852103.0,2855608.0,https://anaconda.org/conda-forge/imbalanced-learn,2022-01-11 19:44:20.853,182268.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +84,Chainer,chainer/chainer,ml-frameworks,,https://github.com/chainer/chainer,https://github.com/chainer/chainer,MIT,2015-06-05 05:50:37.000,2022-01-21 17:09:00.786000,2022-01-05 04:28:43,30604.0,9.0,1378,293.0,6581.0,10.0,2028.0,5675,A flexible framework of neural networks for deep learning.,320.0,36,True,2022-01-05 05:33:36.000,7.8.1,111.0,chainer,conda-forge/chainer,,,,2884.0,2483.0,https://pypi.org/project/chainer,2022-01-05 05:33:36.000,401.0,21595.0,21876.0,https://anaconda.org/conda-forge/chainer,2022-01-21 17:09:00.786,6749.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +85,folium,python-visualization/folium,geospatial-data,,https://github.com/python-visualization/folium,https://github.com/python-visualization/folium,MIT,2013-05-09 04:21:35.000,2022-01-26 20:05:07.000000,2022-01-08 17:19:52,1517.0,42.0,2030,173.0,666.0,204.0,714.0,5612,Python Data. Leaflet.js Maps.,126.0,36,True,2021-11-19 21:01:43.000,0.12.1.post1,26.0,folium,conda-forge/folium,,,,14725.0,14094.0,https://pypi.org/project/folium,2021-11-19 21:08:10.000,631.0,721058.0,728774.0,https://anaconda.org/conda-forge/folium,2021-12-03 19:47:05.533,547877.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +86,UMAP,lmcinnes/umap,data-viz,,https://github.com/lmcinnes/umap,https://github.com/lmcinnes/umap,BSD-3-Clause,2017-07-02 01:11:17.000,2022-02-10 14:14:36.000000,2022-02-10 14:14:32,1572.0,73.0,611,121.0,205.0,316.0,285.0,5387,Uniform Manifold Approximation and Projection.,98.0,36,True,2021-10-29 16:33:56.000,0.5.2,36.0,umap-learn,conda-forge/umap-learn,,,,4810.0,4517.0,https://pypi.org/project/umap-learn,2021-10-29 16:33:56.000,293.0,1017728.0,1036968.0,https://anaconda.org/conda-forge/umap-learn,2022-01-15 02:36:15.851,885085.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +87,dbt,dbt-labs/dbt-core,data-pipelines,,https://github.com/dbt-labs/dbt-core,https://github.com/dbt-labs/dbt-core,Apache-2.0,2016-03-10 02:38:00.000,2022-02-10 14:13:21.000000,2022-02-07 19:14:22,5335.0,120.0,761,93.0,2085.0,295.0,2238.0,4168,dbt enables data analysts and engineers to transform their data using the same practices that software engineers use..,195.0,36,True,2022-01-03 19:01:38.000,1.0.1,173.0,dbt,conda-forge/dbt,,,,326.0,297.0,https://pypi.org/project/dbt,2021-12-06 20:32:12.000,29.0,678739.0,681781.0,https://anaconda.org/conda-forge/dbt,2021-12-09 22:07:39.668,191558.0,,,,,2.0,158.0,,,,,,,,,dbt,,,,,,,,,,, +88,TensorFlow Datasets,tensorflow/datasets,tensorflow-utils,,https://github.com/tensorflow/datasets,https://github.com/tensorflow/datasets,Apache-2.0,2018-09-10 21:27:22.000,2022-02-10 14:55:41.000000,2022-02-10 14:34:51,4640.0,266.0,1200,103.0,2841.0,525.0,613.0,3151,"TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...",241.0,36,True,2022-01-31 15:45:29.000,4.5.2,26.0,tensorflow-datasets,conda-forge/tensorflow-datasets,,,['tensorflow'],151.0,,https://pypi.org/project/tensorflow-datasets,2022-01-31 15:42:28.000,151.0,1306813.0,1307155.0,https://anaconda.org/conda-forge/tensorflow-datasets,2021-08-17 15:33:14.368,3085.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +89,GeoPandas,geopandas/geopandas,geospatial-data,,https://github.com/geopandas/geopandas,https://github.com/geopandas/geopandas,BSD-3-Clause,2013-06-27 17:03:47.000,2022-02-08 22:47:53.000000,2022-02-08 09:18:39,1536.0,40.0,667,108.0,1137.0,414.0,867.0,3000,Python tools for geographic data.,160.0,36,True,2021-10-16 06:59:55.000,0.10.2,40.0,geopandas,conda-forge/geopandas,,,['pandas'],13094.0,12004.0,https://pypi.org/project/geopandas,2021-10-16 06:59:50.000,1090.0,2322042.0,2340697.0,https://anaconda.org/conda-forge/geopandas,2021-12-01 18:19:27.710,1323015.0,,,,,1.0,1408.0,,,,,,,,,,,,,,,,,,,, +90,Thinc,explosion/thinc,ml-frameworks,,https://github.com/explosion/thinc,https://github.com/explosion/thinc,MIT,2014-10-16 16:34:59.000,2022-02-09 12:59:52.000000,2022-02-04 13:41:51,5018.0,15.0,227,84.0,477.0,20.0,97.0,2446,"A refreshing functional take on deep learning, compatible with your favorite libraries.",45.0,36,True,2021-11-05 12:27:02.000,8.0.13,200.0,thinc,conda-forge/thinc,,,,19477.0,18865.0,https://pypi.org/project/thinc,2021-12-17 10:16:52.000,612.0,3591042.0,3621273.0,https://anaconda.org/conda-forge/thinc,2021-12-08 16:36:35.030,1813862.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +91,Rasterio,rasterio/rasterio,geospatial-data,,https://github.com/rasterio/rasterio,https://github.com/rasterio/rasterio,BSD-3-Clause,2013-11-04 16:36:27.000,2022-02-10 02:48:29.000000,2022-02-04 23:23:57,3475.0,32.0,460,157.0,887.0,165.0,1360.0,1672,Rasterio reads and writes geospatial raster datasets.,118.0,36,True,2021-10-21 15:00:11.000,1.3a2,134.0,rasterio,conda-forge/rasterio,,,,5049.0,4312.0,https://pypi.org/project/rasterio,2022-02-04 21:57:43.000,737.0,792959.0,812567.0,https://anaconda.org/conda-forge/rasterio,2022-01-04 20:48:48.980,1391565.0,,,,,1.0,744.0,,,,,,,,,,,,,,,,,,,, +92,SageMaker SDK,aws/sagemaker-python-sdk,ml-experiments,,https://github.com/aws/sagemaker-python-sdk,https://github.com/aws/sagemaker-python-sdk,Apache-2.0,2017-11-14 01:03:33.000,2022-02-10 01:58:37.000000,2022-02-07 23:40:06,2349.0,86.0,738,101.0,1839.0,323.0,648.0,1563,A library for training and deploying machine learning models on Amazon SageMaker.,245.0,36,True,2022-02-08 05:16:05.000,2.75.1,402.0,sagemaker,conda-forge/sagemaker-python-sdk,,,"['mxnet', 'tensorflow']",1193.0,1149.0,https://pypi.org/project/sagemaker,2022-02-08 05:16:05.000,44.0,2663257.0,2671923.0,https://anaconda.org/conda-forge/sagemaker-python-sdk,2022-02-08 09:04:13.236,233990.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +93,jieba,fxsjy/jieba,chinese-nlp,,https://github.com/fxsjy/jieba,https://github.com/fxsjy/jieba,MIT,2012-09-29 07:52:01.000,2021-07-25 14:17:48.000000,2020-02-15 08:33:35,523.0,,6437,1294.0,162.0,630.0,208.0,27832,Chinese Words Segmentation Utilities.,48.0,35,False,2020-01-20 14:27:23.000,0.42.1,32.0,jieba,conda-forge/jieba,,,,13831.0,12324.0,https://pypi.org/project/jieba,2020-01-20 14:27:23.000,1507.0,510904.0,512638.0,https://anaconda.org/conda-forge/jieba,2021-05-30 19:33:02.597,100621.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +94,PyTorch Geometric,pyg-team/pytorch_geometric,graph,,https://github.com/pyg-team/pytorch_geometric,https://github.com/pyg-team/pytorch_geometric,MIT,2017-10-06 16:03:03.000,2022-02-10 11:25:07.000000,2022-02-10 10:15:06,5336.0,189.0,2376,241.0,651.0,915.0,1515.0,13762,Graph Neural Network Library for PyTorch.,242.0,35,True,2021-12-22 06:52:13.000,2.0.3,32.0,torch-geometric,conda-forge/pytorch_geometric,,,['pytorch'],33.0,,https://pypi.org/project/torch-geometric,2021-12-22 06:52:13.000,33.0,45068.0,45362.0,https://anaconda.org/conda-forge/pytorch_geometric,2022-01-19 15:40:54.095,5594.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +95,imgaug,aleju/imgaug,image,,https://github.com/aleju/imgaug,https://github.com/aleju/imgaug,MIT,2015-07-10 20:31:33.000,2021-12-31 00:20:29.231000,2020-06-01 14:58:26,2913.0,,2189,227.0,327.0,257.0,220.0,12249,Image augmentation for machine learning experiments.,36.0,35,False,2020-02-06 06:18:40.000,0.4.0,11.0,imgaug,conda-forge/imgaug,,,,9266.0,8911.0,https://pypi.org/project/imgaug,2020-02-05 20:54:22.000,355.0,288409.0,290312.0,https://anaconda.org/conda-forge/imgaug,2021-12-31 00:20:29.231,60916.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +96,ChatterBot,gunthercox/ChatterBot,nlp,,https://github.com/gunthercox/ChatterBot,https://github.com/gunthercox/ChatterBot,BSD-3-Clause,2014-09-28 14:49:00.000,2022-01-08 01:46:49.000000,2021-06-01 10:43:00,1848.0,,3910,550.0,693.0,300.0,1248.0,11984,"ChatterBot is a machine learning, conversational dialog engine for creating chat bots.",103.0,35,True,2020-08-22 18:42:43.000,1.0.8,86.0,chatterbot,,,,,4496.0,4146.0,https://pypi.org/project/chatterbot,2020-08-22 18:40:36.000,350.0,30774.0,30774.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +97,pyecharts,pyecharts/pyecharts,data-viz,,https://github.com/pyecharts/pyecharts,https://github.com/pyecharts/pyecharts,MIT,2017-06-22 02:50:25.000,2022-01-28 07:13:54.000000,2021-11-16 06:25:52,1522.0,7.0,2583,378.0,435.0,25.0,1516.0,11980,Python Echarts Plotting Library.,30.0,35,True,2021-11-16 06:27:35.000,1.9.1,67.0,pyecharts,,,https://github.com/pyecharts/pyecharts/blob/master/README.en.md,['jupyter'],2249.0,2038.0,https://pypi.org/project/pyecharts,2021-11-16 06:27:35.000,211.0,40766.0,40766.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +98,Albumentations,albumentations-team/albumentations,image,,https://github.com/albumentations-team/albumentations,https://github.com/albumentations-team/albumentations,MIT,2018-06-06 03:10:50.000,2022-02-10 09:27:43.000000,2021-12-24 19:26:29,698.0,15.0,1219,125.0,551.0,239.0,340.0,9645,Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation:..,100.0,35,True,2021-10-04 09:30:33.000,1.1.0,49.0,albumentations,conda-forge/albumentations,,,['pytorch'],6712.0,6533.0,https://pypi.org/project/albumentations,2021-10-04 09:30:33.000,179.0,286283.0,287238.0,https://anaconda.org/conda-forge/albumentations,2021-07-15 13:53:18.638,30568.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +99,MoviePy,Zulko/moviepy,image,,https://github.com/Zulko/moviepy,https://github.com/Zulko/moviepy,MIT,2013-08-12 09:39:28.000,2022-01-13 22:44:54.000000,2021-11-12 17:14:13,1072.0,,1183,244.0,602.0,346.0,865.0,8940,Video editing with Python.,145.0,35,True,2020-05-07 16:29:35.000,1.0.3,85.0,moviepy,conda-forge/moviepy,,,,14163.0,13440.0,https://pypi.org/project/moviepy,2021-12-15 14:41:26.454,723.0,2460943.0,2462782.0,https://anaconda.org/conda-forge/moviepy,2020-02-23 19:57:49.975,101197.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +100,dgl,dmlc/dgl,graph,,https://github.com/dmlc/dgl,https://github.com/dmlc/dgl,Apache-2.0,2018-04-20 14:49:09.000,2022-02-10 11:06:49.000000,2022-02-10 09:46:39,2106.0,106.0,1989,174.0,2393.0,343.0,1058.0,8902,"Python package built to ease deep learning on graph, on top of existing DL frameworks.",188.0,35,True,2021-11-08 04:09:08.000,0.7.2,438.0,dgl,,,,,39.0,,https://pypi.org/project/dgl,2021-05-27 13:25:52.000,39.0,63828.0,63828.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +101,glfw,glfw/glfw,image,,https://github.com/glfw/glfw,https://github.com/glfw/glfw,Zlib,2013-04-18 15:24:53.000,2022-02-09 21:32:09.000000,2022-02-09 21:13:14,4401.0,53.0,3230,377.0,536.0,467.0,1076.0,8625,"A multi-platform library for OpenGL, OpenGL ES, Vulkan, window and input.",178.0,35,False,2021-12-18 09:10:57.000,2.5.0,42.0,glfw,conda-forge/glfw,,,,145.0,1.0,https://pypi.org/project/glfw,2021-12-18 09:10:57.000,144.0,75653.0,108449.0,https://anaconda.org/conda-forge/glfw,2021-12-10 00:25:15.337,44544.0,,,,,2.0,2619435.0,,,,,,,,,,,,,,,,,,,, +102,ParlAI,facebookresearch/ParlAI,nlp,,https://github.com/facebookresearch/ParlAI,https://github.com/facebookresearch/ParlAI,MIT,2017-04-24 17:10:44.000,2022-02-10 07:35:22.000000,2022-02-08 18:45:50,4056.0,89.0,1704,292.0,3028.0,92.0,1149.0,8610,A framework for training and evaluating AI models on a variety of openly available dialogue datasets.,172.0,35,True,2021-10-12 21:51:23.000,1.5.1,21.0,parlai,,,,['pytorch'],62.0,59.0,https://pypi.org/project/parlai,2021-10-12 21:51:23.000,3.0,6787.0,6787.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +103,TextBlob,sloria/TextBlob,nlp,,https://github.com/sloria/TextBlob,https://github.com/sloria/TextBlob,MIT,2013-06-30 18:29:18.000,2021-12-15 14:34:36.304000,2021-10-22 03:17:05,562.0,,1057,272.0,155.0,101.0,154.0,8034,"Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation,..",35.0,35,True,2021-10-22 03:18:24.000,0.17.1,59.0,textblob,conda-forge/textblob,,,,18620.0,17252.0,https://pypi.org/project/textblob,2021-12-15 14:34:36.304,1368.0,1105549.0,1107806.0,https://anaconda.org/conda-forge/textblob,2019-02-24 23:32:55.233,149002.0,,,,,1.0,97.0,,,,,,,,,,,,,,,,,,,, +104,yfinance,ranaroussi/yfinance,financial-data,,https://github.com/ranaroussi/yfinance,https://github.com/ranaroussi/yfinance,Apache-2.0,2017-05-21 10:16:15.000,2022-02-09 06:25:40.000000,2022-01-30 12:13:53,397.0,40.0,1493,196.0,215.0,409.0,332.0,6614,Download market data from Yahoo! Finances API.,53.0,35,True,2022-01-30 12:14:45.000,0.1.70,35.0,yfinance,ranaroussi/yfinance,,,,9566.0,9447.0,https://pypi.org/project/yfinance,2022-01-30 12:14:45.000,119.0,294401.0,298576.0,https://anaconda.org/ranaroussi/yfinance,2021-07-10 20:29:09.532,29225.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +105,Great Expectations,great-expectations/great_expectations,data-pipelines,,https://github.com/great-expectations/great_expectations,https://github.com/great-expectations/great_expectations,Apache-2.0,2017-09-11 00:18:46.000,2022-02-10 14:35:14.000000,2022-02-10 08:27:57,8194.0,270.0,826,65.0,3007.0,193.0,1025.0,6062,Always know what to expect from your data.,262.0,35,True,2022-02-03 22:07:25.000,0.14.5,145.0,great_expectations,conda-forge/great-expectations,,,,27.0,,https://pypi.org/project/great_expectations,2022-02-03 21:55:15.000,27.0,2859893.0,2867442.0,https://anaconda.org/conda-forge/great-expectations,2022-02-04 01:14:47.391,354827.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +106,featuretools,alteryx/featuretools,hyperopt,,https://github.com/alteryx/featuretools,https://github.com/alteryx/featuretools,BSD-3-Clause,2017-09-08 22:15:17.000,2022-02-10 14:32:20.000000,2022-02-09 18:22:25,910.0,52.0,783,157.0,1155.0,166.0,563.0,5977,An open source python library for automated feature engineering.,59.0,35,True,2022-01-28 22:04:06.000,1.4.1,98.0,featuretools,conda-forge/featuretools,,,,983.0,921.0,https://pypi.org/project/featuretools,2022-01-28 22:05:10.000,62.0,591884.0,593937.0,https://anaconda.org/conda-forge/featuretools,2022-02-01 15:31:58.778,78042.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +107,Kornia,kornia/kornia,image,,https://github.com/kornia/kornia,https://github.com/kornia/kornia,Apache-2.0,2018-08-22 10:31:37.000,2022-02-10 10:01:49.000000,2022-02-09 19:18:10,1958.0,61.0,574,111.0,990.0,138.0,399.0,5854,Open Source Differentiable Computer Vision Library.,150.0,35,True,2022-01-31 15:10:06.000,0.6.3,27.0,kornia,conda-forge/kornia,,,['pytorch'],1011.0,967.0,https://pypi.org/project/kornia,2022-01-31 15:10:06.000,44.0,293778.0,294309.0,https://anaconda.org/conda-forge/kornia,2022-02-01 17:05:33.482,11080.0,,,,,2.0,190.0,,,,,,,,,,,,,,,,,,,, +108,espnet,espnet/espnet,audio,,https://github.com/espnet/espnet,https://github.com/espnet/espnet,Apache-2.0,2017-12-13 00:45:11.000,2022-02-10 14:39:22.000000,2022-02-10 00:55:56,13858.0,593.0,1459,178.0,2358.0,313.0,1371.0,4676,End-to-End Speech Processing Toolkit.,232.0,35,True,2022-02-08 12:39:53.000,0.10.6,42.0,espnet,,,,,33.0,32.0,https://pypi.org/project/espnet,2022-02-08 12:39:53.000,1.0,5314.0,5315.0,,,,,,,,1.0,74.0,,,,,,,,,,,,,,,,,,,, +109,MLxtend,rasbt/mlxtend,sklearn-utils,,https://github.com/rasbt/mlxtend,https://github.com/rasbt/mlxtend,BSD-3-Clause,2014-08-14 01:56:16.000,2022-02-07 15:07:05.000000,2022-01-19 17:18:34,1263.0,28.0,732,121.0,452.0,99.0,299.0,3791,A library of extension and helper modules for Pythons data analysis and machine learning libraries.,86.0,35,True,2021-09-03 00:02:55.000,0.19.0,47.0,mlxtend,conda-forge/mlxtend,,,['sklearn'],5290.0,5145.0,https://pypi.org/project/mlxtend,2021-09-03 00:02:55.000,145.0,1981140.0,1984656.0,https://anaconda.org/conda-forge/mlxtend,2021-09-03 13:27:33.719,193427.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +110,wandb client,wandb/client,ml-experiments,,https://github.com/wandb/client,https://github.com/wandb/client,MIT,2017-03-24 05:46:23.000,2022-02-10 07:48:29.000000,2022-02-09 20:35:40,4392.0,113.0,292,34.0,1705.0,358.0,1299.0,3695,A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.,103.0,35,True,2022-02-01 17:14:57.000,0.12.10,217.0,wandb,conda-forge/wandb,,,,205.0,,https://pypi.org/project/wandb,2022-02-01 17:07:37.000,205.0,654148.0,656414.0,https://anaconda.org/conda-forge/wandb,2022-02-02 01:38:21.661,43063.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +111,PyTables,PyTables/PyTables,data-containers,,https://github.com/PyTables/PyTables,https://github.com/PyTables/PyTables,BSD-3-Clause,2011-06-03 19:44:46.000,2022-01-28 10:39:45.000000,2022-01-28 10:39:44,4066.0,102.0,218,59.0,305.0,178.0,497.0,1100,A Python package to manage extremely large amounts of data.,104.0,35,True,2021-12-28 21:59:09.000,3.7.0,35.0,tables,conda-forge/pytables,,,,2324.0,,https://pypi.org/project/tables,2021-12-28 21:42:08.000,2324.0,798498.0,855406.0,https://anaconda.org/conda-forge/pytables,2022-01-25 19:32:03.999,3755848.0,,,,,2.0,165.0,,,,,,,,,,,,,,,,,,,, +112,Nilearn,nilearn/nilearn,medical-data,,https://github.com/nilearn/nilearn,https://github.com/nilearn/nilearn,BSD-3-Clause,2011-01-09 19:02:23.000,2022-02-10 13:52:39.000000,2022-02-07 08:27:11,9560.0,60.0,438,75.0,1629.0,270.0,1294.0,807,Machine learning for NeuroImaging in Python.,180.0,35,True,2022-01-28 17:36:00.000,0.9.0,39.0,nilearn,conda-forge/nilearn,,,['sklearn'],1610.0,1377.0,https://pypi.org/project/nilearn,2022-01-28 17:34:00.000,233.0,19054.0,21039.0,https://anaconda.org/conda-forge/nilearn,2022-01-31 17:25:07.206,136861.0,,,,,1.0,19.0,,,,,,,,,,,,,,,,,,,, +113,pyproj,pyproj4/pyproj,geospatial-data,,https://github.com/pyproj4/pyproj,https://github.com/pyproj4/pyproj,MIT,2014-12-29 21:38:25.000,2022-01-28 03:33:23.000000,2022-01-28 03:31:10,1289.0,18.0,169,29.0,505.0,9.0,456.0,714,Python interface to PROJ (cartographic projections and coordinate transformations library).,46.0,35,True,2021-11-18 01:52:35.000,3.3.0,44.0,pyproj,conda-forge/pyproj,,,,14457.0,12832.0,https://pypi.org/project/pyproj,2021-11-18 01:52:35.000,1625.0,4198893.0,4238312.0,https://anaconda.org/conda-forge/pyproj,2022-01-03 12:33:24.114,2917064.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +114,fastText,facebookresearch/fastText,nlp,,https://github.com/facebookresearch/fastText,https://github.com/facebookresearch/fastText,MIT,2016-07-16 13:38:42.000,2022-01-31 08:22:59.000000,2020-07-18 00:20:40,379.0,,4392,866.0,234.0,470.0,599.0,23356,Library for fast text representation and classification.,58.0,34,False,2020-04-28 09:54:50.000,0.9.2,35.0,fasttext,conda-forge/fasttext,,,,2718.0,2557.0,https://pypi.org/project/fasttext,2020-04-28 09:54:50.000,161.0,449792.0,450295.0,https://anaconda.org/conda-forge/fasttext,2021-11-08 12:46:40.327,26203.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +115,detectron2,facebookresearch/detectron2,image,,https://github.com/facebookresearch/detectron2,https://github.com/facebookresearch/detectron2,Apache-2.0,2019-09-05 21:30:20.000,2022-02-08 16:13:30.000000,2022-02-07 21:41:16,1335.0,39.0,5097,345.0,439.0,143.0,2698.0,19798,"Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.",198.0,34,True,2021-11-15 22:08:26.000,0.6,10.0,detectron2,conda-forge/detectron2,,,['pytorch'],496.0,494.0,https://pypi.org/project/detectron2,2020-02-06 00:35:57.000,2.0,,1847.0,https://anaconda.org/conda-forge/detectron2,2022-01-11 20:10:26.500,38794.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +116,Faiss,facebookresearch/faiss,nn-search,,https://github.com/facebookresearch/faiss,https://github.com/facebookresearch/faiss,MIT,2017-02-07 16:07:05.000,2022-02-10 14:10:34.000000,2022-02-08 03:36:21,592.0,20.0,2503,441.0,458.0,183.0,1540.0,16158,A library for efficient similarity search and clustering of dense vectors.,92.0,34,True,2022-01-25 10:52:10.000,2.0.0,59.0,pymilvus,conda-forge/faiss,,,,566.0,551.0,https://pypi.org/project/pymilvus,2022-01-25 10:52:10.000,15.0,32188.0,43662.0,https://anaconda.org/conda-forge/faiss,2022-02-09 02:10:28.516,240968.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +117,InsightFace,deepinsight/insightface,image,,https://github.com/deepinsight/insightface,https://github.com/deepinsight/insightface,MIT,2017-09-01 00:36:51.000,2022-02-09 09:43:20.000000,2022-02-09 09:43:20,1974.0,104.0,3622,450.0,105.0,998.0,824.0,11168,State-of-the-art 2D and 3D Face Analysis Project.,37.0,34,True,2022-01-29 17:29:00.000,0.6.2,24.0,insightface,,,,['mxnet'],135.0,130.0,https://pypi.org/project/insightface,2022-01-29 17:29:00.000,5.0,22456.0,22456.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +118,AutoKeras,keras-team/autokeras,hyperopt,,https://github.com/keras-team/autokeras,https://github.com/keras-team/autokeras,Apache-2.0,2017-11-19 23:18:20.000,2022-02-08 23:29:21.000000,2022-02-08 23:29:21,1284.0,13.0,1347,311.0,792.0,70.0,728.0,8335,AutoML library for deep learning.,131.0,34,True,2022-02-03 00:19:31.000,1.0.17,54.0,autokeras,,,,['tensorflow'],283.0,273.0,https://pypi.org/project/autokeras,2022-02-03 00:19:31.000,10.0,39559.0,39610.0,,,,,,,,1.0,2612.0,,,,,,,,,,,,,,,,,,,, +119,PySyft,OpenMined/PySyft,privacy-ml,,https://github.com/OpenMined/PySyft,https://github.com/OpenMined/PySyft,Apache-2.0,2017-07-18 20:41:16.000,2022-02-10 13:22:44.000000,2022-02-09 05:41:27,13009.0,506.0,1747,210.0,3220.0,301.0,2760.0,7922,A library for answering questions using data you cannot see.,427.0,34,True,2021-12-01 19:46:09.000,0.6.0,61.0,syft,,,,['pytorch'],5.0,,https://pypi.org/project/syft,2021-12-01 19:46:09.000,5.0,3625.0,3625.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +120,Vowpal Wabbit,VowpalWabbit/vowpal_wabbit,ml-frameworks,,https://github.com/VowpalWabbit/vowpal_wabbit,https://github.com/VowpalWabbit/vowpal_wabbit,BSD-3-Clause,2009-07-31 19:36:58.000,2022-02-10 04:16:54.000000,2022-02-10 01:09:56,9685.0,188.0,1783,366.0,2562.0,135.0,1015.0,7855,Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as..,313.0,34,True,2022-02-01 23:59:19.000,9.0.1,20.0,vowpalwabbit,conda-forge/vowpalwabbit,,,,29.0,,https://pypi.org/project/vowpalwabbit,2022-02-01 23:59:19.000,29.0,53323.0,55091.0,https://anaconda.org/conda-forge/vowpalwabbit,2022-02-02 05:57:37.533,54828.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +121,tensorboardX,lanpa/tensorboardX,ml-experiments,,https://github.com/lanpa/tensorboardX,https://github.com/lanpa/tensorboardX,MIT,2017-06-13 13:54:19.000,2022-02-06 09:48:15.000000,2022-02-06 09:47:28,482.0,8.0,841,85.0,229.0,74.0,365.0,7227,"tensorboard for pytorch (and chainer, mxnet, numpy, ...).",70.0,34,True,2021-11-21 09:12:04.000,2.4.1,16.0,tensorboardX,conda-forge/tensorboardx,,,,17769.0,16907.0,https://pypi.org/project/tensorboardX,2021-11-21 09:12:04.000,862.0,659410.0,672454.0,https://anaconda.org/conda-forge/tensorboardx,2021-08-10 02:00:22.589,638882.0,,,,,2.0,343.0,,,,,,,,,,,,,,,,,,,, +122,sentence-transformers,UKPLab/sentence-transformers,nlp,,https://github.com/UKPLab/sentence-transformers,https://github.com/UKPLab/sentence-transformers,Apache-2.0,2019-07-24 10:53:51.000,2022-02-10 13:44:40.000000,2022-02-10 13:44:02,1052.0,36.0,1360,105.0,129.0,642.0,642.0,7027,Multilingual Sentence & Image Embeddings with BERT.,73.0,34,True,2022-02-10 13:12:24.000,2.2.0,40.0,sentence-transformers,conda-forge/sentence-transformers,,,['pytorch'],2440.0,2360.0,https://pypi.org/project/sentence-transformers,2021-10-01 08:44:06.000,80.0,778599.0,779415.0,https://anaconda.org/conda-forge/sentence-transformers,2021-11-30 09:19:23.391,13883.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +123,Modin,modin-project/modin,data-containers,,https://github.com/modin-project/modin,https://github.com/modin-project/modin,Apache-2.0,2018-06-21 21:35:05.000,2022-02-10 14:12:08.000000,2022-02-09 16:11:49,1716.0,141.0,479,106.0,1741.0,827.0,1659.0,6770,Modin: Speed up your Pandas workflows by changing a single line of code.,88.0,34,True,2022-02-04 18:13:39.000,0.13.1,49.0,modin,conda-forge/modin-core,,,['pandas'],580.0,559.0,https://pypi.org/project/modin,2022-02-04 18:13:39.000,21.0,193974.0,200924.0,https://anaconda.org/conda-forge/modin-core,2022-02-06 13:05:58.330,16772.0,,,,,2.0,195844.0,,,,,,,,,,,,,,,,,,,, +124,Hyperopt,hyperopt/hyperopt,hyperopt,,https://github.com/hyperopt/hyperopt,https://github.com/hyperopt/hyperopt,BSD-3-Clause,2011-09-06 22:24:59.000,2022-02-03 19:34:56.000000,2021-11-29 10:21:36,1194.0,8.0,924,128.0,252.0,360.0,231.0,6065,Distributed Asynchronous Hyperparameter Optimization in Python.,93.0,34,True,2021-11-17 10:05:44.000,0.2.7,13.0,hyperopt,conda-forge/hyperopt,,,,6107.0,5707.0,https://pypi.org/project/hyperopt,2021-11-17 10:05:44.000,400.0,1984889.0,1993291.0,https://anaconda.org/conda-forge/hyperopt,2020-10-14 07:57:14.292,344520.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +125,PyOD,yzhao062/pyod,others,,https://github.com/yzhao062/pyod,https://github.com/yzhao062/pyod,BSD-2-Clause,2017-10-03 20:29:04.000,2022-01-04 05:14:46.022000,2022-01-04 02:56:06,1414.0,10.0,1016,150.0,144.0,118.0,117.0,5240,(JMLR 19) A Python Toolbox for Scalable Outlier Detection (Anomaly Detection).,33.0,34,True,2022-01-04 03:05:12.000,0.9.7,75.0,pyod,conda-forge/pyod,,,,1134.0,1106.0,https://pypi.org/project/pyod,2022-01-04 03:03:42.000,28.0,470808.0,471506.0,https://anaconda.org/conda-forge/pyod,2022-01-04 05:14:46.022,16055.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +126,Gradio,gradio-app/gradio,others,,https://github.com/gradio-app/gradio,https://github.com/gradio-app/gradio,Apache-2.0,2018-12-19 08:24:04.000,2022-02-10 13:52:23.000000,2022-02-10 08:26:05,3184.0,520.0,318,67.0,165.0,56.0,272.0,5134,"Wrap UIs around any model, share with anyone.",45.0,34,True,2022-01-21 18:57:18.000,2.7.5,196.0,gradio,,,,,541.0,525.0,https://pypi.org/project/gradio,2022-02-08 22:51:24.000,16.0,80789.0,80789.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +127,librosa,librosa/librosa,audio,,https://github.com/librosa/librosa,https://github.com/librosa/librosa,ISC,2012-10-20 14:21:01.000,2022-02-10 13:56:33.000000,2022-02-07 13:13:22,3133.0,20.0,788,135.0,505.0,33.0,907.0,4994,Python library for audio and music analysis.,93.0,34,True,2022-02-07 13:16:38.000,0.9.0,33.0,librosa,conda-forge/librosa,,,,1169.0,,https://pypi.org/project/librosa,2022-02-07 13:16:38.000,1169.0,540899.0,547286.0,https://anaconda.org/conda-forge/librosa,2022-02-07 14:30:59.618,427995.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +128,DeepChem,deepchem/deepchem,others,,https://github.com/deepchem/deepchem,https://github.com/deepchem/deepchem,MIT,2015-09-24 23:20:28.000,2022-02-10 14:04:02.000000,2022-02-08 16:35:12,7403.0,105.0,1265,152.0,1467.0,448.0,994.0,3417,"Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology.",180.0,34,True,2022-01-18 21:35:03.000,2.6.1,378.0,deepchem,conda-forge/deepchem,,,['tensorflow'],74.0,70.0,https://pypi.org/project/deepchem,2022-02-08 16:50:02.000,4.0,9248.0,9586.0,https://anaconda.org/conda-forge/deepchem,2022-01-19 16:40:21.191,8134.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +129,tensorflow-hub,tensorflow/hub,tensorflow-utils,,https://github.com/tensorflow/hub,https://github.com/tensorflow/hub,Apache-2.0,2018-03-12 07:55:42.000,2022-02-06 14:51:17.000000,2022-02-06 14:51:15,1024.0,22.0,1624,138.0,199.0,14.0,622.0,3037,A library for transfer learning by reusing parts of TensorFlow models.,83.0,34,True,2021-04-14 13:17:26.000,0.12.0,15.0,tensorflow-hub,conda-forge/tensorflow-hub,,,['tensorflow'],10507.0,10223.0,https://pypi.org/project/tensorflow-hub,2021-04-14 12:54:13.000,284.0,3176351.0,3177715.0,https://anaconda.org/conda-forge/tensorflow-hub,2021-04-18 18:01:14.779,60021.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +130,AzureML SDK,Azure/MachineLearningNotebooks,ml-experiments,,https://github.com/Azure/MachineLearningNotebooks,https://github.com/Azure/MachineLearningNotebooks,MIT,2018-08-17 17:29:14.000,2022-02-02 17:28:49.000000,2022-02-02 17:28:49,1167.0,5.0,1996,2083.0,449.0,206.0,1020.0,2848,Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft.,59.0,34,True,2021-12-13 16:21:23.000,1.37.0,85.0,azureml-sdk,,,,,45.0,,https://pypi.org/project/azureml-sdk,2022-01-24 18:30:50.000,45.0,1521847.0,1521857.0,,,,,,,,2.0,427.0,,,,,,,,,,,,,,,,,,,, +131,PyQtGraph,pyqtgraph/pyqtgraph,data-viz,,https://github.com/pyqtgraph/pyqtgraph,https://github.com/pyqtgraph/pyqtgraph,MIT,2013-09-12 07:18:21.000,2022-02-09 20:47:54.000000,2022-02-09 20:47:54,3145.0,95.0,896,147.0,1166.0,309.0,678.0,2710,Fast data visualization and GUI tools for scientific / engineering applications.,216.0,34,True,2021-10-11 03:35:04.000,0.12.3,16.0,pyqtgraph,conda-forge/pyqtgraph,,,,761.0,,https://pypi.org/project/pyqtgraph,2021-10-11 03:35:04.000,761.0,76968.0,80537.0,https://anaconda.org/conda-forge/pyqtgraph,2021-10-11 16:15:08.513,217743.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +132,spark-nlp,JohnSnowLabs/spark-nlp,nlp,,https://github.com/JohnSnowLabs/spark-nlp,https://github.com/JohnSnowLabs/spark-nlp,Apache-2.0,2017-09-24 19:36:44.000,2022-02-10 14:39:37.000000,2022-02-10 14:33:16,13982.0,1136.0,526,88.0,6200.0,87.0,535.0,2610,State of the Art Natural Language Processing.,112.0,34,True,2022-02-08 18:05:14.000,3.4.1,100.0,spark-nlp,,,,['spark'],9.0,,https://pypi.org/project/spark-nlp,2022-02-08 16:02:17.000,9.0,1438925.0,1438925.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +133,opencv-python,opencv/opencv-python,image,,https://github.com/opencv/opencv-python,https://github.com/opencv/opencv-python,MIT,2016-04-08 13:36:40.000,2022-01-25 14:25:16.000000,2022-01-25 14:25:16,823.0,14.0,489,78.0,107.0,32.0,480.0,2522,"Automated CI toolchain to produce precompiled opencv-python, opencv-python-headless, opencv-contrib-python and opencv-..",36.0,34,True,2021-12-28 06:05:52.000,62,61.0,opencv-python,,,,,8727.0,,https://pypi.org/project/opencv-python,2021-12-29 05:59:26.000,8727.0,4865497.0,4865497.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +134,ipyparallel,ipython/ipyparallel,distributed-ml,,https://github.com/ipython/ipyparallel,https://github.com/ipython/ipyparallel,BSD-3-Clause,2015-04-09 07:43:55.000,2022-02-07 17:40:52.548000,2022-02-07 14:18:40,2555.0,70.0,863,115.0,349.0,49.0,267.0,2154,IPython Parallel: Interactive Parallel Computing in Python.,105.0,34,True,2021-12-22 08:42:58.000,8.1.0,37.0,ipyparallel,conda-forge/ipyparallel,,,['jupyter'],2086.0,1803.0,https://pypi.org/project/ipyparallel,2022-02-07 14:22:40.000,283.0,53664.0,61622.0,https://anaconda.org/conda-forge/ipyparallel,2022-02-07 17:40:52.548,557067.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +135,HoloViews,holoviz/holoviews,data-viz,,https://github.com/holoviz/holoviews,https://github.com/holoviz/holoviews,BSD-3-Clause,2014-05-07 16:59:22.000,2022-02-10 13:43:01.000000,2022-02-08 12:59:37,10279.0,36.0,347,61.0,2462.0,827.0,1919.0,2108,"With Holoviews, your data visualizes itself.",116.0,34,True,2021-12-16 15:54:33.000,1.14.7,76.0,holoviews,conda-forge/holoviews,,,['jupyter'],199.0,,https://pypi.org/project/holoviews,2022-01-21 13:03:26.000,199.0,231316.0,242307.0,https://anaconda.org/conda-forge/holoviews,2022-01-13 13:07:17.601,634819.0,,,,,2.0,,,@pyviz/jupyterlab_pyviz,https://www.npmjs.com/package/@pyviz/jupyterlab_pyviz,2020-05-24 13:49:54.205,,1791.0,,,,,,,,,,,,,, +136,snakemake,snakemake/snakemake,ml-experiments,,https://github.com/snakemake/snakemake,https://github.com/snakemake/snakemake,MIT,2015-10-17 15:43:54.867,2022-02-10 12:34:53.000000,2022-02-09 22:29:28,4300.0,73.0,293,18.0,560.0,529.0,304.0,1232,"This is the development home of the workflow management system Snakemake. For general information, see.",240.0,34,True,2022-02-09 22:30:28.000,6.15.5,204.0,snakemake,bioconda/snakemake,,,,1219.0,1015.0,https://pypi.org/project/snakemake,2022-02-09 22:30:51.000,204.0,70193.0,75197.0,https://anaconda.org/bioconda/snakemake,2022-02-10 04:45:59.115,380367.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +137,Fiona,Toblerity/Fiona,geospatial-data,,https://github.com/Toblerity/Fiona,https://github.com/Toblerity/Fiona,BSD-3-Clause,2011-12-31 19:47:00.000,2022-02-08 04:44:10.347000,2022-02-07 21:39:33,1292.0,23.0,178,48.0,410.0,77.0,584.0,883,Fiona reads and writes geographic data files.,66.0,34,True,2022-02-07 17:34:18.000,1.8.21,99.0,fiona,conda-forge/fiona,,,,8511.0,7738.0,https://pypi.org/project/fiona,2022-02-07 17:17:02.000,773.0,2620327.0,2655750.0,https://anaconda.org/conda-forge/fiona,2022-02-08 04:44:10.347,2515047.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +138,Hail,hail-is/hail,medical-data,,https://github.com/hail-is/hail,https://github.com/hail-is/hail,MIT,2015-10-27 20:55:42.000,2022-02-10 14:16:24.000000,2022-02-09 23:03:08,9467.0,250.0,203,58.0,9347.0,55.0,1968.0,777,Scalable genomic data analysis.,77.0,34,True,2022-02-01 03:50:02.000,0.2.83,103.0,hail,,,,['spark'],53.0,47.0,https://pypi.org/project/hail,2022-02-01 03:50:33.000,6.0,176432.0,176432.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +139,Face Recognition,ageitgey/face_recognition,image,,https://github.com/ageitgey/face_recognition,https://github.com/ageitgey/face_recognition,MIT,2017-03-03 21:52:39.000,2021-12-04 17:06:24.000000,2021-06-14 10:10:40,219.0,,11744,1585.0,191.0,658.0,554.0,43072,The worlds simplest facial recognition api for Python and the command line.,47.0,33,True,2018-08-21 18:34:21.000,1.2.3,21.0,face_recognition,conda-forge/face_recognition,,,['pytorch'],207.0,,https://pypi.org/project/face_recognition,2018-08-21 18:34:21.000,207.0,44074.0,44326.0,https://anaconda.org/conda-forge/face_recognition,2021-04-30 19:06:15.265,4167.0,,,,,2.0,453.0,,,,,,,,,,,,,,,,,,,, +140,DeepSpeech,mozilla/DeepSpeech,audio,,https://github.com/mozilla/DeepSpeech,https://github.com/mozilla/DeepSpeech,MPL-2.0,2016-06-02 15:04:53.000,2022-01-04 18:22:16.000000,2021-11-17 17:52:52,3466.0,2.0,3312,650.0,1656.0,119.0,1936.0,19004,"DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices..",162.0,33,True,2020-12-10 17:22:09.000,0.9.3,100.0,deepspeech,conda-forge/deepspeech,,,['tensorflow'],700.0,665.0,https://pypi.org/project/deepspeech,2020-12-19 10:05:12.000,35.0,8363.0,27766.0,https://anaconda.org/conda-forge/deepspeech,2021-07-29 19:26:04.079,336.0,,,,,1.0,793582.0,,,,,,,,11.0,,,,,,,,,,,, +141,zipline,quantopian/zipline,financial-data,,https://github.com/quantopian/zipline,https://github.com/quantopian/zipline,Apache-2.0,2012-10-19 15:50:29.000,2022-01-20 12:10:43.000000,2020-10-14 16:36:49,6226.0,,4203,1013.0,1864.0,346.0,651.0,14888,"Zipline, a Pythonic Algorithmic Trading Library.",153.0,33,False,2020-10-05 15:46:20.429,1.4.1,30.0,zipline,conda-forge/zipline,,,,909.0,824.0,https://pypi.org/project/zipline,2020-10-05 15:46:20.429,85.0,3298.0,3614.0,https://anaconda.org/conda-forge/zipline,2020-10-05 18:38:58.729,5374.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +142,EasyOCR,JaidedAI/EasyOCR,ocr,,https://github.com/JaidedAI/EasyOCR,https://github.com/JaidedAI/EasyOCR,Apache-2.0,2020-03-14 11:46:39.000,2022-01-20 03:07:12.000000,2022-01-14 14:06:14,476.0,2.0,1792,271.0,155.0,164.0,335.0,13748,"Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic,..",91.0,33,True,2021-09-11 09:38:37.000,1.4.1,25.0,easyocr,,,,,895.0,874.0,https://pypi.org/project/easyocr,2021-09-11 09:38:37.000,21.0,118304.0,174126.0,,,,,,,,1.0,1116459.0,,,,,,,,,,,,,,,,,,,, +143,tensor2tensor,tensorflow/tensor2tensor,tensorflow-utils,,https://github.com/tensorflow/tensor2tensor,https://github.com/tensorflow/tensor2tensor,Apache-2.0,2017-06-15 16:57:39.000,2022-01-12 18:24:42.000000,2022-01-12 18:24:41,4362.0,2.0,2948,450.0,664.0,563.0,669.0,11986,Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.,236.0,33,True,2020-06-17 16:15:36.000,1.15.7,79.0,tensor2tensor,,,,['tensorflow'],1208.0,1115.0,https://pypi.org/project/tensor2tensor,2020-06-17 16:15:36.000,93.0,49714.0,49714.0,,,,,,,,2.0,,,,,,,,,-2.0,,,,,,,,,,,, +144,Lime,marcotcr/lime,interpretability,,https://github.com/marcotcr/lime,https://github.com/marcotcr/lime,BSD-2-Clause,2016-03-15 22:18:10.000,2022-01-14 13:42:13.000000,2021-07-29 23:17:25,531.0,,1514,274.0,105.0,25.0,525.0,9559,Lime: Explaining the predictions of any machine learning classifier.,61.0,33,True,2020-04-03 22:05:03.000,0.2.0.0,38.0,lime,conda-forge/lime,,,,2040.0,1933.0,https://pypi.org/project/lime,2020-06-26 21:38:15.000,107.0,741685.0,743171.0,https://anaconda.org/conda-forge/lime,2020-06-28 01:02:41.538,92139.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +145,wordcloud,amueller/word_cloud,data-viz,,https://github.com/amueller/word_cloud,https://github.com/amueller/word_cloud,MIT,2012-11-04 22:57:59.000,2022-01-10 11:00:09.000000,2021-11-13 00:48:18,549.0,4.0,2144,215.0,207.0,110.0,363.0,8587,A little word cloud generator in Python.,64.0,33,True,2020-11-11 21:41:02.000,1.8.1,16.0,wordcloud,conda-forge/wordcloud,,,,710.0,,https://pypi.org/project/wordcloud,2020-11-11 21:41:02.000,710.0,599085.0,602961.0,https://anaconda.org/conda-forge/wordcloud,2021-11-15 20:34:05.364,255867.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +146,Pyro,pyro-ppl/pyro,probabilistics,,https://github.com/pyro-ppl/pyro,https://github.com/pyro-ppl/pyro,Apache-2.0,2017-06-16 05:03:47.000,2022-02-09 21:44:48.000000,2022-01-27 19:41:08,2300.0,21.0,881,203.0,2107.0,184.0,741.0,7303,Deep universal probabilistic programming with Python and PyTorch.,117.0,33,True,2021-12-14 16:17:56.000,1.8.0,28.0,pyro-ppl,conda-forge/pyro-ppl,,,['pytorch'],668.0,619.0,https://pypi.org/project/pyro-ppl,2021-12-14 16:19:58.000,49.0,74299.0,74673.0,https://anaconda.org/conda-forge/pyro-ppl,2021-12-14 19:13:11.247,4114.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +147,Kedro,kedro-org/kedro,data-pipelines,,https://github.com/kedro-org/kedro,https://github.com/kedro-org/kedro,Apache-2.0,2019-04-18 10:29:56.000,2022-02-10 14:33:02.000000,2022-02-10 14:15:12,1430.0,62.0,600,99.0,538.0,42.0,562.0,6457,"A Python framework for creating reproducible, maintainable and modular data science code.",141.0,33,True,2021-12-09 16:01:14.000,0.17.6,30.0,kedro,,,,,763.0,728.0,https://pypi.org/project/kedro,2021-12-09 16:01:14.000,35.0,295864.0,295864.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +148,auto-sklearn,automl/auto-sklearn,hyperopt,,https://github.com/automl/auto-sklearn,https://github.com/automl/auto-sklearn,BSD-3-Clause,2015-07-02 15:38:10.000,2022-02-09 18:54:09.000000,2022-01-25 22:28:26,2616.0,34.0,1118,214.0,568.0,116.0,737.0,6017,Automated Machine Learning with scikit-learn.,79.0,33,True,2022-01-25 22:31:56.000,0.14.5,39.0,auto-sklearn,conda-forge/auto-sklearn,,,['sklearn'],285.0,255.0,https://pypi.org/project/auto-sklearn,2022-01-25 22:30:32.000,30.0,27909.0,28199.0,https://anaconda.org/conda-forge/auto-sklearn,2022-01-28 12:00:06.183,2900.0,,,,,2.0,14.0,,,,,,,,,,,,,,,,,,,, +149,Datasette,simonw/datasette,others,,https://github.com/simonw/datasette,https://github.com/simonw/datasette,Apache-2.0,2017-10-23 00:39:03.000,2022-02-09 17:48:10.000000,2022-02-09 17:47:54,1919.0,134.0,394,94.0,305.0,352.0,926.0,5773,An open source multi-tool for exploring and publishing data.,61.0,33,True,2022-02-07 23:57:15.000,0.60.2,114.0,datasette,conda-forge/datasette,,,,727.0,584.0,https://pypi.org/project/datasette,2022-02-07 23:57:15.000,143.0,260279.0,260544.0,https://anaconda.org/conda-forge/datasette,2022-02-08 02:44:23.524,2656.0,,,,,2.0,34.0,,,,,,,,,datasette,,,,,,,,,,, +150,sentencepiece,google/sentencepiece,nlp,,https://github.com/google/sentencepiece,https://github.com/google/sentencepiece,Apache-2.0,2017-03-07 10:03:48.000,2022-02-07 17:55:09.466000,2021-07-02 15:44:09,697.0,,786,111.0,228.0,58.0,446.0,5654,Unsupervised text tokenizer for Neural Network-based text generation.,57.0,33,True,2021-06-18 09:34:31.000,0.1.96,31.0,sentencepiece,conda-forge/sentencepiece,,,,12888.0,12537.0,https://pypi.org/project/sentencepiece,2021-06-18 09:34:31.000,351.0,4305967.0,4314386.0,https://anaconda.org/conda-forge/sentencepiece,2022-02-07 17:55:09.466,151033.0,,,,,2.0,19773.0,,,,,,,,,,,,,,,,,,,, +151,OpenNMT,OpenNMT/OpenNMT-py,nlp,,https://github.com/OpenNMT/OpenNMT-py,https://github.com/OpenNMT/OpenNMT-py,MIT,2017-02-22 19:01:50.000,2022-02-09 16:15:17.000000,2022-02-09 16:15:17,2589.0,4.0,2034,165.0,856.0,120.0,1208.0,5447,Open Source Neural Machine Translation in PyTorch.,173.0,33,True,2021-09-14 08:49:23.000,2.2.0,32.0,OpenNMT-py,,,,['pytorch'],133.0,125.0,https://pypi.org/project/OpenNMT-py,2021-09-14 08:49:23.000,8.0,20404.0,20404.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +152,Tokenizers,huggingface/tokenizers,nlp,,https://github.com/huggingface/tokenizers,https://github.com/huggingface/tokenizers,Apache-2.0,2019-11-01 17:52:20.000,2022-02-03 23:46:53.000000,2022-01-28 16:51:51,1528.0,35.0,429,95.0,338.0,157.0,407.0,5227,Fast State-of-the-Art Tokenizers optimized for Research and Production.,50.0,33,True,2022-01-17 22:05:25.000,0.11.4,67.0,tokenizers,conda-forge/tokenizers,,,,133.0,40.0,https://pypi.org/project/tokenizers,2022-01-17 22:05:25.000,93.0,4434948.0,4440880.0,https://anaconda.org/conda-forge/tokenizers,2022-01-18 18:19:00.710,112724.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +153,sktime,alan-turing-institute/sktime,time-series-data,,https://github.com/alan-turing-institute/sktime,https://github.com/alan-turing-institute/sktime,BSD-3-Clause,2018-11-06 15:08:24.000,2022-02-10 14:28:31.000000,2022-02-09 20:29:32,2287.0,168.0,741,109.0,1050.0,304.0,606.0,4938,A unified framework for machine learning with time series.,141.0,33,True,2022-02-01 21:40:02.000,0.10.0,19.0,sktime,conda-forge/sktime-all-extras,,,['sklearn'],367.0,348.0,https://pypi.org/project/sktime,2021-12-08 20:04:41.000,19.0,139670.0,139929.0,https://anaconda.org/conda-forge/sktime-all-extras,2022-02-03 21:43:03.692,1810.0,,,,,1.0,64.0,,,,,,,,,,,,,,,,,,,, +154,Perspective,finos/perspective,data-viz,,https://github.com/finos/perspective,https://github.com/finos/perspective,Apache-2.0,2017-11-02 16:27:54.000,2022-02-06 06:01:42.000000,2022-02-06 06:01:41,5018.0,198.0,441,98.0,1165.0,72.0,424.0,4201,"A data visualization and analytics component, especially well-suited for large and/or streaming datasets.",65.0,33,True,2022-02-02 02:26:58.000,1.2.0,63.0,perspective-python,conda-forge/perspective,,,['jupyter'],234.0,225.0,https://pypi.org/project/perspective-python,2022-02-02 02:26:58.000,9.0,4205.0,8381.0,https://anaconda.org/conda-forge/perspective,2022-02-02 18:38:49.633,40120.0,,,,,2.0,,,@finos/perspective-jupyterlab,https://www.npmjs.com/package/@finos/perspective-jupyterlab,2022-02-01 23:34:51.900,,2170.0,,,,,,,,,,,,,, +155,Tesseract,madmaze/pytesseract,ocr,,https://github.com/madmaze/pytesseract,https://github.com/madmaze/pytesseract,Apache-2.0,2010-10-27 23:02:49.000,2022-02-08 19:12:09.000000,2022-02-02 15:33:55,463.0,31.0,572,102.0,121.0,12.0,278.0,4020,Python-tesseract is an optical character recognition (OCR) tool for python.,40.0,33,True,2022-01-25 22:56:33.000,0.3.9,25.0,pytesseract,conda-forge/pytesseract,,,,919.0,,https://pypi.org/project/pytesseract,2021-06-28 23:00:22.000,919.0,519519.0,535211.0,https://anaconda.org/conda-forge/pytesseract,2022-01-26 21:37:36.574,486477.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +156,Ignite,pytorch/ignite,ml-frameworks,,https://github.com/pytorch/ignite,https://github.com/pytorch/ignite,BSD-3-Clause,2017-11-23 17:31:21.000,2022-02-10 10:45:35.000000,2022-02-08 11:29:34,1332.0,67.0,518,60.0,1437.0,136.0,878.0,3851,High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.,164.0,33,True,2022-01-17 15:29:55.000,0.4.8,808.0,pytorch-ignite,pytorch/ignite,,,['pytorch'],76.0,,https://pypi.org/project/pytorch-ignite,2022-02-10 00:13:11.000,76.0,117295.0,119100.0,https://anaconda.org/pytorch/ignite,2022-01-17 15:33:33.872,79422.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +157,geopy,geopy/geopy,geospatial-data,,https://github.com/geopy/geopy,https://github.com/geopy/geopy,MIT,2010-03-04 22:05:28.000,2021-12-15 15:51:51.000000,2021-09-26 10:28:21,1072.0,,555,97.0,250.0,24.0,227.0,3560,Geocoding library for Python.,123.0,33,True,2021-07-11 12:18:10.000,2.2.0,58.0,geopy,conda-forge/geopy,,,,37020.0,33141.0,https://pypi.org/project/geopy,2021-07-11 12:15:26.000,3879.0,3149909.0,3159047.0,https://anaconda.org/conda-forge/geopy,2021-07-12 18:34:05.605,648835.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +158,Dedupe,dedupeio/dedupe,nlp,,https://github.com/dedupeio/dedupe,https://github.com/dedupeio/dedupe,MIT,2012-04-20 14:57:36.000,2022-02-10 00:41:39.000000,2022-02-08 00:55:04,2920.0,78.0,460,124.0,275.0,28.0,657.0,3276,"A python library for accurate and scalable fuzzy matching, record deduplication and entity-resolution.",63.0,33,True,2022-02-03 17:07:56.000,2.0.12,163.0,dedupe,conda-forge/dedupe,,,,259.0,212.0,https://pypi.org/project/dedupe,2022-02-03 17:07:56.000,47.0,281874.0,282461.0,https://anaconda.org/conda-forge/dedupe,2022-02-04 12:31:59.260,1175.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +159,ClearML,allegroai/clearml,ml-experiments,,https://github.com/allegroai/clearml,https://github.com/allegroai/clearml,Apache-2.0,2019-06-10 08:18:32.000,2022-02-08 22:34:41.000000,2022-02-07 11:38:11,1523.0,110.0,412,74.0,114.0,166.0,294.0,2987,"ClearML - Auto-Magical CI/CD to streamline your ML workflow. Experiment Manager, MLOps and Data-Management.",46.0,33,True,2022-01-20 07:04:15.000,1.1.6,53.0,clearml,,allegroai/trains,,,191.0,187.0,https://pypi.org/project/clearml,2022-02-07 11:36:03.000,4.0,61791.0,62743.0,,,,https://hub.docker.com/r/allegroai/trains,2020-10-05 10:16:46.865671,,30103.0,2.0,385.0,,,,,,,,,,,,,,,,,,,, +160,torchtext,pytorch/text,nlp,,https://github.com/pytorch/text,https://github.com/pytorch/text,BSD-3-Clause,2016-12-12 00:56:03.000,2022-02-10 12:36:13.000000,2022-02-09 05:13:33,996.0,113.0,685,247.0,984.0,323.0,363.0,2945,Data loaders and abstractions for text and NLP.,123.0,33,True,2022-01-27 22:34:29.000,0.11.2,19.0,torchtext,,,,['pytorch'],433.0,,https://pypi.org/project/torchtext,2022-01-27 20:39:13.000,433.0,135125.0,135125.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +161,MONAI,Project-MONAI/MONAI,medical-data,,https://github.com/Project-MONAI/MONAI,https://github.com/Project-MONAI/MONAI,Apache-2.0,2019-10-11 16:41:38.000,2022-02-10 14:21:45.000000,2022-02-10 09:13:40,1697.0,177.0,523,79.0,1822.0,147.0,1308.0,2722,AI Toolkit for Healthcare Imaging.,85.0,33,True,2021-11-25 21:19:49.000,0.8.0,39.0,monai,conda-forge/monai,,,['pytorch'],213.0,202.0,https://pypi.org/project/monai,2022-02-09 20:27:32.000,11.0,44184.0,44229.0,https://anaconda.org/conda-forge/monai,2022-01-09 02:58:07.863,90.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +162,GPyTorch,cornellius-gp/gpytorch,probabilistics,,https://github.com/cornellius-gp/gpytorch,https://github.com/cornellius-gp/gpytorch,MIT,2017-06-09 14:48:20.000,2022-02-09 16:46:07.000000,2022-02-09 16:42:54,3582.0,54.0,392,53.0,737.0,249.0,800.0,2674,A highly efficient and modular implementation of Gaussian Processes in PyTorch.,91.0,33,True,2021-12-04 15:50:17.000,1.6.0,31.0,gpytorch,conda-forge/gpytorch,,,['pytorch'],508.0,478.0,https://pypi.org/project/gpytorch,2021-12-04 15:50:17.000,30.0,140827.0,141892.0,https://anaconda.org/conda-forge/gpytorch,2021-12-14 02:46:49.626,24509.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +163,Flax,google/flax,ml-frameworks,,https://github.com/google/flax,https://github.com/google/flax,Apache-2.0,2020-01-10 09:48:37.000,2022-02-10 14:05:26.000000,2022-02-09 14:06:41,2477.0,163.0,292,72.0,1122.0,182.0,310.0,2632,Flax is a neural network library for JAX that is designed for flexibility.,132.0,33,True,2022-01-27 14:47:49.000,0.4.0,16.0,flax,conda-forge/flax,,,['jax'],716.0,659.0,https://pypi.org/project/flax,2022-01-27 14:47:49.000,57.0,88058.0,88259.0,https://anaconda.org/conda-forge/flax,2022-01-27 17:22:13.419,2208.0,,,,,2.0,31.0,,,,,,,,,,,,,,,,,,,, +164,Keras Tuner,keras-team/keras-tuner,hyperopt,,https://github.com/keras-team/keras-tuner,https://github.com/keras-team/keras-tuner,Apache-2.0,2019-06-06 22:38:21.000,2022-01-30 01:41:37.000000,2022-01-20 18:34:51,869.0,10.0,315,65.0,275.0,162.0,203.0,2463,Hyperparameter tuning for humans.,42.0,33,True,2021-11-05 17:28:50.000,1.1.0,11.0,keras-tuner,conda-forge/keras-tuner,,,['tensorflow'],1139.0,1105.0,https://pypi.org/project/keras-tuner,2021-11-05 17:28:50.000,34.0,528440.0,528653.0,https://anaconda.org/conda-forge/keras-tuner,2022-01-12 03:27:55.158,4909.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +165,scikit-optimize,scikit-optimize/scikit-optimize,hyperopt,,https://github.com/scikit-optimize/scikit-optimize,https://github.com/scikit-optimize/scikit-optimize,BSD-3-Clause,2016-03-20 21:10:54.000,2022-02-03 21:29:27.000000,2021-10-12 13:32:38,1570.0,,417,67.0,512.0,232.0,387.0,2286,Sequential model-based optimization with a `scipy.optimize` interface.,75.0,33,True,2021-10-12 15:33:19.000,0.9.0,23.0,scikit-optimize,conda-forge/scikit-optimize,,,,2526.0,2352.0,https://pypi.org/project/scikit-optimize,2021-10-12 14:21:32.000,174.0,780955.0,790508.0,https://anaconda.org/conda-forge/scikit-optimize,2021-12-15 05:01:56.230,525449.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +166,TF-Agents,tensorflow/agents,reinforcement-learning,,https://github.com/tensorflow/agents,https://github.com/tensorflow/agents,Apache-2.0,2018-11-17 00:29:12.000,2022-02-09 18:44:42.000000,2022-02-09 18:43:45,2004.0,51.0,596,84.0,169.0,109.0,419.0,2180,"TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.",116.0,33,True,2021-11-15 17:59:06.000,0.11.0,30.0,tf-agents,,,,['tensorflow'],714.0,700.0,https://pypi.org/project/tf-agents,2022-01-20 14:56:44.000,14.0,139878.0,139878.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +167,numexpr,pydata/numexpr,data-containers,,https://github.com/pydata/numexpr,https://github.com/pydata/numexpr,MIT,2013-11-30 22:33:48.000,2022-02-06 22:44:16.000000,2022-02-06 22:44:16,709.0,19.0,172,57.0,78.0,60.0,259.0,1713,"Fast numerical array expression evaluator for Python, NumPy, PyTables, pandas, bcolz and more.",59.0,33,True,2021-12-10 22:03:53.000,2.8.1,43.0,numexpr,conda-forge/numexpr,,,,2973.0,,https://pypi.org/project/numexpr,2021-12-15 14:40:01.971,2973.0,2050283.0,2104715.0,https://anaconda.org/conda-forge/numexpr,2022-01-26 18:55:18.852,3592533.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +168,Ax,facebook/Ax,hyperopt,,https://github.com/facebook/Ax,https://github.com/facebook/Ax,MIT,2019-02-09 15:23:44.000,2022-02-10 03:51:33.000000,2022-02-10 03:51:30,1680.0,178.0,180,73.0,464.0,39.0,316.0,1696,Adaptive Experimentation Platform.,109.0,33,True,2021-12-16 18:07:17.000,0.2.3,25.0,ax-platform,conda-forge/ax-platform,,,['pytorch'],252.0,238.0,https://pypi.org/project/ax-platform,2021-12-16 18:07:17.000,14.0,107496.0,107582.0,https://anaconda.org/conda-forge/ax-platform,2021-06-22 17:59:03.357,693.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +169,torchaudio,pytorch/audio,audio,,https://github.com/pytorch/audio,https://github.com/pytorch/audio,BSD-2-Clause,2017-05-05 00:38:05.000,2022-02-10 12:47:42.000000,2022-02-10 05:23:35,1313.0,146.0,385,60.0,1639.0,150.0,449.0,1586,"Data manipulation and transformation for audio signal processing, powered by PyTorch.",150.0,33,True,2022-01-27 22:33:14.000,0.10.2,19.0,torchaudio,,,,['pytorch'],117.0,,https://pypi.org/project/torchaudio,2022-01-27 20:38:29.000,117.0,307680.0,307680.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +170,Geocoder,DenisCarriere/geocoder,geospatial-data,,https://github.com/DenisCarriere/geocoder,https://github.com/DenisCarriere/geocoder,MIT,2014-01-13 04:19:21.000,2022-01-18 20:15:51.000000,2018-10-12 15:53:05,1251.0,,267,54.0,151.0,99.0,217.0,1423,Python Geocoder.,74.0,33,False,2018-04-04 12:34:51.000,1.38.1,110.0,geocoder,conda-forge/geocoder,,,,4908.0,4416.0,https://pypi.org/project/geocoder,2018-04-04 12:34:51.000,492.0,1997004.0,1998597.0,https://anaconda.org/conda-forge/geocoder,2019-06-27 16:40:50.469,95635.0,,,,,2.0,,,,,,,,,,,,,geocoder,,,,,,,, +171,arviz,arviz-devs/arviz,interpretability,,https://github.com/arviz-devs/arviz,https://github.com/arviz-devs/arviz,Apache-2.0,2015-07-29 11:51:10.000,2022-02-10 12:06:02.000000,2022-02-08 20:51:34,1349.0,32.0,260,44.0,1274.0,193.0,560.0,1163,Exploratory analysis of Bayesian models with Python.,111.0,33,True,2021-10-03 11:17:21.000,0.11.4,25.0,arviz,conda-forge/arviz,,,,1950.0,1879.0,https://pypi.org/project/arviz,2021-10-03 11:17:21.000,71.0,322597.0,341373.0,https://anaconda.org/conda-forge/arviz,2021-10-03 15:30:41.137,619548.0,,,,,1.0,111.0,,,,,,,,,,,,,,,,,,,, +172,NIPYPE,nipy/nipype,medical-data,,https://github.com/nipy/nipype,https://github.com/nipy/nipype,Apache-2.0,2010-07-22 17:06:49.000,2022-01-21 20:10:47.000000,2021-12-15 21:43:27,14314.0,21.0,475,48.0,2185.0,359.0,896.0,615,Workflows and interfaces for neuroimaging packages.,227.0,33,True,2021-10-20 17:40:54.000,1.7.0,56.0,nipype,conda-forge/nipype,,,,994.0,843.0,https://pypi.org/project/nipype,2021-10-20 15:33:29.000,151.0,42872.0,49728.0,https://anaconda.org/conda-forge/nipype,2021-10-20 17:02:23.801,459377.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +173,tensorflow-upstream,ROCmSoftwarePlatform/tensorflow-upstream,ml-frameworks,,https://github.com/ROCmSoftwarePlatform/tensorflow-upstream,https://github.com/ROCmSoftwarePlatform/tensorflow-upstream,Apache-2.0,2018-04-09 21:24:50.000,2022-02-10 12:07:07.000000,2022-02-08 01:26:04,128167.0,3821.0,67,52.0,1253.0,56.0,269.0,581,TensorFlow ROCm port.,3931.0,33,True,2021-12-17 21:13:49.000,2.7.0,71.0,tensorflow-rocm,,,,['tensorflow'],5.0,,https://pypi.org/project/tensorflow-rocm,2021-12-17 21:13:49.000,5.0,40745.0,40745.0,,,,,,,,2.0,17.0,,,,,,,,,,,,,,,,,,,, +174,NiBabel,nipy/nibabel,medical-data,,https://github.com/nipy/nibabel,https://github.com/nipy/nibabel,MIT,2010-07-22 16:28:30.000,2022-02-10 14:29:59.000000,2022-02-10 14:29:58,5095.0,24.0,234,40.0,660.0,140.0,312.0,458,Python package to access a cacophony of neuro-imaging file formats.,93.0,33,True,2022-02-07 16:58:12.000,3.2.2,33.0,nibabel,conda-forge/nibabel,,,,7230.0,6261.0,https://pypi.org/project/nibabel,2022-02-07 16:58:12.000,969.0,202668.0,208586.0,https://anaconda.org/conda-forge/nibabel,2022-02-07 20:18:47.734,408406.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +175,Magenta,magenta/magenta,audio,,https://github.com/magenta/magenta,https://github.com/magenta/magenta,Apache-2.0,2016-05-05 20:10:40.000,2022-02-08 16:31:25.000000,2021-06-30 21:44:13,1393.0,,3518,794.0,1101.0,321.0,570.0,17402,Magenta: Music and Art Generation with Machine Intelligence.,149.0,32,True,2020-11-12 19:17:18.000,2.1.3,66.0,magenta,,,,['tensorflow'],368.0,332.0,https://pypi.org/project/magenta,2020-11-12 19:17:18.000,36.0,6270.0,6270.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +176,Prophet,facebook/prophet,time-series-data,,https://github.com/facebook/prophet,https://github.com/facebook/prophet,MIT,2016-11-16 01:50:08.000,2022-02-02 18:19:43.000000,2022-01-31 19:18:56,698.0,4.0,3967,416.0,336.0,180.0,1584.0,14026,Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear..,138.0,32,True,2021-04-02 23:45:16.000,1.0,14.0,fbprophet,conda-forge/prophet,,,,120.0,,https://pypi.org/project/fbprophet,2020-09-05 16:12:50.000,120.0,1314459.0,1317285.0,https://anaconda.org/conda-forge/prophet,2021-08-23 03:00:23.164,28166.0,,,,,1.0,642.0,,,,,,,,,,,,,,,,,,,, +177,Recommenders,microsoft/recommenders,recommender-systems,,https://github.com/microsoft/recommenders,https://github.com/microsoft/recommenders,MIT,2018-09-19 10:06:07.000,2022-02-10 12:16:34.000000,2022-01-13 09:36:20,7343.0,155.0,2113,260.0,986.0,123.0,531.0,12186,Best Practices on Recommendation Systems.,105.0,32,True,2022-01-13 20:18:21.000,1.0.0,10.0,recommenders,,,,,13.0,11.0,https://pypi.org/project/recommenders,2021-03-14 00:31:18.000,2.0,4608.0,4611.0,,,,,,,,1.0,122.0,,,,,,,,4.0,,,,,,,,,,,, +178,TFlearn,tflearn/tflearn,ml-frameworks,,https://github.com/tflearn/tflearn,https://github.com/tflearn/tflearn,MIT,2016-03-31 12:05:53.000,2021-01-25 09:41:59.000000,2020-11-30 04:34:51,613.0,,2429,466.0,255.0,563.0,362.0,9577,Deep learning library featuring a higher-level API for TensorFlow.,128.0,32,False,2020-11-11 19:26:11.000,0.5.0,8.0,tflearn,,,,['tensorflow'],4192.0,3704.0,https://pypi.org/project/tflearn,2020-11-11 19:13:47.000,488.0,12582.0,12582.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +179,Annoy,spotify/annoy,nn-search,,https://github.com/spotify/annoy,https://github.com/spotify/annoy,Apache-2.0,2013-04-01 20:29:40.000,2022-01-28 19:54:18.237000,2022-01-03 17:22:52,834.0,2.0,964,318.0,247.0,38.0,300.0,9437,Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk.,80.0,32,True,2020-09-18 16:07:59.000,1.17.0,43.0,annoy,conda-forge/python-annoy,,,,2154.0,1919.0,https://pypi.org/project/annoy,2020-09-18 16:07:59.000,235.0,845835.0,849137.0,https://anaconda.org/conda-forge/python-annoy,2022-01-28 19:54:18.237,214657.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +180,fuzzywuzzy,seatgeek/fuzzywuzzy,nlp,,https://github.com/seatgeek/fuzzywuzzy,https://github.com/seatgeek/fuzzywuzzy,GPL-2.0,2011-07-08 19:32:34.000,2021-11-02 23:56:01.000000,2021-09-09 20:54:41,384.0,,864,268.0,145.0,103.0,102.0,8603,Fuzzy String Matching in Python.,70.0,32,False,2020-02-13 22:14:12.000,0.18.0,27.0,fuzzywuzzy,conda-forge/fuzzywuzzy,,,,13022.0,11089.0,https://pypi.org/project/fuzzywuzzy,2020-02-13 21:06:25.000,1933.0,5447912.0,5453084.0,https://anaconda.org/conda-forge/fuzzywuzzy,2020-11-18 12:59:01.409,346584.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +181,TPOT,EpistasisLab/tpot,hyperopt,,https://github.com/EpistasisLab/tpot,https://github.com/EpistasisLab/tpot,LGPL-3.0,2015-11-03 21:08:40.000,2022-02-06 17:03:57.000000,2021-01-06 15:17:46,2368.0,,1420,293.0,403.0,234.0,602.0,8435,A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.,108.0,32,False,2021-01-06 15:20:08.000,0.11.7,60.0,tpot,conda-forge/tpot,,,['sklearn'],1342.0,1288.0,https://pypi.org/project/tpot,2021-01-06 15:20:08.000,54.0,27537.0,29715.0,https://anaconda.org/conda-forge/tpot,2021-03-05 04:04:38.005,141624.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +182,Ludwig,ludwig-ai/ludwig,ml-frameworks,,https://github.com/ludwig-ai/ludwig,https://github.com/ludwig-ai/ludwig,Apache-2.0,2018-12-27 23:58:12.000,2022-02-09 03:36:11.000000,2022-02-08 22:47:45,2384.0,148.0,961,185.0,1062.0,183.0,498.0,8110,Data-centric declarative deep learning framework.,111.0,32,True,2022-02-01 07:49:55.000,0.4.1,20.0,ludwig,,,,['tensorflow'],107.0,99.0,https://pypi.org/project/ludwig,2022-02-01 07:49:55.000,8.0,2873.0,2873.0,,,,,,,,3.0,,,,,,,,,3.0,,,,,,,,,,,, +183,PaddleHub,PaddlePaddle/PaddleHub,others,,https://github.com/PaddlePaddle/PaddleHub,https://github.com/PaddlePaddle/PaddleHub,Apache-2.0,2018-12-21 06:00:48.000,2022-02-10 01:04:07.000000,2022-01-21 02:49:57,2214.0,31.0,1497,140.0,770.0,380.0,624.0,7508,"Awesome pre-trained models toolkit based on PaddlePaddle.(300+ models including Image, Text, Audio and Video with Easy..",54.0,32,True,2021-12-28 02:55:41.000,2.2.0,47.0,paddlehub,,,,['paddle'],694.0,690.0,https://pypi.org/project/paddlehub,2021-12-28 02:55:41.000,4.0,9572.0,9588.0,,,,,,,,2.0,563.0,,,,,,,,,,,,,,,,,,,, +184,tensorpack,tensorpack/tensorpack,ml-frameworks,,https://github.com/tensorpack/tensorpack,https://github.com/tensorpack/tensorpack,Apache-2.0,2015-12-25 23:08:44.000,2022-02-09 23:36:34.000000,2021-11-27 04:08:51,2937.0,1.0,1808,201.0,205.0,13.0,1332.0,6160,"A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility.",58.0,32,True,2020-04-24 19:01:06.000,0.10.1,37.0,tensorpack,conda-forge/tensorpack,,,['tensorflow'],980.0,934.0,https://pypi.org/project/tensorpack,2021-01-22 08:44:03.000,46.0,21641.0,21693.0,https://anaconda.org/conda-forge/tensorpack,2022-02-06 19:35:57.930,200.0,,,,,3.0,129.0,,,,,,,,,,,,,,,,,,,, +185,stanza,stanfordnlp/stanza,nlp,,https://github.com/stanfordnlp/stanza,https://github.com/stanfordnlp/stanza,Apache-2.0,2017-09-26 08:00:56.000,2022-02-09 22:33:01.000000,2022-01-26 16:46:45,2267.0,3.0,754,144.0,307.0,69.0,570.0,5984,Official Stanford NLP Python Library for Many Human Languages.,41.0,32,True,2021-10-06 06:28:19.000,1.3.0,14.0,stanza,stanfordnlp/stanza,,,,894.0,845.0,https://pypi.org/project/stanza,2021-10-05 06:37:56.000,49.0,380561.0,380762.0,https://anaconda.org/stanfordnlp/stanza,2021-10-05 07:17:34.873,4643.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +186,Pydub,jiaaro/pydub,audio,,https://github.com/jiaaro/pydub,https://github.com/jiaaro/pydub,MIT,2011-05-02 18:42:38.000,2021-12-28 02:38:36.000000,2021-06-08 14:06:40,742.0,,781,126.0,181.0,204.0,256.0,5904,Manipulate audio with a simple and easy high level interface.,90.0,32,True,2021-03-10 02:10:41.000,0.25.1,68.0,pydub,conda-forge/pydub,,,,11408.0,10507.0,https://pypi.org/project/pydub,2021-03-10 02:09:53.000,901.0,1722314.0,1722855.0,https://anaconda.org/conda-forge/pydub,2021-03-13 05:16:50.142,20575.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +187,Bayesian Optimization,fmfn/BayesianOptimization,hyperopt,,https://github.com/fmfn/BayesianOptimization,https://github.com/fmfn/BayesianOptimization,MIT,2014-06-06 08:18:56.000,2022-01-28 14:10:56.000000,2020-12-19 01:11:23,199.0,,1212,150.0,81.0,47.0,173.0,5737,A Python implementation of global optimization with gaussian processes.,27.0,32,False,2020-05-16 16:03:51.000,1.2.0,8.0,bayesian-optimization,,,,,1116.0,1051.0,https://pypi.org/project/bayesian-optimization,2020-05-16 15:56:09.000,65.0,139281.0,139282.0,,,,,,,,2.0,76.0,,,,,,,,,,,,,,,,,,,, +188,Autograd,HIPS/autograd,others,,https://github.com/HIPS/autograd,https://github.com/HIPS/autograd,MIT,2014-11-24 15:50:23.000,2021-04-22 18:19:00.000000,2021-03-03 09:27:58,1376.0,,782,218.0,207.0,163.0,223.0,5653,Efficiently computes derivatives of numpy code.,51.0,32,True,2017-08-24 17:00:41.000,1.1.13,24.0,autograd,conda-forge/autograd,,,,3207.0,2937.0,https://pypi.org/project/autograd,2019-07-25 16:21:07.000,270.0,1242951.0,1245974.0,https://anaconda.org/conda-forge/autograd,2019-07-25 18:29:55.493,199536.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +189,Metaflow,Netflix/metaflow,ml-experiments,,https://github.com/Netflix/metaflow,https://github.com/Netflix/metaflow,Apache-2.0,2019-09-17 17:48:25.000,2022-02-10 00:14:49.000000,2022-02-03 22:48:07,466.0,79.0,464,230.0,580.0,225.0,197.0,5286,Build and manage real-life data science projects with ease!.,47.0,32,True,2022-01-26 00:36:44.000,2.5.0,40.0,metaflow,conda-forge/metaflow,,,,249.0,244.0,https://pypi.org/project/metaflow,2022-01-26 00:36:44.000,5.0,44706.0,45905.0,https://anaconda.org/conda-forge/metaflow,2022-01-26 02:44:04.006,31184.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +190,GluonCV,dmlc/gluon-cv,image,,https://github.com/dmlc/gluon-cv,https://github.com/dmlc/gluon-cv,Apache-2.0,2018-02-26 01:33:21.000,2022-02-10 09:01:03.000000,2022-02-02 20:45:58,890.0,5.0,1133,154.0,936.0,60.0,751.0,5056,Gluon CV Toolkit.,115.0,32,True,2021-07-25 02:48:59.000,0.10.4,1297.0,gluoncv,,,,['mxnet'],717.0,658.0,https://pypi.org/project/gluoncv,2022-02-10 09:01:03.000,59.0,563365.0,563365.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +191,DEAP,deap/deap,distributed-ml,,https://github.com/DEAP/deap,https://github.com/DEAP/deap,LGPL-3.0,2014-05-21 20:07:39.000,2022-02-07 17:43:18.000000,2022-01-22 18:26:24,2187.0,23.0,947,205.0,187.0,225.0,246.0,4581,Distributed Evolutionary Algorithms in Python.,78.0,32,False,2020-01-21 01:18:06.000,1.3.1,19.0,deap,conda-forge/deap,,,,2691.0,2370.0,https://pypi.org/project/deap,2020-01-21 01:18:06.000,321.0,198310.0,200695.0,https://anaconda.org/conda-forge/deap,2021-11-07 17:27:38.136,162243.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +192,InterpretML,interpretml/interpret,interpretability,,https://github.com/interpretml/interpret,https://github.com/interpretml/interpret,MIT,2019-05-03 05:47:52.000,2022-02-09 17:34:15.000000,2022-02-09 17:34:05,1896.0,75.0,556,145.0,45.0,87.0,184.0,4542,Fit interpretable models. Explain blackbox machine learning.,28.0,32,True,2021-09-23 20:41:03.000,0.2.7,37.0,interpret,,,,['jupyter'],165.0,157.0,https://pypi.org/project/interpret,2021-09-23 19:52:27.000,8.0,87843.0,87843.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +193,PML,KevinMusgrave/pytorch-metric-learning,pytorch-utils,,https://github.com/KevinMusgrave/pytorch-metric-learning,https://github.com/KevinMusgrave/pytorch-metric-learning,MIT,2019-10-23 17:20:35.000,2022-02-10 08:02:30.000000,2022-01-12 13:03:18,838.0,91.0,505,67.0,65.0,43.0,281.0,4096,"The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.",23.0,32,True,2021-12-28 04:39:25.000,1.1.0,172.0,pytorch-metric-learning,metric-learning/pytorch-metric-learning,,,['pytorch'],205.0,197.0,https://pypi.org/project/pytorch-metric-learning,2022-02-10 08:02:30.000,8.0,161868.0,162099.0,https://anaconda.org/metric-learning/pytorch-metric-learning,2021-12-28 05:17:47.281,5799.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +194,BigDL,intel-analytics/BigDL,distributed-ml,,https://github.com/intel-analytics/BigDL,https://github.com/intel-analytics/BigDL,Apache-2.0,2016-08-29 07:59:50.000,2022-02-10 13:43:44.000000,2022-02-10 13:43:44,16666.0,397.0,967,243.0,2885.0,367.0,806.0,3837,Building Large-Scale AI Applications for Distributed Big Data.,130.0,32,True,2021-07-09 12:20:26.000,0.13.0,133.0,bigdl,,,,,38.0,33.0,https://pypi.org/project/bigdl,2022-02-10 13:12:34.000,1.0,13798.0,13798.0,,,,,,,,2.0,,,,,,,,,,,,,,com.intel.analytics.bigdl:bigdl-SPARK_2.4,https://search.maven.org/artifact/com.intel.analytics.bigdl/bigdl-SPARK_2.4,2021-04-20 01:33:14,4.0,,,, +195,speechbrain,speechbrain/speechbrain,audio,,https://github.com/speechbrain/speechbrain,https://github.com/speechbrain/speechbrain,Apache-2.0,2020-04-28 17:48:45.000,2022-02-08 19:22:12.000000,2022-01-24 15:10:41,5961.0,313.0,667,107.0,659.0,120.0,470.0,3699,A PyTorch-based Speech Toolkit.,149.0,32,True,2021-12-20 04:22:27.000,0.5.11,10.0,speechbrain,,,,['pytorch'],123.0,121.0,https://pypi.org/project/speechbrain,2021-12-20 04:23:25.000,2.0,6433.0,6433.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +196,bqplot,bqplot/bqplot,data-viz,,https://github.com/bqplot/bqplot,https://github.com/bqplot/bqplot,Apache-2.0,2015-09-26 04:02:18.000,2022-02-10 14:19:20.000000,2022-02-10 08:31:03,3491.0,62.0,457,108.0,911.0,222.0,355.0,3232,Plotting library for IPython/Jupyter notebooks.,56.0,32,True,2022-01-07 12:38:39.000,0.12.32,99.0,bqplot,conda-forge/bqplot,,,['jupyter'],130.0,30.0,https://pypi.org/project/bqplot,2022-01-07 12:37:12.000,90.0,64622.0,102334.0,https://anaconda.org/conda-forge/bqplot,2022-01-07 13:02:09.921,920799.0,,,,,2.0,,,bqplot,https://www.npmjs.com/package/bqplot,2022-01-07 12:35:41.247,10.0,24368.0,,,,,,,,,,,,,, +197,VisPy,vispy/vispy,data-viz,,https://github.com/vispy/vispy,https://github.com/vispy/vispy,BSD-3-Clause,2013-03-21 18:43:22.000,2022-02-08 01:26:52.000000,2022-02-08 01:26:52,6919.0,19.0,581,124.0,1017.0,283.0,1024.0,2807,High-performance interactive 2D/3D data visualization library.,168.0,32,True,2022-02-04 23:31:38.000,0.9.6,29.0,vispy,conda-forge/vispy,,,['jupyter'],773.0,679.0,https://pypi.org/project/vispy,2022-02-04 22:57:54.000,94.0,41056.0,44953.0,https://anaconda.org/conda-forge/vispy,2022-02-05 03:17:42.117,202147.0,,,,,2.0,,,vispy,https://www.npmjs.com/package/vispy,2020-03-15 14:39:41.516,,10.0,,,,,,,,,,,,,, +198,ART,Trusted-AI/adversarial-robustness-toolbox,adversarial,,https://github.com/Trusted-AI/adversarial-robustness-toolbox,https://github.com/Trusted-AI/adversarial-robustness-toolbox,MIT,2018-03-15 14:40:43.000,2022-02-10 13:54:12.000000,2022-02-09 21:47:55,9410.0,257.0,756,86.0,822.0,75.0,559.0,2776,"Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction,..",90.0,32,True,2022-01-07 13:51:53.000,1.9.1,38.0,adversarial-robustness-toolbox,conda-forge/adversarial-robustness-toolbox,,,,190.0,184.0,https://pypi.org/project/adversarial-robustness-toolbox,2022-01-07 13:32:42.000,6.0,4128.0,4534.0,https://anaconda.org/conda-forge/adversarial-robustness-toolbox,2022-01-10 15:59:27.185,7716.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +199,implicit,benfred/implicit,recommender-systems,,https://github.com/benfred/implicit,https://github.com/benfred/implicit,MIT,2016-04-17 03:45:23.000,2022-01-29 16:35:56.077000,2022-01-29 04:10:37,372.0,50.0,533,81.0,165.0,62.0,314.0,2623,Fast Python Collaborative Filtering for Implicit Feedback Datasets.,30.0,32,True,2022-01-29 04:12:37.000,0.5.2,41.0,implicit,conda-forge/implicit,,,,566.0,535.0,https://pypi.org/project/implicit,2022-01-29 04:12:37.000,31.0,162347.0,169057.0,https://anaconda.org/conda-forge/implicit,2022-01-29 16:35:56.077,328809.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +200,mrjob,Yelp/mrjob,data-pipelines,,https://github.com/Yelp/mrjob,https://github.com/Yelp/mrjob,Apache-2.0,2010-10-13 18:35:21.000,2022-02-06 18:33:13.189000,2020-11-16 22:20:52,8622.0,,600,111.0,918.0,205.0,1093.0,2574,Run MapReduce jobs on Hadoop or Amazon Web Services.,142.0,32,False,2020-09-17 22:26:01.000,0.7.4,62.0,mrjob,conda-forge/mrjob,,,,1039.0,926.0,https://pypi.org/project/mrjob,2020-09-17 22:26:01.000,113.0,100949.0,107607.0,https://anaconda.org/conda-forge/mrjob,2022-02-06 18:33:13.189,432789.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +201,hmmlearn,hmmlearn/hmmlearn,probabilistics,,https://github.com/hmmlearn/hmmlearn,https://github.com/hmmlearn/hmmlearn,BSD-3-Clause,2014-03-23 10:33:09.000,2022-02-10 14:30:38.000000,2022-02-10 14:30:31,406.0,25.0,686,113.0,81.0,56.0,320.0,2422,"Hidden Markov Models in Python, with scikit-learn like API.",38.0,32,True,2022-02-10 14:13:50.000,0.2.7,10.0,hmmlearn,conda-forge/hmmlearn,,,['sklearn'],1304.0,1178.0,https://pypi.org/project/hmmlearn,2022-02-10 14:13:50.000,126.0,325450.0,328236.0,https://anaconda.org/conda-forge/hmmlearn,2021-11-13 15:23:53.699,108663.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +202,BoTorch,pytorch/botorch,hyperopt,,https://github.com/pytorch/botorch,https://github.com/pytorch/botorch,MIT,2018-07-30 23:59:57.000,2022-02-10 04:48:13.000000,2022-02-09 15:14:07,1077.0,65.0,237,50.0,781.0,57.0,182.0,2182,Bayesian optimization in PyTorch.,68.0,32,True,2021-12-09 01:25:08.000,0.6.0,19.0,botorch,conda-forge/botorch,,,['pytorch'],219.0,207.0,https://pypi.org/project/botorch,2021-12-09 01:25:08.000,12.0,128691.0,129642.0,https://anaconda.org/conda-forge/botorch,2021-12-09 13:45:15.046,17123.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +203,pgmpy,pgmpy/pgmpy,probabilistics,,https://github.com/pgmpy/pgmpy,https://github.com/pgmpy/pgmpy,MIT,2013-09-20 08:18:58.000,2022-01-21 08:39:02.000000,2022-01-21 08:39:02,2805.0,10.0,627,80.0,754.0,218.0,552.0,1984,"Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in..",103.0,32,True,2021-12-30 23:16:42.000,0.1.17,16.0,pgmpy,,,,,324.0,315.0,https://pypi.org/project/pgmpy,2021-12-30 23:11:18.000,9.0,61868.0,61874.0,,,,,,,,2.0,126.0,,,,,,,,,,,,,,,,,,,, +204,Lifelines,CamDavidsonPilon/lifelines,medical-data,,https://github.com/CamDavidsonPilon/lifelines,https://github.com/CamDavidsonPilon/lifelines,MIT,2013-08-28 00:16:42.000,2022-02-04 22:28:18.021000,2022-01-19 23:27:45,2157.0,8.0,461,66.0,450.0,227.0,621.0,1797,Survival analysis in Python.,99.0,32,True,2021-11-30 20:20:36.000,0.26.4,160.0,lifelines,conda-forge/lifelines,,,,867.0,766.0,https://pypi.org/project/lifelines,2021-11-30 20:20:36.000,101.0,362119.0,364766.0,https://anaconda.org/conda-forge/lifelines,2022-02-04 22:28:18.021,180060.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +205,ipyleaflet,jupyter-widgets/ipyleaflet,geospatial-data,,https://github.com/jupyter-widgets/ipyleaflet,https://github.com/jupyter-widgets/ipyleaflet,MIT,2014-05-07 16:32:10.000,2022-02-09 16:13:58.000000,2022-02-09 16:13:58,992.0,40.0,316,66.0,458.0,181.0,293.0,1221,A Jupyter - Leaflet.js bridge.,74.0,32,True,2021-12-06 12:34:17.000,0.15.0,72.0,ipyleaflet,conda-forge/ipyleaflet,,,['jupyter'],1550.0,1446.0,https://pypi.org/project/ipyleaflet,2021-12-06 12:34:17.000,102.0,56329.0,112393.0,https://anaconda.org/conda-forge/ipyleaflet,2021-12-09 18:45:12.043,789797.0,,,,,3.0,,,jupyter-leaflet,https://www.npmjs.com/package/jupyter-leaflet,2021-12-06 12:32:39.669,2.0,44618.0,,,,,,,,,,,,,, +206,TF Model Optimization,tensorflow/model-optimization,tensorflow-utils,,https://github.com/tensorflow/model-optimization,https://github.com/tensorflow/model-optimization,Apache-2.0,2018-10-31 20:34:28.000,2022-02-10 09:04:28.000000,2022-02-10 09:04:18,720.0,37.0,268,125.0,661.0,154.0,149.0,1197,"A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.",65.0,32,True,2022-02-09 08:07:26.000,0.7.1,25.0,tensorflow-model-optimization,,,,['tensorflow'],1513.0,1494.0,https://pypi.org/project/tensorflow-model-optimization,2022-02-09 06:42:12.000,19.0,181907.0,181907.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +207,Wand,emcconville/wand,image,,https://github.com/emcconville/wand,https://github.com/emcconville/wand,MIT,2011-09-30 21:36:38.000,2022-01-31 13:27:57.000000,2022-01-31 13:27:53,1744.0,7.0,192,29.0,190.0,16.0,348.0,1143,The ctypes-based simple ImageMagick binding for Python.,97.0,32,True,2021-08-17 02:43:04.000,0.6.7,50.0,wand,conda-forge/wand,,,,9717.0,9038.0,https://pypi.org/project/wand,2021-08-17 02:13:00.000,679.0,418146.0,418585.0,https://anaconda.org/conda-forge/wand,2020-11-30 13:27:29.373,8600.0,,,,,2.0,5974.0,,,,,,,,,,,,,,,,,,,, +208,PyVista,pyvista/pyvista,data-viz,,https://github.com/pyvista/pyvista,https://github.com/pyvista/pyvista,MIT,2017-05-31 18:01:42.000,2022-02-10 12:46:10.000000,2022-02-10 00:46:09,2526.0,147.0,207,29.0,1169.0,178.0,509.0,1111,3D plotting and mesh analysis through a streamlined interface for the Visualization Toolkit (VTK).,70.0,32,True,2022-01-11 06:33:57.000,0.33.2,54.0,pyvista,conda-forge/pyvista,,,['jupyter'],683.0,598.0,https://pypi.org/project/pyvista,2022-01-11 06:33:57.000,85.0,42401.0,46674.0,https://anaconda.org/conda-forge/pyvista,2022-01-11 14:06:19.759,140739.0,,,,,2.0,489.0,,,,,,,,,,,,,,,,,,,, +209,cartopy,SciTools/cartopy,data-viz,,https://github.com/SciTools/cartopy,https://github.com/SciTools/cartopy,LGPL-3.0,2012-08-03 07:43:59.000,2022-02-01 17:53:30.000000,2022-01-29 00:36:59,2590.0,48.0,302,57.0,969.0,303.0,763.0,993,Cartopy - a cartographic python library with matplotlib support.,107.0,32,False,2022-01-13 02:45:47.000,0.20.2,25.0,cartopy,conda-forge/cartopy,,,,2436.0,2133.0,https://pypi.org/project/cartopy,2022-01-13 02:48:14.000,303.0,136569.0,163836.0,https://anaconda.org/conda-forge/cartopy,2022-01-19 16:01:54.059,1935964.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +210,TensorFlow Transform,tensorflow/transform,tensorflow-utils,,https://github.com/tensorflow/transform,https://github.com/tensorflow/transform,Apache-2.0,2017-02-10 00:36:53.000,2022-02-09 04:38:18.000000,2022-02-09 04:38:17,756.0,39.0,179,60.0,79.0,24.0,152.0,903,Input pipeline framework.,27.0,32,True,2022-01-21 18:33:56.000,1.6.0,45.0,tensorflow-transform,,,,['tensorflow'],746.0,691.0,https://pypi.org/project/tensorflow-transform,2022-01-21 18:33:56.000,55.0,8878713.0,8878713.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +211,zarr,zarr-developers/zarr-python,data-containers,,https://github.com/zarr-developers/zarr-python,https://github.com/zarr-developers/zarr-python,MIT,2015-12-15 14:49:40.000,2022-02-09 07:26:11.000000,2022-02-09 07:20:21,1548.0,58.0,141,42.0,475.0,210.0,281.0,842,"An implementation of chunked, compressed, N-dimensional arrays for Python.",55.0,32,True,2022-02-07 14:06:16.000,2.11.0,50.0,zarr,conda-forge/zarr,,,,1221.0,1030.0,https://pypi.org/project/zarr,2022-02-07 14:06:16.000,191.0,83190.0,100890.0,https://anaconda.org/conda-forge/zarr,2022-02-07 17:13:38.389,1221308.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +212,datalad,datalad/datalad,others,,https://github.com/datalad/datalad,https://github.com/datalad/datalad,MIT,2013-11-01 19:40:08.000,2022-02-10 14:15:29.000000,2022-02-10 06:36:08,15194.0,409.0,88,26.0,2995.0,467.0,2907.0,278,"Keep code, data, containers under control with git and git-annex.",46.0,32,False,2022-02-09 18:00:50.000,0.15.5,78.0,datalad,conda-forge/datalad,,,,48.0,,https://pypi.org/project/datalad,2022-02-09 18:00:50.000,48.0,5841.0,9830.0,https://anaconda.org/conda-forge/datalad,2022-01-10 19:42:09.272,187496.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +213,CNTK,microsoft/CNTK,ml-frameworks,,https://github.com/microsoft/CNTK,https://github.com/microsoft/CNTK,MIT,2015-11-26 09:52:06.000,2021-08-27 04:46:43.000000,2020-03-31 15:55:14,16116.0,,4402,1289.0,552.0,836.0,2527.0,17127,"Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit.",271.0,31,False,2019-04-26 14:13:32.000,2.7,32.0,cntk,,,,,18.0,,https://pypi.org/project/cntk,2020-12-09 22:21:57.000,18.0,1970.0,2160.0,,,,,,,,3.0,13933.0,,,,,,,,,,,,,,,,,,,, +214,Turi Create,apple/turicreate,ml-frameworks,,https://github.com/apple/turicreate,https://github.com/apple/turicreate,BSD-3-Clause,2017-12-01 00:42:04.000,2021-11-29 19:55:31.000000,2021-11-29 19:55:31,1571.0,1.0,1111,360.0,1679.0,484.0,1284.0,10572,Turi Create simplifies the development of custom machine learning models.,85.0,31,True,2020-09-30 22:51:40.000,6.4.1,31.0,turicreate,,,,,307.0,288.0,https://pypi.org/project/turicreate,2020-09-30 22:51:40.000,19.0,28072.0,28171.0,,,,,,,,3.0,4984.0,,,,,,,,,,,,,,,,,,,, +215,pretrainedmodels,Cadene/pretrained-models.pytorch,pytorch-utils,,https://github.com/Cadene/pretrained-models.pytorch,https://github.com/Cadene/pretrained-models.pytorch,BSD-3-Clause,2017-04-09 15:54:23.000,2021-07-29 10:41:37.000000,2020-04-16 08:02:22,154.0,,1755,227.0,45.0,92.0,93.0,8396,"Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.",22.0,31,False,2018-10-29 08:18:45.000,0.7.4,16.0,pretrainedmodels,conda-forge/pretrainedmodels,,,['pytorch'],1472.0,1392.0,https://pypi.org/project/pretrainedmodels,2018-10-29 08:18:45.000,80.0,81450.0,81659.0,https://anaconda.org/conda-forge/pretrainedmodels,2021-04-30 19:04:30.054,4196.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +216,Qlib,microsoft/qlib,financial-data,,https://github.com/microsoft/qlib,https://github.com/microsoft/qlib,MIT,2020-08-14 06:46:00.000,2022-02-09 23:59:17.000000,2022-02-07 13:45:53,1677.0,130.0,1341,217.0,464.0,154.0,308.0,7967,"Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research,..",81.0,31,True,2022-01-19 18:07:01.000,0.8.3,24.0,pyqlib,,,,['pytorch'],11.0,11.0,https://pypi.org/project/pyqlib,2022-01-19 18:07:01.000,,4378.0,4393.0,,,,,,,,1.0,271.0,,,,,,,,,,,,,,,,,,,, +217,carla,carla-simulator/carla,others,,https://github.com/carla-simulator/carla,https://github.com/carla-simulator/carla,MIT,2017-10-24 09:06:23.000,2022-02-10 14:17:33.000000,2021-11-19 11:13:47,5439.0,4.0,2082,237.0,1119.0,504.0,3166.0,7242,Open-source simulator for autonomous driving research.,138.0,31,True,2021-11-17 08:28:27.000,0.9.13,24.0,carla,,,,,127.0,124.0,https://pypi.org/project/carla,2021-11-17 08:28:27.000,3.0,2483.0,2483.0,,,,,,,,2.0,,,,,,,,,-2.0,,,,,,,,,,,, +218,DeepSpeed,microsoft/DeepSpeed,distributed-ml,,https://github.com/microsoft/DeepSpeed,https://github.com/microsoft/DeepSpeed,MIT,2020-01-23 18:35:18.000,2022-02-10 06:07:41.000000,2022-02-10 06:06:02,864.0,98.0,677,123.0,930.0,372.0,394.0,6271,"DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.",89.0,31,True,2022-01-19 00:37:05.000,0.5.10,41.0,deepspeed,,deepspeed/deepspeed,,['pytorch'],173.0,164.0,https://pypi.org/project/deepspeed,2022-01-19 00:36:25.000,9.0,72354.0,72884.0,,,,https://hub.docker.com/r/deepspeed/deepspeed,2021-05-05 21:39:11.981563,3.0,13255.0,2.0,,,,,,,,,,,,,,,,,,,,, +219,tsfresh,blue-yonder/tsfresh,time-series-data,,https://github.com/blue-yonder/tsfresh,https://github.com/blue-yonder/tsfresh,MIT,2016-10-26 11:29:17.000,2021-12-21 18:56:28.651000,2021-12-21 03:31:43,507.0,18.0,956,152.0,403.0,41.0,438.0,6167,Automatic extraction of relevant features from time series:.,82.0,31,True,2021-12-21 03:37:03.000,0.19.0,27.0,tsfresh,conda-forge/tsfresh,,,['sklearn'],55.0,,https://pypi.org/project/tsfresh,2021-12-21 03:37:03.000,55.0,396261.0,398103.0,https://anaconda.org/conda-forge/tsfresh,2021-12-21 18:56:28.651,93984.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +220,SpeechRecognition,Uberi/speech_recognition,audio,,https://github.com/Uberi/speech_recognition,https://github.com/Uberi/speech_recognition,BSD-3-Clause,2014-04-23 04:53:54.000,2022-02-09 15:55:46.000000,2022-02-09 15:55:46,376.0,3.0,1995,283.0,97.0,234.0,279.0,6076,"Speech recognition module for Python, supporting several engines and APIs, online and offline.",42.0,31,True,2017-12-05 14:05:14.000,3.8.1,52.0,SpeechRecognition,conda-forge/speechrecognition,,,,674.0,,https://pypi.org/project/SpeechRecognition,2017-12-05 13:58:29.000,674.0,273281.0,275287.0,https://anaconda.org/conda-forge/speechrecognition,2021-12-13 09:59:53.408,132444.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +221,faust,robinhood/faust,data-pipelines,,https://github.com/robinhood/faust,https://github.com/robinhood/faust,BSD-3-Clause,2017-03-08 18:36:11.000,2022-01-29 00:41:00.000000,2020-10-09 12:59:42,4137.0,,503,136.0,284.0,249.0,236.0,5991,Python Stream Processing.,93.0,31,False,2020-02-25 22:57:18.000,1.10.4,46.0,faust,,,,,968.0,939.0,https://pypi.org/project/faust,2020-02-25 22:57:18.000,29.0,100206.0,100206.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +222,TinyDB,msiemens/tinydb,data-containers,,https://github.com/msiemens/tinydb,https://github.com/msiemens/tinydb,MIT,2013-07-12 23:31:13.000,2022-02-05 15:33:36.000000,2022-01-18 17:25:01,652.0,18.0,422,105.0,137.0,8.0,271.0,4842,TinyDB is a lightweight document oriented database optimized for your happiness :).,73.0,31,True,2022-01-18 17:10:30.000,4.6.1,65.0,tinydb,conda-forge/tinydb,,,,788.0,,https://pypi.org/project/tinydb,2022-01-18 17:10:26.000,788.0,316413.0,318727.0,https://anaconda.org/conda-forge/tinydb,2022-01-18 22:12:29.785,157391.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +223,polars,pola-rs/polars,data-containers,,https://github.com/pola-rs/polars,https://github.com/pola-rs/polars,MIT,2020-05-13 19:45:33.000,2022-02-10 14:27:08.000000,2022-02-10 10:04:53,3131.0,654.0,247,62.0,1583.0,86.0,879.0,4541,Fast multi-threaded DataFrame library in Rust | Python | Node.js.,69.0,31,True,2022-02-09 16:56:41.000,0.12.23,140.0,polars,,,,,13.0,2.0,https://pypi.org/project/polars,2022-02-09 16:56:41.000,11.0,33153.0,33153.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +224,einops,arogozhnikov/einops,ml-frameworks,,https://github.com/arogozhnikov/einops,https://github.com/arogozhnikov/einops,MIT,2018-09-22 00:45:08.000,2022-02-03 07:45:45.000000,2022-02-03 07:45:42,387.0,12.0,182,56.0,54.0,34.0,67.0,4407,"Deep learning operations reinvented (for pytorch, tensorflow, jax and others).",14.0,31,True,2022-01-18 07:38:25.000,0.4.0,6.0,einops,conda-forge/einops,,,,2088.0,1895.0,https://pypi.org/project/einops,2022-01-18 07:38:25.000,193.0,695240.0,695596.0,https://anaconda.org/conda-forge/einops,2022-01-18 22:31:33.149,10326.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +225,VisualDL,PaddlePaddle/VisualDL,ml-experiments,,https://github.com/PaddlePaddle/VisualDL,https://github.com/PaddlePaddle/VisualDL,Apache-2.0,2017-12-20 12:34:31.000,2022-01-27 16:18:22.000000,2021-12-30 09:58:24,860.0,3.0,577,151.0,653.0,61.0,332.0,4273,Deep Learning Visualization Toolkit.,31.0,31,True,2021-11-09 12:29:34.000,2.2.2,35.0,visualdl,,,,['paddle'],979.0,956.0,https://pypi.org/project/visualdl,2022-01-06 11:05:02.000,23.0,53596.0,53604.0,,,,,,,,2.0,164.0,,,,,,,,,,,,,,,,,,,, +226,mlpack,mlpack/mlpack,ml-frameworks,,https://github.com/mlpack/mlpack,https://github.com/mlpack/mlpack,BSD-3-Clause,2014-12-17 18:16:59.000,2022-02-10 04:37:00.000000,2022-01-30 02:20:36,27367.0,83.0,1384,187.0,1750.0,103.0,1350.0,3909,mlpack: a scalable C++ machine learning library --.,283.0,31,True,2020-10-28 18:28:47.000,3.4.2,40.0,mlpack,conda-forge/mlpack,,,,1.0,,https://pypi.org/project/mlpack,2020-10-28 18:28:47.000,1.0,254.0,2513.0,https://anaconda.org/conda-forge/mlpack,2021-11-09 18:05:21.719,97168.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +227,PaddleSeg,PaddlePaddle/PaddleSeg,image,,https://github.com/PaddlePaddle/PaddleSeg,https://github.com/PaddlePaddle/PaddleSeg,Apache-2.0,2019-08-26 02:32:22.000,2022-02-06 07:17:56.000000,2022-02-01 06:32:29,2225.0,184.0,816,53.0,887.0,435.0,441.0,3653,"Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in..",74.0,31,True,2022-01-20 03:15:31.000,2.4.0,14.0,paddleseg,,,,['paddle'],490.0,488.0,https://pypi.org/project/paddleseg,2022-01-20 03:15:31.000,2.0,1249.0,1249.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +228,dyNET,clab/dynet,ml-frameworks,,https://github.com/clab/dynet,https://github.com/clab/dynet,Apache-2.0,2015-02-08 23:09:21.000,2022-01-13 00:41:55.000000,2021-01-27 15:43:03,3267.0,,703,190.0,728.0,259.0,659.0,3278,DyNet: The Dynamic Neural Network Toolkit.,156.0,31,False,2020-10-21 14:31:01.000,2.1.2,24.0,dyNET,,,,,229.0,201.0,https://pypi.org/project/dyNET,2020-10-21 14:31:01.000,28.0,19041.0,19112.0,,,,,,,,3.0,4568.0,,,,,,,,,,,,,,,,,,,, +229,ftfy,rspeer/python-ftfy,nlp,,https://github.com/rspeer/python-ftfy,https://github.com/rspeer/python-ftfy,MIT,2012-08-24 16:14:59.000,2022-02-09 19:54:44.000000,2022-02-09 19:43:12,605.0,15.0,111,73.0,62.0,10.0,116.0,3193,"Fixes mojibake and other glitches in Unicode text, after the fact.",18.0,31,True,2022-02-09 19:44:15.000,6.1.1,48.0,ftfy,conda-forge/ftfy,,,,5329.0,4841.0,https://pypi.org/project/ftfy,2022-02-09 19:44:15.000,488.0,1538291.0,1540690.0,https://anaconda.org/conda-forge/ftfy,2021-05-25 06:35:21.702,139193.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +230,deepface,serengil/deepface,image,,https://github.com/serengil/deepface,https://github.com/serengil/deepface,MIT,2020-02-08 20:42:28.000,2022-02-02 18:43:43.000000,2022-02-02 18:43:43,724.0,84.0,712,66.0,29.0,3.0,393.0,3170,"A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python.",21.0,31,True,2022-01-12 10:39:32.000,0.0.72,71.0,deepface,,,,,409.0,406.0,https://pypi.org/project/deepface,2022-01-12 10:39:32.000,3.0,36815.0,36815.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +231,Koalas,databricks/koalas,data-containers,,https://github.com/databricks/koalas,https://github.com/databricks/koalas,Apache-2.0,2019-01-03 21:46:54.000,2021-10-26 06:53:37.000000,2021-10-21 22:12:35,1547.0,,324,223.0,1629.0,94.0,483.0,3079,Koalas: pandas API on Apache Spark.,51.0,31,True,2021-10-19 22:26:46.000,1.8.2,47.0,koalas,conda-forge/koalas,,,"['spark', 'pandas']",176.0,169.0,https://pypi.org/project/koalas,2021-10-19 22:26:05.000,7.0,2187875.0,2191305.0,https://anaconda.org/conda-forge/koalas,2021-10-20 00:43:43.868,112297.0,,,,,2.0,998.0,,,,,,,,,,,,,,,,,,,, +232,Blaze,blaze/blaze,data-containers,,https://github.com/blaze/blaze,https://github.com/blaze/blaze,BSD-3-Clause,2012-10-26 14:25:22.000,2020-02-01 19:33:09.000000,2019-08-15 21:14:59,7496.0,,381,200.0,942.0,263.0,500.0,3025,NumPy and Pandas interface to Big Data.,64.0,31,False,2016-07-19 20:40:03.000,0.11.0,14.0,blaze,conda-forge/blaze,,,,8863.0,8045.0,https://pypi.org/project/blaze,2016-05-06 21:19:21.000,818.0,14462.0,18085.0,https://anaconda.org/conda-forge/blaze,2018-07-15 22:16:17.685,195667.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +233,Captum,pytorch/captum,interpretability,,https://github.com/pytorch/captum,https://github.com/pytorch/captum,BSD-3-Clause,2019-08-27 15:34:41.000,2022-02-03 23:30:57.000000,2022-01-27 17:25:55,888.0,18.0,303,195.0,543.0,78.0,256.0,2924,Model interpretability and understanding for PyTorch.,78.0,31,True,2021-11-02 21:47:58.000,0.4.1,7.0,captum,conda-forge/captum,,,['pytorch'],410.0,393.0,https://pypi.org/project/captum,2021-11-02 02:41:19.000,17.0,32599.0,32688.0,https://anaconda.org/conda-forge/captum,2022-01-27 08:29:58.970,178.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +234,Catalyst,catalyst-team/catalyst,ml-experiments,,https://github.com/catalyst-team/catalyst,https://github.com/catalyst-team/catalyst,Apache-2.0,2018-08-20 07:56:13.000,2022-02-09 10:59:14.000000,2022-02-07 05:53:36,1689.0,47.0,352,47.0,1065.0,5.0,328.0,2832,Accelerated deep learning R&D.,102.0,31,True,2021-12-28 04:11:48.000,21.12,105.0,catalyst,,,,['pytorch'],503.0,474.0,https://pypi.org/project/catalyst,2022-02-07 06:10:51.000,29.0,11483.0,11483.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +235,ta,bukosabino/ta,financial-data,,https://github.com/bukosabino/ta,https://github.com/bukosabino/ta,MIT,2018-01-02 18:08:48.000,2022-01-27 15:32:04.000000,2022-01-27 15:31:59,603.0,20.0,654,127.0,96.0,109.0,94.0,2786,Technical Analysis Library using Pandas and Numpy.,26.0,31,True,2022-01-09 21:07:25.000,0.9.0,52.0,ta,conda-forge/ta,,,,1007.0,980.0,https://pypi.org/project/ta,2022-01-09 21:07:25.000,27.0,88543.0,88726.0,https://anaconda.org/conda-forge/ta,2022-01-12 11:50:54.974,2204.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +236,Core ML Tools,apple/coremltools,model-serialisation,,https://github.com/apple/coremltools,https://github.com/apple/coremltools,BSD-3-Clause,2017-06-30 07:39:02.000,2022-02-05 03:43:55.000000,2022-01-21 19:53:08,911.0,4.0,389,100.0,540.0,318.0,548.0,2545,"Core ML tools contain supporting tools for Core ML model conversion, editing, and validation.",119.0,31,True,2021-11-09 18:32:21.000,5.1.0,35.0,coremltools,conda-forge/coremltools,,,,901.0,757.0,https://pypi.org/project/coremltools,2021-11-09 18:32:21.000,144.0,94547.0,96298.0,https://anaconda.org/conda-forge/coremltools,2021-10-15 05:58:32.248,26805.0,,,,,1.0,4032.0,,,,,,,,,,,,,,,,,,,, +237,aim,aimhubio/aim,ml-experiments,,https://github.com/aimhubio/aim,https://github.com/aimhubio/aim,Apache-2.0,2019-05-31 18:25:07.000,2022-02-10 14:13:53.000000,2022-02-09 16:25:14,1319.0,216.0,122,32.0,963.0,110.0,219.0,2132,Aim an easy-to-use and performant open-source experiment tracker.,27.0,31,True,2022-02-10 09:31:35.000,3.5.1,119.0,aim,conda-forge/aim,,,,54.0,52.0,https://pypi.org/project/aim,2022-02-04 18:23:58.000,2.0,11582.0,12601.0,https://anaconda.org/conda-forge/aim,2021-10-15 14:36:27.336,7134.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +238,filterpy,rlabbe/filterpy,probabilistics,,https://github.com/rlabbe/filterpy,https://github.com/rlabbe/filterpy,MIT,2014-07-15 02:15:19.000,2021-12-27 15:31:49.000000,2021-05-04 18:33:52,542.0,,481,73.0,68.0,47.0,154.0,2110,"Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman..",36.0,31,True,2018-10-10 22:38:24.000,1.4.5,49.0,filterpy,conda-forge/filterpy,,,,1332.0,1206.0,https://pypi.org/project/filterpy,2018-10-10 22:38:24.000,126.0,650835.0,652117.0,https://anaconda.org/conda-forge/filterpy,2020-05-05 21:13:59.073,71810.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +239,hdbscan,scikit-learn-contrib/hdbscan,others,,https://github.com/scikit-learn-contrib/hdbscan,https://github.com/scikit-learn-contrib/hdbscan,BSD-3-Clause,2015-04-22 13:32:37.000,2022-02-10 13:34:49.848000,2022-02-08 17:00:29,939.0,16.0,396,57.0,113.0,269.0,154.0,2084,A high performance implementation of HDBSCAN clustering.,76.0,31,True,2022-02-08 17:15:41.000,0.8.28.wheels,44.0,hdbscan,conda-forge/hdbscan,,,['sklearn'],1339.0,1189.0,https://pypi.org/project/hdbscan,2022-02-08 15:45:27.000,150.0,359817.0,374839.0,https://anaconda.org/conda-forge/hdbscan,2022-02-10 13:34:49.848,1006517.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +240,textacy,chartbeat-labs/textacy,nlp,,https://github.com/chartbeat-labs/textacy,https://github.com/chartbeat-labs/textacy,Apache-2.0,2016-02-03 16:52:45.000,2022-02-06 16:50:51.205000,2021-12-06 14:45:21,1714.0,101.0,232,91.0,108.0,27.0,220.0,1876,"NLP, before and after spaCy.",31.0,31,True,2021-12-06 15:00:07.000,0.12.0,31.0,textacy,conda-forge/textacy,,,,100.0,,https://pypi.org/project/textacy,2021-12-06 15:00:07.000,100.0,45452.0,47253.0,https://anaconda.org/conda-forge/textacy,2022-02-06 16:50:51.205,102670.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +241,category_encoders,scikit-learn-contrib/category_encoders,sklearn-utils,,https://github.com/scikit-learn-contrib/category_encoders,https://github.com/scikit-learn-contrib/category_encoders,BSD-3-Clause,2015-11-29 19:32:37.000,2022-02-06 22:32:31.000000,2021-11-16 22:47:58,740.0,1.0,338,39.0,105.0,78.0,162.0,1821,A library of sklearn compatible categorical variable encoders.,48.0,31,True,2021-10-13 15:40:27.000,2.3.0-rerelease,19.0,category_encoders,conda-forge/category_encoders,,,['sklearn'],3024.0,3001.0,https://pypi.org/project/category_encoders,2018-10-14 14:15:54.000,23.0,1178204.0,1180316.0,https://anaconda.org/conda-forge/category_encoders,2021-10-13 18:33:34.503,141512.0,,,,,2.0,,,,,,,,,-2.0,,,,,,,,,,,, +242,Pillow-SIMD,uploadcare/pillow-simd,image,,https://github.com/uploadcare/pillow-simd,https://github.com/uploadcare/pillow-simd,PIL,2014-11-12 15:33:02.000,2022-02-10 12:15:14.000000,2022-01-17 10:12:52,12562.0,271.0,77,40.0,41.0,9.0,63.0,1737,The friendly PIL fork.,384.0,31,False,2022-01-02 09:51:23.000,9.0.0,47.0,pillow-simd,,,,,49.0,,https://pypi.org/project/pillow-simd,2022-01-04 16:11:51.000,49.0,53753.0,53753.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +243,Pythran,serge-sans-paille/pythran,others,,https://github.com/serge-sans-paille/pythran,https://github.com/serge-sans-paille/pythran,BSD-3-Clause,2012-05-29 08:02:14.000,2022-02-10 14:28:43.000000,2022-02-01 11:14:03,3500.0,33.0,166,53.0,1227.0,113.0,632.0,1683,Ahead of Time compiler for numeric kernels.,64.0,31,True,2021-12-14 08:16:44.000,0.11.0,52.0,pythran,conda-forge/pythran,,,,118.0,104.0,https://pypi.org/project/pythran,2021-12-14 08:16:44.000,14.0,348902.0,353716.0,https://anaconda.org/conda-forge/pythran,2021-12-14 10:56:04.258,216647.0,,,,,2.0,,,,,,,,,,,,,,,,,,pythran,python-pythran,, +244,jellyfish,jamesturk/jellyfish,nlp,,https://github.com/jamesturk/jellyfish,https://github.com/jamesturk/jellyfish,BSD-2-Clause,2010-07-09 20:41:11.000,2022-01-09 18:22:30.772000,2022-01-07 20:13:06,422.0,14.0,148,42.0,51.0,9.0,99.0,1610,a python library for doing approximate and phonetic matching of strings.,25.0,31,True,2022-01-07 20:20:43.000,0.9.0,32.0,jellyfish,conda-forge/jellyfish,,,,3629.0,3231.0,https://pypi.org/project/jellyfish,2022-01-07 20:20:43.000,398.0,1849697.0,1852322.0,https://anaconda.org/conda-forge/jellyfish,2022-01-09 18:22:30.772,170651.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +245,GPflow,GPflow/GPflow,probabilistics,,https://github.com/GPflow/GPflow,https://github.com/GPflow/GPflow,Apache-2.0,2016-01-14 11:29:24.000,2022-02-10 09:35:41.000000,2022-02-10 09:33:16,2272.0,24.0,415,77.0,1037.0,125.0,624.0,1586,Gaussian processes in TensorFlow.,76.0,31,True,2022-01-20 11:46:07.000,2.3.1,33.0,gpflow,conda-forge/gpflow,,,['tensorflow'],352.0,324.0,https://pypi.org/project/gpflow,2022-01-20 11:46:07.000,28.0,8517.0,8740.0,https://anaconda.org/conda-forge/gpflow,2022-02-06 12:16:39.296,10065.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +246,mleap,combust/mleap,data-pipelines,,https://github.com/combust/mleap,https://github.com/combust/mleap,Apache-2.0,2016-08-23 03:51:03.000,2022-02-08 21:36:57.000000,2022-01-27 12:35:32,981.0,32.0,290,74.0,367.0,90.0,351.0,1354,MLeap: Deploy ML Pipelines to Production.,71.0,31,True,2022-01-12 10:21:57.000,0.19.0,9.0,mleap,conda-forge/mleap,,,,201.0,176.0,https://pypi.org/project/mleap,2022-01-12 10:21:57.000,25.0,202708.0,203979.0,https://anaconda.org/conda-forge/mleap,2022-01-12 12:53:12.772,43247.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +247,Model Analysis,tensorflow/model-analysis,interpretability,,https://github.com/tensorflow/model-analysis,https://github.com/tensorflow/model-analysis,Apache-2.0,2018-03-23 19:08:49.000,2022-02-09 19:27:06.000000,2022-02-09 19:27:04,1105.0,41.0,244,70.0,88.0,27.0,47.0,1141,Model analysis tools for TensorFlow.,37.0,31,True,2022-01-24 17:50:57.000,0.37.0,47.0,tensorflow-model-analysis,,,,"['tensorflow', 'jupyter']",21.0,,https://pypi.org/project/tensorflow-model-analysis,2022-01-24 18:05:57.000,21.0,5363121.0,5363121.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +248,pmdarima,alkaline-ml/pmdarima,time-series-data,,https://github.com/alkaline-ml/pmdarima,https://github.com/alkaline-ml/pmdarima,MIT,2017-03-30 14:58:30.000,2022-01-24 06:23:07.000000,2022-01-04 15:25:50,1046.0,4.0,194,33.0,213.0,24.0,242.0,1119,"A statistical library designed to fill the void in Pythons time series analysis capabilities, including the equivalent..",19.0,31,True,2021-11-05 12:39:58.000,1.8.4,36.0,pmdarima,conda-forge/pmdarima,,,,1776.0,1732.0,https://pypi.org/project/pmdarima,2021-11-05 12:39:58.000,44.0,998535.0,1000370.0,https://anaconda.org/conda-forge/pmdarima,2021-11-15 19:38:27.612,29365.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +249,FiftyOne,voxel51/fiftyone,data-viz,,https://github.com/voxel51/fiftyone,https://github.com/voxel51/fiftyone,Apache-2.0,2020-04-22 13:43:28.000,2022-02-07 22:14:35.000000,2022-02-07 16:39:17,12471.0,486.0,125,22.0,932.0,212.0,465.0,984,"Visualize, create, and debug image and video datasets and model predictions.",25.0,31,True,2022-02-07 18:47:35.000,0.14.4,67.0,fiftyone,,,,"['tensorflow', 'pytorch', 'jupyter']",81.0,80.0,https://pypi.org/project/fiftyone,2022-02-07 18:47:35.000,1.0,22121.0,22121.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +250,petl,petl-developers/petl,data-pipelines,,https://github.com/petl-developers/petl,https://github.com/petl-developers/petl,MIT,2011-08-19 09:51:03.000,2022-02-08 23:00:59.000000,2022-02-08 22:19:56,1226.0,72.0,172,48.0,179.0,73.0,365.0,967,Python Extract Transform and Load Tables of Data.,54.0,31,True,2022-02-08 23:00:01.000,1.7.8,83.0,petl,conda-forge/petl,,http://petl.readthedocs.org,,696.0,622.0,https://pypi.org/project/petl,2022-02-08 23:00:59.000,74.0,55589.0,56664.0,https://anaconda.org/conda-forge/petl,2022-02-05 02:56:55.882,69888.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +251,TensorFlow Text,tensorflow/text,nlp,,https://github.com/tensorflow/text,https://github.com/tensorflow/text,Apache-2.0,2019-05-29 22:10:03.000,2022-02-10 12:43:54.000000,2022-02-06 21:31:31,596.0,39.0,180,39.0,683.0,69.0,123.0,889,Making text a first-class citizen in TensorFlow.,73.0,31,True,2022-02-04 11:02:37.000,2.8.1,46.0,tensorflow-text,,,,['tensorflow'],1488.0,1419.0,https://pypi.org/project/tensorflow-text,2022-02-04 10:33:22.000,69.0,1994725.0,1994725.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +252,metrics,PyTorchLightning/metrics,distributed-ml,,https://github.com/PyTorchLightning/metrics,https://github.com/PyTorchLightning/metrics,Apache-2.0,2020-12-22 20:02:42.000,2022-02-10 14:17:42.000000,2022-02-10 13:30:42,676.0,145.0,149,21.0,462.0,65.0,240.0,667,"Machine learning metrics for distributed, scalable PyTorch applications.",115.0,31,True,2022-02-03 20:42:24.000,0.7.1,15.0,metrics,conda-forge/torchmetrics,,,['pytorch'],1840.0,1826.0,https://pypi.org/project/metrics,2018-04-28 10:58:56.000,14.0,2670.0,27793.0,https://anaconda.org/conda-forge/torchmetrics,2022-02-04 00:12:34.443,275936.0,,,,,2.0,428.0,,,,,,,,,,,,,,,,,,,, +253,baselines,openai/baselines,reinforcement-learning,,https://github.com/openai/baselines,https://github.com/openai/baselines,MIT,2017-05-24 01:58:13.000,2021-12-03 07:10:56.000000,2020-01-31 13:06:18,347.0,,4144,577.0,367.0,472.0,430.0,12314,OpenAI Baselines: high-quality implementations of reinforcement learning algorithms.,114.0,30,False,2018-02-26 17:07:07.000,0.1.5,6.0,baselines,,,,,406.0,367.0,https://pypi.org/project/baselines,2018-02-26 17:07:07.000,39.0,1160.0,1160.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +254,Dopamine,google/dopamine,reinforcement-learning,,https://github.com/google/dopamine,https://github.com/google/dopamine,Apache-2.0,2018-07-26 09:58:36.000,2021-12-14 17:59:05.000000,2021-12-14 17:59:04,282.0,6.0,1301,447.0,40.0,80.0,82.0,9724,Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.,14.0,30,True,2021-12-13 23:17:39.000,4.0.2,42.0,dopamine-rl,,,,['tensorflow'],37.0,,https://pypi.org/project/dopamine-rl,2021-12-13 23:17:39.000,37.0,602304.0,602304.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +255,Sonnet,deepmind/sonnet,ml-frameworks,,https://github.com/deepmind/sonnet,https://github.com/deepmind/sonnet,Apache-2.0,2017-04-03 11:34:35.000,2022-02-10 00:16:31.000000,2022-02-01 18:28:37,847.0,4.0,1281,437.0,64.0,22.0,147.0,9190,TensorFlow-based neural network library.,53.0,30,True,2020-03-27 10:36:19.000,2.0.0,27.0,dm-sonnet,conda-forge/sonnet,,,['tensorflow'],816.0,764.0,https://pypi.org/project/dm-sonnet,2020-03-27 10:36:10.000,52.0,22552.0,23026.0,https://anaconda.org/conda-forge/sonnet,2020-11-14 18:13:23.843,12822.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +256,Vaex,vaexio/vaex,data-containers,,https://github.com/vaexio/vaex,https://github.com/vaexio/vaex,MIT,2014-09-27 09:44:42.000,2022-02-09 20:07:29.000000,2022-02-09 18:39:51,3423.0,135.0,534,142.0,829.0,361.0,638.0,6905,"Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a..",63.0,30,True,2022-02-07 15:14:31.000,4.8.0,58.0,vaex,conda-forge/vaex,,,,16.0,,https://pypi.org/project/vaex,2022-02-07 15:14:31.000,16.0,26307.0,28202.0,https://anaconda.org/conda-forge/vaex,2021-12-30 12:48:14.043,121154.0,,,,,3.0,226.0,,,,,,,,,,,,,,,,,,,, +257,imageai,OlafenwaMoses/ImageAI,image,,https://github.com/OlafenwaMoses/ImageAI,https://github.com/OlafenwaMoses/ImageAI,MIT,2018-03-19 23:12:33.000,2022-02-10 01:20:44.000000,2021-05-08 20:05:36,292.0,,1874,276.0,66.0,250.0,426.0,6818,A python library built to empower developers to build applications and systems with self-contained Computer Vision..,15.0,30,True,2021-01-05 01:26:01.000,2.1.6,10.0,imageai,conda-forge/imageai,,,,1054.0,1038.0,https://pypi.org/project/imageai,2021-01-05 01:26:01.000,16.0,7917.0,23429.0,https://anaconda.org/conda-forge/imageai,2021-04-30 19:03:25.297,2360.0,,,,,2.0,707869.0,,,,,,,,,,,,,,,,,,,, +258,PaddleDetection,PaddlePaddle/PaddleDetection,image,,https://github.com/PaddlePaddle/PaddleDetection,https://github.com/PaddlePaddle/PaddleDetection,Apache-2.0,2019-10-25 07:21:14.000,2022-02-10 12:41:52.000000,2022-02-10 11:26:36,1318.0,66.0,1584,153.0,2238.0,909.0,2049.0,6312,"Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object..",80.0,30,True,2021-12-09 11:11:05.000,2.3.0,6.0,paddledet,,,,['paddle'],8.0,8.0,https://pypi.org/project/paddledet,2021-11-26 08:48:44.000,,308.0,308.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +259,OCRmyPDF,ocrmypdf/OCRmyPDF,ocr,,https://github.com/ocrmypdf/OCRmyPDF,https://github.com/ocrmypdf/OCRmyPDF,MPL-2.0,2013-12-20 08:26:28.000,2022-02-08 08:46:27.000000,2022-02-08 08:46:26,3159.0,83.0,535,118.0,102.0,87.0,725.0,5900,"OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them to be searched.",61.0,30,True,2022-01-26 21:13:25.000,13.3.0,191.0,ocrmypdf,conda-forge/ocrmypdf,,,,12.0,,https://pypi.org/project/ocrmypdf,2022-01-26 21:13:25.000,12.0,23369.0,24059.0,https://anaconda.org/conda-forge/ocrmypdf,2022-01-26 23:49:36.723,8282.0,,,,,2.0,,,,,,,,,,ocrmypdf,ocrmypdf,,,,,,,,,, +260,DeepPavlov,deepmipt/DeepPavlov,nlp,,https://github.com/deepmipt/DeepPavlov,https://github.com/deepmipt/DeepPavlov,Apache-2.0,2017-11-17 14:35:29.000,2022-02-07 18:47:45.000000,2021-12-16 19:43:39,2611.0,2.0,990,213.0,920.0,116.0,503.0,5592,An open source library for deep learning end-to-end dialog systems and chatbots.,67.0,30,True,2021-12-16 19:47:39.000,0.17.2,47.0,deeppavlov,,,,['tensorflow'],250.0,244.0,https://pypi.org/project/deeppavlov,2021-12-16 19:47:39.000,6.0,9535.0,9535.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +261,CleverHans,cleverhans-lab/cleverhans,adversarial,,https://github.com/cleverhans-lab/cleverhans,https://github.com/cleverhans-lab/cleverhans,MIT,2016-09-15 00:28:04.000,2022-01-23 02:08:30.000000,2021-09-23 22:14:27,3201.0,,1304,187.0,780.0,25.0,422.0,5399,"An adversarial example library for constructing attacks, building defenses, and benchmarking both.",128.0,30,True,2021-07-24 08:53:21.000,4.0.0,8.0,cleverhans,conda-forge/cleverhans,,,['tensorflow'],305.0,294.0,https://pypi.org/project/cleverhans,2021-07-24 08:53:21.000,11.0,1076.0,1202.0,https://anaconda.org/conda-forge/cleverhans,2021-07-29 12:49:41.903,2529.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +262,pyAudioAnalysis,tyiannak/pyAudioAnalysis,audio,,https://github.com/tyiannak/pyAudioAnalysis,https://github.com/tyiannak/pyAudioAnalysis,Apache-2.0,2014-08-27 12:43:13.000,2022-02-09 19:42:05.000000,2022-02-09 19:41:47,765.0,42.0,1069,206.0,86.0,176.0,117.0,4601,"Python Audio Analysis Library: Feature Extraction, Classification, Segmentation and Applications.",26.0,30,True,2022-02-07 22:36:53.000,0.3.14,23.0,pyAudioAnalysis,,,,,269.0,250.0,https://pypi.org/project/pyAudioAnalysis,2022-02-07 22:36:53.000,19.0,11452.0,11452.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +263,cuDF,rapidsai/cudf,gpu-utilities,,https://github.com/rapidsai/cudf,https://github.com/rapidsai/cudf,Apache-2.0,2017-05-07 03:43:37.000,2022-02-10 14:31:19.000000,2022-02-10 14:31:08,34691.0,366.0,586,142.0,5914.0,707.0,3686.0,4486,cuDF - GPU DataFrame Library.,229.0,30,True,2022-02-02 16:43:03.000,22.02.00,22.0,cudf,,,,,3.0,,https://pypi.org/project/cudf,2020-06-01 20:07:47.000,3.0,995.0,995.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +264,Activeloop,activeloopai/Hub,data-pipelines,,https://github.com/activeloopai/Hub,https://github.com/activeloopai/Hub,MPL-2.0,2019-08-09 06:17:59.000,2022-02-10 14:12:50.000000,2022-02-09 16:32:06,5135.0,184.0,350,61.0,1136.0,68.0,274.0,4256,"Dataset format for AI. Build, manage, & visualize datasets for deep learning. Stream data real-time to..",91.0,30,True,2022-02-01 17:13:34.000,2.2.3,124.0,hub,,,,,52.0,,https://pypi.org/project/hub,2022-02-01 17:09:05.000,52.0,3182.0,3182.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +265,pyfolio,quantopian/pyfolio,financial-data,,https://github.com/quantopian/pyfolio,https://github.com/quantopian/pyfolio,Apache-2.0,2015-06-01 15:31:39.000,2021-12-26 17:08:51.000000,2020-07-15 13:46:58,1184.0,,1302,306.0,290.0,134.0,265.0,4251,Portfolio and risk analytics in Python.,55.0,30,False,2019-04-15 15:00:21.000,0.9.2,22.0,pyfolio,conda-forge/pyfolio,,,,397.0,365.0,https://pypi.org/project/pyfolio,2019-04-15 15:00:21.000,32.0,5997.0,6162.0,https://anaconda.org/conda-forge/pyfolio,2020-05-16 14:11:57.267,7964.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +266,imutils,PyImageSearch/imutils,image,,https://github.com/PyImageSearch/imutils,https://github.com/PyImageSearch/imutils,MIT,2015-01-11 20:05:39.000,2022-01-27 13:24:16.000000,2022-01-27 13:24:16,139.0,1.0,937,149.0,104.0,146.0,76.0,3967,"A series of convenience functions to make basic image processing operations such as translation, rotation, resizing,..",21.0,30,True,2021-01-15 10:53:17.000,0.5.4,29.0,imutils,conda-forge/imutils,,,,23358.0,22603.0,https://pypi.org/project/imutils,2021-01-15 10:53:17.000,755.0,308196.0,310572.0,https://anaconda.org/conda-forge/imutils,2021-12-09 01:25:49.387,76042.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +267,NeMo,NVIDIA/NeMo,nlp,,https://github.com/NVIDIA/NeMo,https://github.com/NVIDIA/NeMo,Apache-2.0,2019-08-05 20:16:42.000,2022-02-10 13:39:07.000000,2022-02-09 15:58:52,4167.0,229.0,846,130.0,2479.0,72.0,899.0,3864,NeMo: a toolkit for conversational AI.,128.0,30,True,2022-02-05 06:09:02.000,1.6.2,49.0,nemo-toolkit,,,,['pytorch'],7.0,,https://pypi.org/project/nemo-toolkit,2022-02-05 06:11:26.000,7.0,11945.0,12083.0,,,,,,,,2.0,4013.0,,,,,,,,,,,,,,,,,,,, +268,huey,coleifer/huey,data-pipelines,,https://github.com/coleifer/huey,https://github.com/coleifer/huey,MIT,2011-11-03 16:39:43.000,2022-01-10 17:30:34.000000,2022-01-10 17:30:10,934.0,7.0,329,82.0,159.0,,491.0,3818,a little task queue for python.,66.0,30,True,2021-12-28 18:36:38.000,2.4.3,64.0,huey,conda-forge/huey,,,,1019.0,859.0,https://pypi.org/project/huey,2021-12-28 18:36:38.000,160.0,58947.0,59445.0,https://anaconda.org/conda-forge/huey,2019-10-16 15:34:27.487,22928.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +269,River,online-ml/river,others,,https://github.com/online-ml/river,https://github.com/online-ml/river,BSD-3-Clause,2019-01-24 15:18:26.000,2022-02-09 12:25:57.000000,2022-02-09 12:22:54,3258.0,58.0,336,79.0,283.0,6.0,333.0,3156,Online machine learning in Python.,72.0,30,True,2022-02-04 15:14:56.000,0.10.0,6.0,river,conda-forge/river,,,,79.0,73.0,https://pypi.org/project/river,2022-02-04 15:29:10.000,6.0,5763.0,6423.0,https://anaconda.org/conda-forge/river,2021-12-09 16:10:41.029,6603.0,,,,,2.0,,,,,,,,,5.0,,,,,,,,,,,, +270,plotnine,has2k1/plotnine,data-viz,,https://github.com/has2k1/plotnine,https://github.com/has2k1/plotnine,GPL-2.0,2017-04-24 19:00:44.000,2022-01-20 13:07:25.000000,2022-01-07 11:52:10,1713.0,9.0,152,65.0,95.0,80.0,384.0,2944,A grammar of graphics for Python.,89.0,30,False,2021-03-25 12:57:10.000,0.8.0,11.0,plotnine,conda-forge/plotnine,,,,3123.0,2930.0,https://pypi.org/project/plotnine,2021-03-25 10:49:20.000,193.0,206616.0,209188.0,https://anaconda.org/conda-forge/plotnine,2021-03-25 12:31:04.423,146657.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +271,nlpaug,makcedward/nlpaug,nlp,,https://github.com/makcedward/nlpaug,https://github.com/makcedward/nlpaug,MIT,2019-03-21 03:00:17.000,2022-01-04 22:17:45.000000,2022-01-04 22:17:09,710.0,43.0,326,36.0,107.0,27.0,139.0,2916,Data augmentation for NLP.,26.0,30,True,2021-12-25 02:49:58.000,1.1.10,36.0,nlpaug,conda-forge/nlpaug,,,,262.0,248.0,https://pypi.org/project/nlpaug,2021-12-23 17:35:56.000,14.0,40973.0,41128.0,https://anaconda.org/conda-forge/nlpaug,2021-12-25 16:31:39.772,1245.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +272,pomegranate,jmschrei/pomegranate,probabilistics,,https://github.com/jmschrei/pomegranate,https://github.com/jmschrei/pomegranate,MIT,2014-11-24 18:36:58.000,2022-02-07 03:46:26.000000,2022-02-06 20:36:39,931.0,17.0,508,102.0,315.0,59.0,608.0,2828,"Fast, flexible and easy to use probabilistic modelling in Python.",65.0,30,True,2021-11-19 21:46:05.000,0.14.7,67.0,pomegranate,conda-forge/pomegranate,,,,673.0,629.0,https://pypi.org/project/pomegranate,2021-11-19 21:46:05.000,44.0,39993.0,42553.0,https://anaconda.org/conda-forge/pomegranate,2021-11-16 01:22:35.020,79386.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +273,datashader,holoviz/datashader,data-viz,,https://github.com/holoviz/datashader,https://github.com/holoviz/datashader,BSD-3-Clause,2015-12-23 18:02:20.000,2022-02-09 20:59:49.000000,2022-02-08 20:24:37,1301.0,4.0,329,89.0,554.0,130.0,355.0,2703,Quickly and accurately render even the largest data.,45.0,30,True,2021-06-09 23:30:20.000,0.13.0,24.0,datashader,conda-forge/datashader,,,,1027.0,953.0,https://pypi.org/project/datashader,2021-06-09 22:59:52.000,74.0,46327.0,51430.0,https://anaconda.org/conda-forge/datashader,2021-06-10 09:04:19.929,260280.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +274,Arctic,man-group/arctic,data-containers,,https://github.com/man-group/arctic,https://github.com/man-group/arctic,LGPL-2.1,2015-05-29 13:37:30.000,2022-02-10 10:22:22.000000,2022-02-10 10:22:22,1110.0,25.0,522,172.0,429.0,96.0,443.0,2592,Arctic is a high performance datastore for numeric data.,75.0,30,True,2022-01-24 17:37:17.000,1.80.4,89.0,arctic,conda-forge/arctic,,,,183.0,149.0,https://pypi.org/project/arctic,2022-01-24 17:37:17.000,34.0,9155.0,9683.0,https://anaconda.org/conda-forge/arctic,2019-12-16 08:57:24.231,17383.0,,,,,3.0,181.0,,,,,,,,,,,,,,,,,,,, +275,Neural Network Libraries,sony/nnabla,ml-frameworks,,https://github.com/sony/nnabla,https://github.com/sony/nnabla,Apache-2.0,2017-06-26 01:07:10.000,2022-02-10 02:36:22.000000,2022-01-26 00:02:46,2971.0,71.0,313,164.0,962.0,32.0,45.0,2517,Neural Network Libraries.,64.0,30,True,2022-01-26 00:19:08.000,1.25.0,62.0,nnabla,,,,,51.0,,https://pypi.org/project/nnabla,2022-01-26 00:05:16.000,51.0,4577.0,4586.0,,,,,,,,3.0,533.0,,,,,,,,,,,,,,,,,,,, +276,Cufflinks,santosjorge/cufflinks,data-viz,,https://github.com/santosjorge/cufflinks,https://github.com/santosjorge/cufflinks,MIT,2014-11-19 20:59:33.000,2022-01-27 10:30:57.000000,2021-02-25 05:05:09,452.0,,585,105.0,72.0,92.0,123.0,2491,Productivity Tools for Plotly + Pandas.,38.0,30,True,2020-03-01 17:42:01.000,0.17.3,28.0,cufflinks,,,,['pandas'],5324.0,5166.0,https://pypi.org/project/cufflinks,2021-12-15 15:49:58.297,158.0,281366.0,281366.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +277,TorchServe,pytorch/serve,model-serialisation,,https://github.com/pytorch/serve,https://github.com/pytorch/serve,Apache-2.0,2019-10-03 03:17:43.000,2022-02-10 10:57:18.000000,2022-02-10 01:54:13,2586.0,248.0,448,47.0,662.0,128.0,664.0,2420,Model Serving on PyTorch.,95.0,30,True,2021-12-29 21:45:21.000,0.5.2,13.0,torchserve,pytorch/torchserve,pytorch/torchserve,,['pytorch'],8.0,,https://pypi.org/project/torchserve,2021-12-29 21:04:22.000,8.0,11477.0,46889.0,https://anaconda.org/pytorch/torchserve,2021-12-29 21:04:49.234,18712.0,https://hub.docker.com/r/pytorch/torchserve,2021-12-29 21:11:42.894442,11.0,966552.0,2.0,951.0,,,,,,,,,,,,,,,,,,,, +278,ImageHash,JohannesBuchner/imagehash,image,,https://github.com/JohannesBuchner/imagehash,https://github.com/JohannesBuchner/imagehash,BSD-2-Clause,2013-03-02 23:32:48.000,2022-01-04 14:27:58.000000,2021-09-07 19:15:32,209.0,,283,67.0,52.0,13.0,93.0,2263,A Python Perceptual Image Hashing Module.,20.0,30,True,2021-07-15 12:35:01.000,4.2.1,18.0,ImageHash,conda-forge/imagehash,,,,4547.0,4232.0,https://pypi.org/project/ImageHash,2021-07-15 12:35:01.000,315.0,1356389.0,1359022.0,https://anaconda.org/conda-forge/imagehash,2021-07-15 15:00:27.543,165905.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +279,tslearn,tslearn-team/tslearn,time-series-data,,https://github.com/tslearn-team/tslearn,https://github.com/tslearn-team/tslearn,BSD-2-Clause,2017-05-04 13:08:13.000,2022-02-09 16:42:55.000000,2021-12-06 15:56:44,1581.0,5.0,255,56.0,128.0,73.0,178.0,2008,A machine learning toolkit dedicated to time-series data.,36.0,30,True,2021-08-16 07:09:52.000,0.5.2,94.0,tslearn,conda-forge/tslearn,,,['sklearn'],418.0,399.0,https://pypi.org/project/tslearn,2021-08-16 07:29:50.000,19.0,102366.0,107612.0,https://anaconda.org/conda-forge/tslearn,2022-01-15 08:48:51.564,246566.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +280,hnswlib,nmslib/hnswlib,nn-search,,https://github.com/nmslib/hnswlib,https://github.com/nmslib/hnswlib,Apache-2.0,2017-07-06 13:08:46.000,2022-02-07 01:26:28.000000,2022-02-06 22:39:24,370.0,30.0,355,61.0,141.0,123.0,120.0,1875,Header-only C++/python library for fast approximate nearest neighbors.,54.0,30,True,2022-02-07 01:26:28.000,0.6.1,8.0,hnswlib,conda-forge/hnswlib,,,,210.0,190.0,https://pypi.org/project/hnswlib,2022-02-07 01:26:28.000,20.0,66996.0,69501.0,https://anaconda.org/conda-forge/hnswlib,2021-02-04 20:34:56.456,35083.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +281,TextAttack,QData/TextAttack,adversarial,,https://github.com/QData/TextAttack,https://github.com/QData/TextAttack,MIT,2019-10-15 00:51:44.000,2022-02-10 06:14:42.000000,2021-12-16 02:24:09,2403.0,22.0,219,30.0,428.0,39.0,152.0,1839,"TextAttack is a Python framework for adversarial attacks, data augmentation, and model training in NLP..",46.0,30,True,2021-11-10 01:36:28.000,0.3.4,42.0,textattack,conda-forge/textattack,,,,65.0,62.0,https://pypi.org/project/textattack,2021-11-10 01:36:28.000,3.0,10897.0,11046.0,https://anaconda.org/conda-forge/textattack,2021-06-29 21:16:15.345,2538.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +282,TFX,tensorflow/tfx,data-pipelines,,https://github.com/tensorflow/tfx,https://github.com/tensorflow/tfx,Apache-2.0,2019-02-04 17:14:36.000,2022-02-10 10:30:36.000000,2022-02-10 10:30:30,4083.0,114.0,522,91.0,3944.0,249.0,488.0,1694,TFX is an end-to-end platform for deploying production ML pipelines.,127.0,30,True,2022-02-08 22:39:24.000,1.6.1,72.0,tfx,,,,['tensorflow'],7.0,,https://pypi.org/project/tfx,2022-02-08 22:39:24.000,7.0,307131.0,307131.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +283,datasketch,ekzhu/datasketch,data-containers,,https://github.com/ekzhu/datasketch,https://github.com/ekzhu/datasketch,MIT,2015-03-20 01:21:46.000,2022-02-04 09:05:43.000000,2022-02-04 08:52:34,205.0,10.0,234,51.0,48.0,29.0,99.0,1656,"MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog, HyperLogLog++, LSH Ensemble.",21.0,30,True,2022-02-04 09:05:43.000,1.5.7,79.0,datasketch,,,,,400.0,346.0,https://pypi.org/project/datasketch,2022-02-04 09:04:49.000,54.0,420523.0,420523.0,,,,,,,,3.0,19.0,,,,,,,,,,,,,,,,,,,, +284,FairScale,facebookresearch/fairscale,distributed-ml,,https://github.com/facebookresearch/fairscale,https://github.com/facebookresearch/fairscale,BSD-3-Clause,2020-07-07 19:02:01.000,2022-02-09 23:15:48.000000,2022-02-08 21:38:48,587.0,44.0,147,36.0,659.0,59.0,209.0,1604,PyTorch extensions for high performance and large scale training.,54.0,30,True,2022-01-14 20:24:58.000,0.4.5,27.0,fairscale,conda-forge/fairscale,,,['pytorch'],178.0,165.0,https://pypi.org/project/fairscale,2022-01-14 20:24:56.000,13.0,59175.0,60765.0,https://anaconda.org/conda-forge/fairscale,2022-02-05 10:19:33.275,4772.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +285,pyLDAvis,bmabey/pyLDAvis,interpretability,,https://github.com/bmabey/pyLDAvis,https://github.com/bmabey/pyLDAvis,BSD-3-Clause,2015-04-09 22:48:03.000,2022-02-01 14:45:02.000000,2021-03-24 13:03:31,240.0,,320,56.0,64.0,86.0,77.0,1567,Python library for interactive topic model visualization. Port of the R LDAvis package.,32.0,30,True,2021-03-24 13:05:21.000,3.3.1,24.0,pyldavis,conda-forge/pyldavis,,,['jupyter'],3199.0,3069.0,https://pypi.org/project/pyldavis,2021-03-24 12:57:08.000,130.0,609470.0,610233.0,https://anaconda.org/conda-forge/pyldavis,2021-03-24 15:17:07.309,33602.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +286,PyCUDA,inducer/pycuda,gpu-utilities,,https://github.com/inducer/pycuda,https://github.com/inducer/pycuda,MIT,2011-04-06 02:53:31.000,2022-01-15 14:07:57.000000,2022-01-11 14:17:08,1513.0,5.0,246,54.0,117.0,65.0,155.0,1267,"CUDA integration for Python, plus shiny features.",74.0,30,True,2019-08-12 04:15:37.000,2019.1.2,47.0,pycuda,conda-forge/pycuda,,,,1346.0,1156.0,https://pypi.org/project/pycuda,2021-04-03 22:28:54.000,190.0,31796.0,36822.0,https://anaconda.org/conda-forge/pycuda,2021-11-06 22:00:35.210,55288.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +287,ArcGIS API,Esri/arcgis-python-api,geospatial-data,,https://github.com/Esri/arcgis-python-api,https://github.com/Esri/arcgis-python-api,Apache-2.0,2016-03-16 01:09:14.000,2022-02-10 09:27:44.000000,2022-02-01 23:45:13,3388.0,84.0,866,140.0,777.0,123.0,292.0,1218,Documentation and samples for ArcGIS API for Python.,77.0,30,True,2022-02-02 00:09:26.000,2.0.0,32.0,arcgis,,esridocker/arcgis-api-python-notebook,,,22.0,,https://pypi.org/project/arcgis,2022-02-03 03:33:19.000,22.0,48212.0,48320.0,,,,https://hub.docker.com/r/esridocker/arcgis-api-python-notebook,2022-02-04 23:58:53.044266,33.0,5860.0,3.0,1747.0,,,,,,,,,,,,,,,,,,,, +288,tensorly,tensorly/tensorly,others,,https://github.com/tensorly/tensorly,https://github.com/tensorly/tensorly,BSD-2-Clause,2016-10-21 23:14:52.000,2022-02-09 17:05:36.000000,2022-01-24 05:01:10,1340.0,33.0,224,38.0,182.0,45.0,131.0,1178,TensorLy: Tensor Learning in Python.,49.0,30,True,2021-11-08 13:38:03.000,0.7.0,18.0,tensorly,conda-forge/tensorly,,,,249.0,219.0,https://pypi.org/project/tensorly,2021-11-08 13:38:03.000,30.0,5641.0,10157.0,https://anaconda.org/conda-forge/tensorly,2021-12-09 16:07:42.501,203236.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +289,PennyLane,PennyLaneAI/PennyLane,others,,https://github.com/PennyLaneAI/pennylane,https://github.com/PennyLaneAI/pennylane,Apache-2.0,2018-04-17 16:45:42.000,2022-02-10 14:33:57.000000,2022-02-10 02:27:50,2344.0,141.0,344,55.0,1614.0,149.0,468.0,1156,PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum..,89.0,30,True,2022-02-08 07:20:40.000,0.21.0,31.0,pennylane,conda-forge/pennylane,,,,28.0,,https://pypi.org/project/pennylane,2022-02-08 07:20:40.000,28.0,11471.0,11584.0,https://anaconda.org/conda-forge/pennylane,2021-12-14 10:39:20.290,338.0,,,,,2.0,59.0,,,,,,,,,,,,,,,,,,,, +290,agate,wireservice/agate,others,,https://github.com/wireservice/agate,https://github.com/wireservice/agate,MIT,2014-04-25 13:59:09.000,2021-12-15 16:39:08.973000,2021-07-15 17:22:49,1466.0,,134,42.0,124.0,54.0,630.0,1082,A Python data analysis library that is optimized for humans instead of machines.,49.0,30,True,2021-07-15 16:32:29.000,1.6.3,26.0,agate,conda-forge/agate,,,,896.0,763.0,https://pypi.org/project/agate,2021-07-15 16:32:29.000,133.0,1084065.0,1085339.0,https://anaconda.org/conda-forge/agate,2021-07-16 07:46:42.405,76499.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +291,Keras-Preprocessing,keras-team/keras-preprocessing,tensorflow-utils,,https://github.com/keras-team/keras-preprocessing,https://github.com/keras-team/keras-preprocessing,MIT,2018-05-30 22:43:36.000,2022-02-07 17:40:36.000000,2021-02-04 19:43:30,284.0,,437,44.0,175.0,93.0,100.0,1011,"Utilities for working with image data, text data, and sequence data.",50.0,30,True,2020-05-14 03:53:47.000,1.1.2,12.0,keras-preprocessing,conda-forge/keras-preprocessing,,,['tensorflow'],1481.0,,https://pypi.org/project/keras-preprocessing,2020-05-14 03:53:47.000,1481.0,8824071.0,8851166.0,https://anaconda.org/conda-forge/keras-preprocessing,2021-01-15 12:28:58.923,1192209.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +292,igraph,igraph/python-igraph,graph,,https://github.com/igraph/python-igraph,https://github.com/igraph/python-igraph,GPL-2.0,2015-01-08 23:55:16.000,2022-02-06 21:40:28.000000,2022-02-06 21:37:48,1862.0,40.0,211,35.0,130.0,37.0,338.0,927,Python interface for igraph.,56.0,30,False,2022-01-10 14:51:15.000,0.9.9,27.0,python-igraph,conda-forge/igraph,,,,829.0,459.0,https://pypi.org/project/python-igraph,2022-01-10 14:51:15.000,370.0,257230.0,267039.0,https://anaconda.org/conda-forge/igraph,2022-01-11 11:59:41.931,268443.0,,,,,1.0,335409.0,,,,,,,,,,,,,,,,,,,, +293,pyopencl,inducer/pyopencl,others,,https://github.com/inducer/pyopencl,https://github.com/inducer/pyopencl,MIT,2011-04-06 02:51:33.000,2022-01-19 07:52:32.759000,2022-01-17 04:41:32,3047.0,13.0,219,48.0,235.0,67.0,234.0,872,"OpenCL integration for Python, plus shiny features.",90.0,30,True,2022-01-16 22:25:02.000,2021.2.12,75.0,pyopencl,conda-forge/pyopencl,,,,807.0,627.0,https://pypi.org/project/pyopencl,2022-01-17 04:42:46.000,180.0,26448.0,35128.0,https://anaconda.org/conda-forge/pyopencl,2022-01-19 07:52:32.759,555571.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +294,patsy,pydata/patsy,probabilistics,,https://github.com/pydata/patsy,https://github.com/pydata/patsy,BSD-2-Clause,2012-07-10 12:30:06.000,2021-09-26 16:29:44.000000,2021-09-26 16:29:39,539.0,,94,29.0,52.0,73.0,68.0,812,Describing statistical models in Python using symbolic formulas.,16.0,30,True,2021-09-27 02:10:26.000,0.5.2,9.0,patsy,conda-forge/patsy,,,,49589.0,46943.0,https://pypi.org/project/patsy,2021-09-26 05:26:37.000,2646.0,5471180.0,5534480.0,https://anaconda.org/conda-forge/patsy,2021-09-26 14:43:31.594,4177833.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +295,Satpy,pytroll/satpy,geospatial-data,,https://github.com/pytroll/satpy,https://github.com/pytroll/satpy,GPL-3.0,2016-02-09 20:29:43.000,2022-02-10 06:25:49.000000,2022-02-09 16:13:38,9601.0,412.0,224,31.0,1284.0,363.0,435.0,800,Python package for earth-observing satellite data processing.,120.0,30,False,2021-12-17 18:19:32.000,0.33.1,74.0,satpy,conda-forge/satpy,,,,66.0,58.0,https://pypi.org/project/satpy,2021-12-17 18:19:32.000,8.0,2107.0,3996.0,https://anaconda.org/conda-forge/satpy,2021-12-17 21:16:26.729,81238.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +296,Bottleneck,pydata/bottleneck,data-containers,,https://github.com/pydata/bottleneck,https://github.com/pydata/bottleneck,BSD-2-Clause,2010-11-27 23:21:22.000,2022-02-07 02:25:53.000000,2022-02-07 02:24:57,1242.0,1.0,74,27.0,177.0,37.0,179.0,701,Fast NumPy array functions written in C.,22.0,30,True,2020-02-21 06:22:16.000,1.3.2,21.0,Bottleneck,conda-forge/bottleneck,,,,31832.0,30276.0,https://pypi.org/project/Bottleneck,2020-02-21 06:22:16.000,1556.0,412329.0,439606.0,https://anaconda.org/conda-forge/bottleneck,2021-11-04 11:55:30.352,1882181.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +297,data-validation,tensorflow/data-validation,data-viz,,https://github.com/tensorflow/data-validation,https://github.com/tensorflow/data-validation,Apache-2.0,2018-07-02 15:47:02.000,2022-02-09 04:38:20.000000,2022-02-09 04:38:19,730.0,38.0,113,47.0,65.0,37.0,112.0,599,Library for exploring and validating machine learning data.,23.0,30,True,2022-01-21 02:20:35.000,1.6.0,36.0,tensorflow-data-validation,,,,"['tensorflow', 'jupyter']",406.0,380.0,https://pypi.org/project/tensorflow-data-validation,2022-01-21 02:20:35.000,26.0,7339145.0,7339152.0,,,,,,,,2.0,297.0,,,,,,,,,,,,,,,,,,,, +298,snowballstemmer,snowballstem/snowball,nlp,,https://github.com/snowballstem/snowball,https://github.com/snowballstem/snowball,BSD-3-Clause,2013-02-23 07:17:42.000,2022-02-01 21:28:26.000000,2021-12-17 04:08:52,919.0,2.0,148,32.0,106.0,25.0,44.0,541,Snowball compiler and stemming algorithms.,28.0,30,True,2021-11-16 18:38:34.000,2.2.0,10.0,snowballstemmer,conda-forge/snowballstemmer,,,,6731.0,4.0,https://pypi.org/project/snowballstemmer,2021-11-16 18:38:34.000,6727.0,6224167.0,6281198.0,https://anaconda.org/conda-forge/snowballstemmer,2021-11-17 09:59:16.947,3764061.0,,,,,2.0,,,,,,,,,-2.0,,,,,,,,,,,, +299,TensorFlow I/O,tensorflow/io,tensorflow-utils,,https://github.com/tensorflow/io,https://github.com/tensorflow/io,Apache-2.0,2018-11-09 22:44:05.000,2022-02-10 01:05:43.000000,2022-02-09 21:47:34,1553.0,48.0,216,40.0,1142.0,164.0,328.0,532,"Dataset, streaming, and file system extensions maintained by TensorFlow SIG-IO.",88.0,30,True,2022-02-04 22:19:51.000,0.24.0,31.0,tensorflow-io,,,,['tensorflow'],18.0,,https://pypi.org/project/tensorflow-io,2022-02-04 22:16:58.000,18.0,171102.0,171102.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +300,DIPY,dipy/dipy,medical-data,,https://github.com/dipy/dipy,https://github.com/dipy/dipy,BSD-3-Clause,2010-02-06 11:43:08.000,2022-02-10 10:53:32.000000,2022-02-09 21:08:25,11758.0,28.0,331,50.0,1712.0,123.0,642.0,489,"DIPY is the paragon 3D/4D+ imaging library in Python. Contains generic methods for spatial normalization, signal..",128.0,30,True,2021-05-06 04:40:48.000,1.4.1,23.0,dipy,conda-forge/dipy,,,,574.0,494.0,https://pypi.org/project/dipy,2021-05-06 04:40:48.000,80.0,10737.0,14795.0,https://anaconda.org/conda-forge/dipy,2021-05-06 13:36:55.402,280048.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +301,vit-pytorch,lucidrains/vit-pytorch,image,,https://github.com/lucidrains/vit-pytorch,https://github.com/lucidrains/vit-pytorch,MIT,2020-10-03 22:47:24.000,2022-01-31 16:56:17.000000,2022-01-31 16:55:31,221.0,42.0,1367,107.0,27.0,82.0,88.0,8513,"Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single..",14.0,29,True,2022-01-31 16:56:17.000,0.26.7,116.0,vit-pytorch,,,,['pytorch'],70.0,69.0,https://pypi.org/project/vit-pytorch,2022-01-31 16:56:17.000,1.0,14663.0,14663.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +302,backtrader,mementum/backtrader,financial-data,,https://github.com/mementum/backtrader,https://github.com/mementum/backtrader,GPL-3.0,2015-01-10 07:14:52.000,2022-01-21 15:41:19.000000,2021-07-17 22:17:12,2385.0,,2401,544.0,195.0,37.0,,8175,Python Backtesting library for trading strategies.,52.0,29,False,,,155.0,backtrader,,,,,949.0,900.0,https://pypi.org/project/backtrader,2020-07-03 13:02:14.000,49.0,17435.0,17435.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +303,pysc2,deepmind/pysc2,others,,https://github.com/deepmind/pysc2,https://github.com/deepmind/pysc2,Apache-2.0,2017-07-25 18:16:57.000,2022-01-29 13:11:26.000000,2019-09-27 15:23:22,513.0,,1112,370.0,74.0,60.0,205.0,7430,StarCraft II Learning Environment.,34.0,29,False,2019-09-27 15:48:01.000,3.0.0,7.0,pysc2,,,,,366.0,341.0,https://pypi.org/project/pysc2,2019-09-27 15:48:01.000,25.0,2056.0,2573.0,,,,,,,,2.0,27941.0,,,,,,,,,,,,,,,,,,,, +304,keras-rl,keras-rl/keras-rl,reinforcement-learning,,https://github.com/keras-rl/keras-rl,https://github.com/keras-rl/keras-rl,MIT,2016-07-02 15:53:12.000,2022-01-05 17:17:48.000000,2019-11-11 22:14:54,308.0,,1323,216.0,154.0,40.0,219.0,5202,Deep Reinforcement Learning for Keras.,40.0,29,False,2018-06-01 07:52:24.000,0.4.2,8.0,keras-rl,,,,['tensorflow'],605.0,552.0,https://pypi.org/project/keras-rl,2018-06-01 07:52:24.000,53.0,1745.0,1745.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +305,skorch,skorch-dev/skorch,ml-frameworks,,https://github.com/skorch-dev/skorch,https://github.com/skorch-dev/skorch,BSD-3-Clause,2017-07-18 00:13:54.000,2022-02-09 22:40:54.000000,2022-01-18 15:50:19,975.0,3.0,298,82.0,414.0,52.0,370.0,4350,A scikit-learn compatible neural network library that wraps PyTorch.,48.0,29,True,2021-10-31 15:54:20.000,0.11.0,14.0,skorch,conda-forge/skorch,,,"['pytorch', 'sklearn']",467.0,434.0,https://pypi.org/project/skorch,2021-10-31 15:48:51.000,33.0,19766.0,32056.0,https://anaconda.org/conda-forge/skorch,2021-11-30 10:48:50.965,503911.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +306,AutoGluon,awslabs/autogluon,hyperopt,,https://github.com/awslabs/autogluon,https://github.com/awslabs/autogluon,Apache-2.0,2019-07-29 18:51:24.000,2022-02-10 10:30:27.000000,2022-02-08 18:52:35,780.0,82.0,552,82.0,860.0,136.0,485.0,4115,"AutoGluon: AutoML for Image, Text, and Tabular Data.",65.0,29,True,2021-08-31 20:48:52.000,0.3.1,688.0,autogluon,,,,['mxnet'],101.0,97.0,https://pypi.org/project/autogluon,2022-02-10 09:04:31.000,4.0,45056.0,45056.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +307,Coqui TTS,coqui-ai/TTS,audio,,https://github.com/coqui-ai/TTS,https://github.com/coqui-ai/TTS,MPL-2.0,2020-05-20 15:45:28.000,2022-02-10 14:38:06.000000,2022-01-03 17:25:18,3775.0,256.0,342,83.0,186.0,31.0,191.0,3918,"- a deep learning toolkit for Text-to-Speech, battle-tested in research and production.",82.0,29,True,2022-01-03 17:28:41.000,0.5.0,22.0,tts,conda-forge/tts,,,"['pytorch', 'tensorflow']",,,https://pypi.org/project/tts,2017-07-14 20:02:42.000,,4561.0,11126.0,https://anaconda.org/conda-forge/tts,2021-12-15 19:29:56.367,1096.0,,,,,2.0,69208.0,,,,,,,,,,,,,,,,,,,, +308,Lasagne,Lasagne/Lasagne,ml-frameworks,,https://github.com/Lasagne/Lasagne,https://github.com/Lasagne/Lasagne,MIT,2014-09-11 15:31:41.000,2021-12-15 16:05:43.118000,2019-11-20 20:28:30,1161.0,,977,216.0,407.0,139.0,402.0,3800,Lightweight library to build and train neural networks in Theano.,72.0,29,False,2015-08-13 21:00:09.000,0.1,2.0,lasagne,,,,,1151.0,890.0,https://pypi.org/project/lasagne,2021-12-15 16:05:43.118,261.0,3699.0,3699.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +309,sacred,IDSIA/sacred,ml-experiments,,https://github.com/IDSIA/sacred,https://github.com/IDSIA/sacred,MIT,2014-03-31 18:05:29.000,2022-02-10 14:16:43.000000,2022-01-26 14:08:42,1315.0,1.0,338,82.0,336.0,96.0,427.0,3717,"Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.",96.0,29,True,2020-12-14 15:21:05.000,0.8.2,27.0,sacred,conda-forge/sacred,,,,1300.0,1198.0,https://pypi.org/project/sacred,2020-12-14 15:21:05.000,102.0,25346.0,25389.0,https://anaconda.org/conda-forge/sacred,2021-11-14 09:49:23.948,129.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +310,FinRL,AI4Finance-Foundation/FinRL,reinforcement-learning,,https://github.com/AI4Finance-Foundation/FinRL,https://github.com/AI4Finance-Foundation/FinRL,MIT,2020-07-26 13:18:16.000,2022-02-10 03:14:59.000000,2022-02-10 03:14:59,1398.0,270.0,898,123.0,124.0,79.0,250.0,3320,FinRL: Financial Reinforcement Learning Framework. Please star.,52.0,29,True,2022-01-08 13:58:14.000,0.3.4,6.0,finrl,,,,,10.0,10.0,https://pypi.org/project/finrl,2022-01-08 13:58:14.000,,405.0,405.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +311,nevergrad,facebookresearch/nevergrad,hyperopt,,https://github.com/facebookresearch/nevergrad,https://github.com/facebookresearch/nevergrad,MIT,2018-11-21 00:33:17.000,2022-02-09 13:15:37.000000,2022-02-09 13:15:37,955.0,34.0,299,66.0,1146.0,97.0,153.0,3229,A Python toolbox for performing gradient-free optimization.,47.0,29,True,2021-01-28 12:05:40.000,0.4.3,34.0,nevergrad,conda-forge/nevergrad,,,,301.0,284.0,https://pypi.org/project/nevergrad,2021-11-10 18:52:59.000,17.0,20447.0,21431.0,https://anaconda.org/conda-forge/nevergrad,2021-06-14 12:44:22.518,21656.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +312,missingno,ResidentMario/missingno,data-viz,,https://github.com/ResidentMario/missingno,https://github.com/ResidentMario/missingno,MIT,2016-03-27 15:18:50.000,2021-07-04 16:12:30.000000,2021-07-04 16:09:34,180.0,,385,70.0,32.0,12.0,102.0,3064,Missing data visualization module for Python.,17.0,29,True,2021-07-04 16:12:30.000,0.5.0,24.0,missingno,conda-forge/missingno,,,,6309.0,6198.0,https://pypi.org/project/missingno,2021-07-04 16:12:30.000,111.0,811829.0,814435.0,https://anaconda.org/conda-forge/missingno,2020-02-15 10:07:41.253,143337.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +313,D-Tale,man-group/dtale,data-viz,,https://github.com/man-group/dtale,https://github.com/man-group/dtale,LGPL-2.1,2019-07-15 09:34:48.000,2022-02-08 14:58:05.000000,2022-02-08 14:58:04,562.0,33.0,230,62.0,189.0,44.0,399.0,3061,Visualizer for pandas data structures.,20.0,29,True,2021-11-18 04:17:35.000,1.61.1,141.0,dtale,conda-forge/dtale,,,"['pandas', 'jupyter']",295.0,284.0,https://pypi.org/project/dtale,2021-11-18 04:17:35.000,11.0,55725.0,60078.0,https://anaconda.org/conda-forge/dtale,2021-11-18 04:41:08.411,104487.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +314,causalml,uber/causalml,others,,https://github.com/uber/causalml,https://github.com/uber/causalml,Apache-2.0,2019-07-09 02:08:58.000,2022-02-09 07:56:49.000000,2022-02-05 14:56:50,430.0,62.0,424,66.0,211.0,44.0,200.0,2773,Uplift modeling and causal inference with machine learning algorithms.,35.0,29,True,2022-02-05 03:12:17.000,0.12.1,17.0,causalml,,,,,38.0,37.0,https://pypi.org/project/causalml,2022-02-05 03:12:17.000,1.0,42868.0,42868.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +315,gpustat,wookayin/gpustat,gpu-utilities,,https://github.com/wookayin/gpustat,https://github.com/wookayin/gpustat,MIT,2016-04-24 10:46:43.000,2022-02-08 20:10:37.000000,2021-08-13 10:24:05,170.0,,213,42.0,38.0,22.0,57.0,2731,A simple command-line utility for querying and monitoring GPU status.,12.0,29,True,2019-07-22 06:37:00.000,0.6.0,11.0,gpustat,conda-forge/gpustat,,,,1706.0,1607.0,https://pypi.org/project/gpustat,2021-01-02 05:59:41.000,99.0,475503.0,478862.0,https://anaconda.org/conda-forge/gpustat,2020-11-24 19:59:04.772,117599.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +316,NMSLIB,nmslib/nmslib,nn-search,,https://github.com/nmslib/nmslib,https://github.com/nmslib/nmslib,Apache-2.0,2013-07-10 11:06:06.000,2021-11-22 21:32:33.032000,2021-09-19 04:51:57,1511.0,,376,97.0,119.0,60.0,332.0,2690,Non-Metric Space Library (NMSLIB): An efficient similarity search library and a toolkit for evaluation of k-NN methods..,45.0,29,True,2021-02-03 16:40:09.000,2.1.1,32.0,nmslib,conda-forge/nmslib,,,,594.0,547.0,https://pypi.org/project/nmslib,2021-02-03 00:02:08.000,47.0,111100.0,113241.0,https://anaconda.org/conda-forge/nmslib,2021-11-22 21:32:33.032,47116.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +317,aubio,aubio/aubio,audio,,https://github.com/aubio/aubio,https://github.com/aubio/aubio,GPL-3.0,2009-12-04 21:07:44.000,2022-01-27 08:50:43.000000,2022-01-25 17:32:20,4123.0,12.0,338,84.0,56.0,127.0,177.0,2645,a library for audio and music analysis.,24.0,29,False,2019-02-27 09:00:43.000,0.4.9,10.0,aubio,conda-forge/aubio,,,,311.0,286.0,https://pypi.org/project/aubio,2019-02-08 11:21:02.000,25.0,2078.0,10332.0,https://anaconda.org/conda-forge/aubio,2021-11-09 17:08:03.654,487042.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +318,GluonNLP,dmlc/gluon-nlp,nlp,,https://github.com/dmlc/gluon-nlp,https://github.com/dmlc/gluon-nlp,Apache-2.0,2018-04-04 20:57:13.000,2021-12-02 15:56:37.000000,2021-08-24 19:11:38,840.0,,519,103.0,1034.0,260.0,295.0,2364,"Toolkit that enables easy text preprocessing, datasets loading and neural models building to help you speed up your..",82.0,29,True,2020-08-13 19:17:42.000,0.10.0,26.0,gluonnlp,,,,['mxnet'],728.0,706.0,https://pypi.org/project/gluonnlp,2020-08-13 19:17:42.000,22.0,98936.0,98936.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +319,pytorch-optimizer,jettify/pytorch-optimizer,pytorch-utils,,https://github.com/jettify/pytorch-optimizer,https://github.com/jettify/pytorch-optimizer,Apache-2.0,2020-01-03 03:16:39.000,2022-02-07 10:09:41.000000,2021-11-11 16:56:57,430.0,,221,32.0,380.0,16.0,28.0,2312,torch-optimizer -- collection of optimizers for Pytorch.,25.0,29,True,2021-10-31 03:00:19.000,0.3.0,21.0,torch_optimizer,conda-forge/torch-optimizer,,,['pytorch'],483.0,460.0,https://pypi.org/project/torch_optimizer,2021-10-31 03:00:19.000,23.0,79266.0,79345.0,https://anaconda.org/conda-forge/torch-optimizer,2021-10-31 17:20:09.384,792.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +320,Foolbox,bethgelab/foolbox,adversarial,,https://github.com/bethgelab/foolbox,https://github.com/bethgelab/foolbox,MIT,2017-06-14 13:05:48.000,2022-02-09 23:34:43.000000,2022-02-04 21:24:54,1685.0,35.0,374,46.0,331.0,61.0,298.0,2148,"A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX.",32.0,29,True,2021-02-23 07:09:34.000,3.3.1,68.0,foolbox,conda-forge/foolbox,,,,276.0,263.0,https://pypi.org/project/foolbox,2021-02-23 07:07:53.000,13.0,2993.0,3274.0,https://anaconda.org/conda-forge/foolbox,2021-04-30 19:06:43.853,5339.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +321,STUMPY,TDAmeritrade/stumpy,time-series-data,,https://github.com/TDAmeritrade/stumpy,https://github.com/TDAmeritrade/stumpy,BSD-3-Clause,2019-05-03 19:23:44.000,2022-02-08 15:13:19.000000,2022-02-08 14:59:09,991.0,64.0,203,49.0,96.0,32.0,261.0,2092,STUMPY is a powerful and scalable Python library for modern time series analysis.,28.0,29,True,2021-12-24 18:12:10.000,1.10.2,25.0,stumpy,conda-forge/stumpy,,,,4.0,,https://pypi.org/project/stumpy,2021-12-24 18:12:10.000,4.0,303636.0,304707.0,https://anaconda.org/conda-forge/stumpy,2021-12-24 18:44:17.831,35367.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +322,pytorch-forecasting,jdb78/pytorch-forecasting,time-series-data,,https://github.com/jdb78/pytorch-forecasting,https://github.com/jdb78/pytorch-forecasting,MIT,2020-07-03 13:05:24.000,2022-02-08 19:14:12.000000,2022-01-21 09:51:18,1151.0,126.0,260,30.0,473.0,155.0,235.0,1714,Time series forecasting with PyTorch.,28.0,29,True,2021-11-29 19:55:05.000,0.9.2,29.0,pytorch-forecasting,conda-forge/pytorch-forecasting,,,,4.0,,https://pypi.org/project/pytorch-forecasting,2021-11-29 19:55:05.000,4.0,24761.0,25701.0,https://anaconda.org/conda-forge/pytorch-forecasting,2021-11-29 23:42:09.447,15992.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +323,Haiku,deepmind/dm-haiku,ml-frameworks,,https://github.com/deepmind/dm-haiku,https://github.com/deepmind/dm-haiku,Apache-2.0,2020-02-18 07:14:02.000,2022-02-10 11:44:57.000000,2022-02-10 11:44:53,675.0,40.0,129,35.0,183.0,33.0,99.0,1713,JAX-based neural network library.,57.0,29,True,2021-11-01 13:18:31.000,0.0.5,7.0,dm-haiku,conda-forge/dm-haiku,,,,348.0,324.0,https://pypi.org/project/dm-haiku,2021-11-01 13:18:31.000,24.0,80366.0,80527.0,https://anaconda.org/conda-forge/dm-haiku,2021-11-03 20:10:14.530,1935.0,,,,,3.0,,,,,,,,,4.0,,,,,,,,,,,, +324,IB-insync,erdewit/ib_insync,financial-data,,https://github.com/erdewit/ib_insync,https://github.com/erdewit/ib_insync,BSD-2-Clause,2017-07-12 12:09:24.000,2022-02-06 10:56:38.000000,2022-02-06 10:56:35,631.0,17.0,467,173.0,58.0,4.0,370.0,1711,Python sync/async framework for Interactive Brokers API.,29.0,29,True,2021-11-28 19:34:09.000,0.9.70,95.0,ib_insync,conda-forge/ib-insync,,,,19.0,,https://pypi.org/project/ib_insync,2021-11-28 19:34:09.000,19.0,9765.0,10227.0,https://anaconda.org/conda-forge/ib-insync,2021-11-29 01:17:29.243,14339.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +325,shapash,MAIF/shapash,interpretability,,https://github.com/MAIF/shapash,https://github.com/MAIF/shapash,Apache-2.0,2020-04-29 07:34:23.000,2022-02-08 14:06:20.000000,2022-02-08 10:01:49,968.0,62.0,208,33.0,184.0,12.0,86.0,1579,Shapash makes Machine Learning models transparent and understandable by everyone.,31.0,29,True,2022-01-14 09:36:25.000,1.6.1,17.0,shapash,,,,['jupyter'],61.0,61.0,https://pypi.org/project/shapash,2022-01-14 09:36:25.000,,20909.0,20909.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +326,Alibi,SeldonIO/alibi,interpretability,,https://github.com/SeldonIO/alibi,https://github.com/SeldonIO/alibi,Apache-2.0,2019-02-26 10:10:56.000,2022-02-10 11:57:11.000000,2022-02-04 13:55:51,367.0,43.0,177,43.0,336.0,110.0,155.0,1515,Algorithms for explaining machine learning models.,18.0,29,True,2022-01-28 18:03:00.000,0.6.4,23.0,alibi,,,,,160.0,138.0,https://pypi.org/project/alibi,2022-01-28 18:01:31.000,22.0,45224.0,45224.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +327,datatable,h2oai/datatable,data-containers,,https://github.com/h2oai/datatable,https://github.com/h2oai/datatable,MPL-2.0,2017-03-03 02:32:59.000,2022-02-10 00:44:09.000000,2022-02-10 00:44:09,2119.0,20.0,126,101.0,1804.0,137.0,1254.0,1450,A Python package for manipulating 2-dimensional tabular data structures.,33.0,29,True,2021-07-02 00:15:35.000,1.0.0,16.0,datatable,conda-forge/datatable,,,,12.0,,https://pypi.org/project/datatable,2021-07-01 23:36:34.000,12.0,79166.0,80019.0,https://anaconda.org/conda-forge/datatable,2020-12-23 12:48:44.694,11636.0,,,,,3.0,1225.0,,,,,,,,,,,,,,,,,,,, +328,ploomber,ploomber/ploomber,data-pipelines,,https://github.com/ploomber/ploomber,https://github.com/ploomber/ploomber,Apache-2.0,2020-01-20 20:13:06.000,2022-02-10 14:15:54.000000,2022-02-10 05:14:22,2379.0,205.0,92,15.0,65.0,136.0,377.0,1250,"The fastest way to build data pipelines. Develop iteratively, deploy anywhere.",34.0,29,True,2022-01-30 16:44:40.000,0.14.8,73.0,ploomber,conda-forge/ploomber,,,,32.0,28.0,https://pypi.org/project/ploomber,2022-02-09 03:17:27.000,4.0,7691.0,8177.0,https://anaconda.org/conda-forge/ploomber,2022-02-03 18:40:47.888,3890.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +329,TabPy,tableau/TabPy,others,,https://github.com/tableau/TabPy,https://github.com/tableau/TabPy,MIT,2016-09-27 21:26:03.000,2022-02-08 20:58:37.000000,2022-01-20 21:20:43,869.0,26.0,451,113.0,241.0,10.0,276.0,1191,Execute Python code on the fly and display results in Tableau visualizations:.,46.0,29,True,2022-01-20 22:19:32.000,2.5.0,26.0,tabpy,anaconda/tabpy-client,,,,83.0,81.0,https://pypi.org/project/tabpy,2022-01-20 22:19:32.000,2.0,17105.0,17146.0,https://anaconda.org/anaconda/tabpy-client,2022-01-20 12:23:08.667,2421.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +330,ktrain,amaiya/ktrain,ml-frameworks,,https://github.com/amaiya/ktrain,https://github.com/amaiya/ktrain,Apache-2.0,2019-02-06 17:01:39.000,2022-02-09 02:41:31.000000,2022-02-09 02:40:19,2585.0,37.0,233,32.0,32.0,3.0,383.0,947,ktrain is a Python library that makes deep learning and AI more accessible and easier to apply.,13.0,29,True,2022-02-09 02:41:31.000,0.29.2,163.0,ktrain,,,,['tensorflow'],258.0,256.0,https://pypi.org/project/ktrain,2022-02-09 02:40:08.000,2.0,33451.0,33451.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +331,pingouin,raphaelvallat/pingouin,probabilistics,,https://github.com/raphaelvallat/pingouin,https://github.com/raphaelvallat/pingouin,GPL-3.0,2018-04-01 01:10:22.000,2022-02-10 04:40:03.000000,2022-02-10 04:40:03,1169.0,12.0,82,25.0,43.0,34.0,157.0,903,Statistical package in Python based on Pandas.,25.0,29,False,2021-10-28 22:09:53.000,0.5.0,35.0,pingouin,conda-forge/pingouin,,,,479.0,457.0,https://pypi.org/project/pingouin,2021-10-28 21:59:14.000,22.0,62396.0,63719.0,https://anaconda.org/conda-forge/pingouin,2021-10-29 00:37:42.640,50292.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +332,arch,bashtage/arch,financial-data,,https://github.com/bashtage/arch,https://github.com/bashtage/arch,NCSA,2014-08-29 15:41:28.000,2022-02-10 00:14:26.000000,2022-02-04 23:04:54,915.0,19.0,195,41.0,391.0,15.0,150.0,858,ARCH models in Python.,30.0,29,False,2021-11-19 16:00:03.000,5.1.0,35.0,arch,conda-forge/arch-py,,,,491.0,453.0,https://pypi.org/project/arch,2021-11-19 16:00:03.000,38.0,137768.0,141116.0,https://anaconda.org/conda-forge/arch-py,2021-11-20 00:25:28.916,90403.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +333,dask-ml,dask/dask-ml,distributed-ml,,https://github.com/dask/dask-ml,https://github.com/dask/dask-ml,BSD-3-Clause,2017-06-15 15:56:06.000,2022-01-22 16:40:06.510000,2022-01-20 16:14:49,797.0,9.0,218,40.0,477.0,230.0,238.0,782,Scalable Machine Learning with Dask.,71.0,29,True,2022-01-22 13:23:47.000,2022.1.22,33.0,dask-ml,conda-forge/dask-ml,,,,607.0,552.0,https://pypi.org/project/dask-ml,2022-01-22 13:23:47.000,55.0,61711.0,66785.0,https://anaconda.org/conda-forge/dask-ml,2022-01-22 16:40:06.510,263891.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +334,Sentinelsat,sentinelsat/sentinelsat,geospatial-data,,https://github.com/sentinelsat/sentinelsat,https://github.com/sentinelsat/sentinelsat,GPL-3.0,2015-05-22 20:32:26.000,2022-01-06 09:30:10.449000,2022-01-05 19:57:41,1116.0,10.0,204,57.0,238.0,9.0,308.0,714,Search and download Copernicus Sentinel satellite images.,42.0,29,False,2022-01-05 19:58:27.000,1.1.1,40.0,sentinelsat,conda-forge/sentinelsat,,,,296.0,266.0,https://pypi.org/project/sentinelsat,2022-01-05 19:58:27.000,30.0,19597.0,19855.0,https://anaconda.org/conda-forge/sentinelsat,2022-01-06 09:30:10.449,4084.0,,,,,3.0,227.0,,,,,,,,,,,,,,,,,,,, +335,CLTK,cltk/cltk,nlp,,https://github.com/cltk/cltk,https://github.com/cltk/cltk,MIT,2014-01-11 23:59:47.000,2022-02-06 04:37:47.000000,2022-02-06 04:37:28,3613.0,21.0,307,68.0,639.0,22.0,491.0,706,The Classical Language Toolkit.,114.0,29,True,2022-01-05 18:55:36.000,1.0.22,193.0,cltk,,,,,231.0,189.0,https://pypi.org/project/cltk,2022-02-04 23:48:53.000,42.0,2504.0,2504.0,,,,,,,,2.0,25.0,,,,,,,,,,,,,,,,,,,, +336,audioread,beetbox/audioread,audio,,https://github.com/beetbox/audioread,https://github.com/beetbox/audioread,MIT,2011-11-08 19:53:18.000,2022-01-08 02:58:29.695000,2021-12-03 18:19:53,251.0,19.0,89,19.0,43.0,31.0,46.0,389,cross-library (GStreamer + Core Audio + MAD + FFmpeg) audio decoding for Python.,21.0,29,True,2020-10-20 11:23:09.000,2.1.9,25.0,audioread,conda-forge/audioread,,,,7641.0,7316.0,https://pypi.org/project/audioread,2020-10-20 11:23:09.000,325.0,510337.0,516033.0,https://anaconda.org/conda-forge/audioread,2022-01-08 02:58:29.695,381647.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +337,huggingface_hub,huggingface/huggingface_hub,model-serialisation,,https://github.com/huggingface/huggingface_hub,https://github.com/huggingface/huggingface_hub,Apache-2.0,2020-12-22 10:20:28.000,2022-02-10 11:30:23.000000,2022-02-09 22:32:24,548.0,123.0,71,36.0,470.0,103.0,109.0,331,All the open source things related to the Hugging Face Hub.,55.0,29,True,2022-01-26 18:30:22.000,0.4.0,26.0,huggingface_hub,conda-forge/huggingface_hub,,,,51.0,,https://pypi.org/project/huggingface_hub,2022-01-11 10:51:32.000,51.0,2482576.0,2484826.0,https://anaconda.org/conda-forge/huggingface_hub,2022-01-12 11:57:27.670,27008.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +338,spleeter,deezer/spleeter,audio,,https://github.com/deezer/spleeter,https://github.com/deezer/spleeter,MIT,2019-09-26 15:40:46.000,2022-02-10 07:01:32.000000,2021-12-08 16:06:40,474.0,1.0,2029,370.0,82.0,115.0,524.0,18757,Deezer source separation library including pretrained models.,18.0,28,True,2021-09-03 09:59:00.000,2.3.0,34.0,spleeter,conda-forge/spleeter,,,['tensorflow'],3.0,,https://pypi.org/project/spleeter,2021-09-03 09:55:50.000,3.0,10081.0,63075.0,https://anaconda.org/conda-forge/spleeter,2020-06-30 14:33:43.220,62111.0,,,,,3.0,1419441.0,,,,,,,,,,,,,,,,,,,, +339,TensorLayer,tensorlayer/tensorlayer,reinforcement-learning,,https://github.com/tensorlayer/TensorLayer,https://github.com/tensorlayer/TensorLayer,Apache-2.0,2016-06-07 15:55:16.000,2021-12-03 08:14:02.000000,2021-10-29 08:29:08,3350.0,,1494,462.0,696.0,20.0,437.0,6816,Deep Learning and Reinforcement Learning Library for Scientists and Engineers.,132.0,28,True,2021-01-06 07:16:21.000,2.2.4,82.0,tensorlayer,,,,['tensorflow'],39.0,,https://pypi.org/project/tensorlayer,2020-06-19 00:53:37.000,39.0,2531.0,2551.0,,,,,,,,2.0,1362.0,,,,,,,,,,,,,,,,,,,, +340,NuPIC,numenta/nupic,ml-frameworks,,https://github.com/numenta/nupic,https://github.com/numenta/nupic,AGPL-3.0,2013-04-05 23:14:27.000,2021-03-25 21:39:47.000000,2019-10-23 20:45:07,6625.0,,1585,634.0,2110.0,456.0,1337.0,6294,"Numenta Platform for Intelligent Computing is an implementation of Hierarchical Temporal Memory (HTM), a theory of..",121.0,28,False,2018-06-01 15:37:54.000,1.0.5,53.0,nupic,,,,,146.0,108.0,https://pypi.org/project/nupic,2018-06-01 15:37:54.000,38.0,3005.0,3005.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +341,PyText,facebookresearch/pytext,nlp,,https://github.com/facebookresearch/pytext,https://github.com/facebookresearch/pytext,BSD-3-Clause,2018-07-31 23:40:46.000,2022-02-08 22:04:02.000000,2022-02-08 22:03:58,1688.0,17.0,804,169.0,1580.0,145.0,74.0,6273,A natural language modeling framework based on PyTorch.,219.0,28,True,2020-06-08 23:30:58.000,0.3.3,13.0,pytext-nlp,,,,['pytorch'],104.0,103.0,https://pypi.org/project/pytext-nlp,2020-06-08 22:49:33.000,1.0,284.0,291.0,,,,,,,,2.0,287.0,,,,,,,,,,,,,,,,,,,, +342,PyTorch3D,facebookresearch/pytorch3d,image,,https://github.com/facebookresearch/pytorch3d,https://github.com/facebookresearch/pytorch3d,,2019-10-25 02:23:45.000,2022-02-09 20:49:57.000000,2022-02-09 20:49:55,657.0,53.0,787,139.0,95.0,82.0,839.0,5627,PyTorch3D is FAIRs library of reusable components for deep learning with 3D data.,75.0,28,False,2021-12-16 19:13:11.000,0.6.1,10.0,pytorch3d,pytorch3d/pytorch3d,,,['pytorch'],155.0,151.0,https://pypi.org/project/pytorch3d,2021-12-16 16:50:38.000,4.0,9297.0,10578.0,https://anaconda.org/pytorch3d/pytorch3d,2021-12-16 16:50:37.672,34602.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +343,MindsDB,mindsdb/mindsdb,ml-frameworks,,https://github.com/mindsdb/mindsdb,https://github.com/mindsdb/mindsdb,GPL-3.0,2018-08-02 17:56:45.000,2022-02-10 12:42:32.000000,2022-02-10 12:42:32,4883.0,379.0,610,222.0,1075.0,85.0,762.0,5437,In-Database Machine Learning.,95.0,28,False,2022-02-08 13:20:18.000,22.2.1.2,92.0,mindsdb,,,,['pytorch'],4.0,,https://pypi.org/project/mindsdb,2019-03-19 05:07:23.000,4.0,5804.0,5804.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +344,scikit-surprise,NicolasHug/Surprise,recommender-systems,,https://github.com/NicolasHug/Surprise,https://github.com/NicolasHug/Surprise,BSD-3-Clause,2016-10-23 14:59:38.000,2022-02-02 21:13:06.000000,2020-08-05 17:45:59,622.0,,895,150.0,66.0,51.0,292.0,5220,A Python scikit for building and analyzing recommender systems.,38.0,28,False,2020-07-19 14:50:48.000,1.1.1,9.0,scikit-surprise,conda-forge/scikit-surprise,,,,26.0,,https://pypi.org/project/scikit-surprise,2020-07-19 14:50:48.000,26.0,77749.0,82027.0,https://anaconda.org/conda-forge/scikit-surprise,2021-11-18 20:15:44.176,209622.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +345,Edward,blei-lab/edward,probabilistics,,https://github.com/blei-lab/edward,https://github.com/blei-lab/edward,Apache-2.0,2016-02-10 20:06:05.000,2019-10-22 20:30:48.000000,2018-07-25 01:28:08,1796.0,,767,281.0,437.0,212.0,328.0,4687,"A probabilistic programming language in TensorFlow. Deep generative models, variational inference.",87.0,28,False,2018-01-22 06:03:37.000,1.3.5,28.0,edward,,,,['tensorflow'],292.0,252.0,https://pypi.org/project/edward,2018-01-22 06:03:05.000,40.0,3179.0,3179.0,,,,,,,,3.0,15.0,,,,,,,,,,,,,,,,,,,, +346,kaggle,Kaggle/kaggle-api,ml-experiments,,https://github.com/Kaggle/kaggle-api,https://github.com/Kaggle/kaggle-api,Apache-2.0,2018-01-25 03:02:39.000,2021-12-17 19:19:11.878000,2021-03-15 15:49:05,145.0,,884,180.0,74.0,190.0,145.0,4563,Official Kaggle API.,36.0,28,True,2021-03-13 00:50:03.000,1.5.12,48.0,kaggle,conda-forge/kaggle,,,,324.0,,https://pypi.org/project/kaggle,2021-03-13 00:50:03.000,324.0,126068.0,128407.0,https://anaconda.org/conda-forge/kaggle,2021-12-17 19:19:11.878,77210.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +347,haystack,deepset-ai/haystack,nlp,,https://github.com/deepset-ai/haystack,https://github.com/deepset-ai/haystack,Apache-2.0,2019-11-14 09:05:28.000,2022-02-10 14:50:01.000000,2022-02-10 14:07:02,1065.0,172.0,667,78.0,928.0,173.0,982.0,4140,Haystack is an open source NLP framework that leverages Transformer models. It enables developers to implement..,97.0,28,True,2022-01-20 16:24:00.000,1.1.0,35.0,haystack,,,,,85.0,,https://pypi.org/project/haystack,2021-12-15 14:01:39.322,85.0,841.0,841.0,,,,,,,,2.0,3.0,,,,,,,,,,,,,,,,,,,, +348,T5,google-research/text-to-text-transfer-transformer,nlp,,https://github.com/google-research/text-to-text-transfer-transformer,https://github.com/google-research/text-to-text-transfer-transformer,Apache-2.0,2019-10-17 21:45:14.000,2022-02-04 16:39:30.000000,2022-02-04 08:46:54,539.0,16.0,540,100.0,504.0,64.0,334.0,3938,Code for the paper Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer.,44.0,28,True,2021-10-18 13:55:26.000,0.9.3,28.0,t5,,,,['tensorflow'],84.0,82.0,https://pypi.org/project/t5,2021-10-18 13:55:26.000,2.0,6095.0,6095.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +349,lightfm,lyst/lightfm,recommender-systems,,https://github.com/lyst/lightfm,https://github.com/lyst/lightfm,Apache-2.0,2015-07-30 08:34:00.000,2022-02-07 20:17:36.000000,2021-12-31 20:43:26,431.0,3.0,614,96.0,191.0,91.0,345.0,3916,"A Python implementation of LightFM, a hybrid recommendation algorithm.",44.0,28,True,2020-11-27 19:48:30.000,1.16,14.0,lightfm,conda-forge/lightfm,,,,681.0,636.0,https://pypi.org/project/lightfm,2020-11-27 19:55:08.000,45.0,300433.0,302746.0,https://anaconda.org/conda-forge/lightfm,2021-02-07 22:19:58.097,113381.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +350,Darts,unit8co/darts,time-series-data,,https://github.com/unit8co/darts,https://github.com/unit8co/darts,Apache-2.0,2018-09-13 15:17:28.000,2022-02-10 10:03:07.000000,2022-02-08 10:08:47,703.0,65.0,341,45.0,449.0,119.0,212.0,3651,A python library for easy manipulation and forecasting of time series.,43.0,28,True,2022-01-24 16:09:58.000,0.16.1,25.0,u8darts,conda-forge/u8darts-all,unit8/darts,,,30.0,28.0,https://pypi.org/project/u8darts,2022-01-24 16:09:58.000,2.0,5110.0,5408.0,https://anaconda.org/conda-forge/u8darts-all,2022-01-25 10:35:22.560,2045.0,https://hub.docker.com/r/unit8/darts,2022-01-24 16:17:27.778393,,256.0,2.0,,,,,,,,,,,,,,,,,,,,, +351,DoWhy,Microsoft/dowhy,interpretability,,https://github.com/microsoft/dowhy,https://github.com/microsoft/dowhy,MIT,2018-05-31 13:07:04.000,2022-02-09 11:03:17.000000,2022-02-06 15:57:04,484.0,18.0,555,120.0,201.0,52.0,126.0,3605,DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions...,48.0,28,True,2022-01-10 08:50:57.000,0.7,7.0,dowhy,conda-forge/dowhy,,,,87.0,83.0,https://pypi.org/project/dowhy,2022-01-10 08:51:22.000,4.0,99345.0,99551.0,https://anaconda.org/conda-forge/dowhy,2022-01-22 14:36:04.116,4336.0,,,,,2.0,24.0,,,,,,,,,,,,,,,,,,,, +352,Alpha Vantage,RomelTorres/alpha_vantage,financial-data,,https://github.com/RomelTorres/alpha_vantage,https://github.com/RomelTorres/alpha_vantage,MIT,2017-04-29 17:23:00.000,2022-01-04 14:23:20.000000,2021-06-14 05:10:42,518.0,,632,175.0,76.0,14.0,249.0,3594,A python wrapper for Alpha Vantage API for financial data.,39.0,28,True,2020-12-21 02:37:29.000,2.3.1,28.0,alpha_vantage,conda-forge/alpha_vantage,,,,104.0,,https://pypi.org/project/alpha_vantage,2018-08-26 18:55:11.000,104.0,21717.0,21786.0,https://anaconda.org/conda-forge/alpha_vantage,2021-01-14 18:10:30.064,908.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +353,triton,openai/triton,model-serialisation,,https://github.com/openai/triton,https://github.com/openai/triton,MIT,2014-08-30 17:07:16.000,2022-02-10 09:57:40.000000,2022-02-10 09:57:39,424.0,66.0,262,85.0,269.0,61.0,114.0,3480,Development repository for the Triton language and compiler.,34.0,28,True,2015-08-15 18:58:53.000,3.4.1,95.0,triton,,,,,68.0,66.0,https://pypi.org/project/triton,2022-02-10 00:11:39.000,2.0,51729.0,51729.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,True, +354,Sumy,miso-belica/sumy,nlp,,https://github.com/miso-belica/sumy,https://github.com/miso-belica/sumy,Apache-2.0,2013-02-20 12:56:48.000,2021-11-23 21:07:29.000000,2021-11-23 21:07:29,403.0,3.0,462,113.0,68.0,15.0,83.0,2748,Module for automatic summarization of text documents and HTML pages.,21.0,28,True,2021-10-21 17:24:42.000,0.9.0,14.0,sumy,conda-forge/sumy,,,,1200.0,1099.0,https://pypi.org/project/sumy,2021-10-21 17:24:42.000,101.0,25529.0,25607.0,https://anaconda.org/conda-forge/sumy,2021-10-22 09:47:02.763,624.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +355,Porcupine,Picovoice/Porcupine,audio,,https://github.com/Picovoice/porcupine,https://github.com/Picovoice/porcupine,Apache-2.0,2018-03-08 01:55:25.000,2022-02-06 01:19:31.000000,2022-02-06 09:19:27,675.0,117.0,387,61.0,304.0,4.0,356.0,2644,On-device wake word detection powered by deep learning.,31.0,28,True,2022-02-04 21:45:16.000,2.1.1,26.0,pvporcupine,,,,,16.0,8.0,https://pypi.org/project/pvporcupine,2022-02-04 21:45:16.000,8.0,2232.0,2232.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +356,TextDistance,life4/textdistance,nlp,,https://github.com/life4/textdistance,https://github.com/life4/textdistance,MIT,2017-05-05 08:46:10.000,2021-12-03 13:09:42.000000,2021-11-29 10:29:02,321.0,5.0,204,59.0,41.0,9.0,,2596,"Compute distance between sequences. 30+ algorithms, pure python implementation, common interface, optional external..",11.0,28,True,2021-10-27 13:15:53.000,4.2.2,22.0,textdistance,conda-forge/textdistance,,,,1696.0,1657.0,https://pypi.org/project/textdistance,2021-10-27 13:15:53.000,39.0,289138.0,290779.0,https://anaconda.org/conda-forge/textdistance,2021-10-27 17:04:18.548,73451.0,,,,,2.0,462.0,,,,,,,,,,,,,,,,,,,, +357,Acme,deepmind/acme,reinforcement-learning,,https://github.com/deepmind/acme,https://github.com/deepmind/acme,Apache-2.0,2020-05-01 09:18:12.000,2022-02-10 11:50:11.000000,2022-02-10 11:49:19,725.0,96.0,298,72.0,38.0,40.0,120.0,2518,A library of reinforcement learning components and agents.,58.0,28,True,2022-02-10 06:52:01.000,0.4.0,15.0,dm-acme,conda-forge/dm-acme,,,['tensorflow'],58.0,56.0,https://pypi.org/project/dm-acme,2022-02-10 06:52:27.000,2.0,3920.0,4042.0,https://anaconda.org/conda-forge/dm-acme,2021-12-09 14:52:24.765,1837.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +358,analytics-zoo,intel-analytics/analytics-zoo,distributed-ml,,https://github.com/intel-analytics/analytics-zoo,https://github.com/intel-analytics/analytics-zoo,Apache-2.0,2017-05-05 02:27:30.000,2022-02-10 04:55:12.000000,2022-02-10 00:55:20,3423.0,27.0,713,102.0,3826.0,561.0,840.0,2469,"Distributed Tensorflow, Keras and PyTorch on Apache Spark/Flink & Ray.",105.0,28,True,2022-01-25 00:20:26.000,0.11.2,235.0,analytics-zoo,,,,['spark'],4.0,3.0,https://pypi.org/project/analytics-zoo,2022-02-09 22:06:32.000,1.0,9498.0,9498.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +359,GluonTS,awslabs/gluon-ts,time-series-data,,https://github.com/awslabs/gluon-ts,https://github.com/awslabs/gluon-ts,Apache-2.0,2019-05-15 17:17:29.000,2022-02-09 20:54:25.000000,2022-02-09 20:54:24,843.0,54.0,504,68.0,1001.0,273.0,424.0,2455,Probabilistic time series modeling in Python.,84.0,28,True,2021-08-12 10:05:38.000,0.8.1,43.0,gluonts,anaconda/gluonts,,,['mxnet'],3.0,,https://pypi.org/project/gluonts,2021-11-11 15:18:16.000,3.0,77430.0,77430.0,https://anaconda.org/anaconda/gluonts,2021-10-14 12:53:07.201,2.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +360,pygal,Kozea/pygal,graph,,https://github.com/Kozea/pygal,https://github.com/Kozea/pygal,LGPL-3.0,2011-09-23 10:17:50.000,2021-11-29 10:47:48.000000,2021-11-24 21:04:02,1018.0,3.0,391,136.0,126.0,177.0,244.0,2431,PYthon svg GrAph plotting Library.,71.0,28,False,2021-11-24 21:07:22.000,3.0.0,75.0,pygal,conda-forge/pygal,,,,628.0,,https://pypi.org/project/pygal,2021-11-24 21:07:22.000,628.0,111144.0,111455.0,https://anaconda.org/conda-forge/pygal,2019-06-04 02:55:56.728,9965.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +361,StellarGraph,stellargraph/stellargraph,graph,,https://github.com/stellargraph/stellargraph,https://github.com/stellargraph/stellargraph,Apache-2.0,2018-04-13 07:35:51.000,2022-01-24 20:10:29.000000,2021-10-29 06:15:49,2535.0,,339,60.0,925.0,252.0,734.0,2273,StellarGraph - Machine Learning on Graphs.,36.0,28,True,2020-06-30 05:15:21.000,1.2.1,25.0,stellargraph,,,,['tensorflow'],122.0,119.0,https://pypi.org/project/stellargraph,2020-06-30 05:10:43.000,3.0,40046.0,40046.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +362,pandas-ta,twopirllc/pandas-ta,probabilistics,,https://github.com/twopirllc/pandas-ta,https://github.com/twopirllc/pandas-ta,MIT,2019-02-19 16:41:09.000,2022-02-08 20:25:18.000000,2022-01-31 16:47:12,581.0,2.0,490,73.0,128.0,57.0,304.0,2120,Technical Analysis Indicators - Pandas TA is an easy to use Python 3 Pandas Extension with 130+ Indicators.,44.0,28,True,2021-07-28 20:21:21.000,0.3.14,19.0,pandas-ta,conda-forge/pandas-ta,,,['pandas'],443.0,433.0,https://pypi.org/project/pandas-ta,2021-07-28 20:51:17.000,10.0,83142.0,83218.0,https://anaconda.org/conda-forge/pandas-ta,2021-10-05 09:16:48.657,307.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +363,Essentia,MTG/essentia,audio,,https://github.com/MTG/essentia,https://github.com/MTG/essentia,AGPL-3.0,2013-06-03 14:53:47.000,2022-02-06 01:41:30.000000,2022-02-02 17:16:05,3066.0,98.0,435,109.0,298.0,347.0,598.0,2036,"C++ library for audio and music analysis, description and synthesis, including Python bindings.",73.0,28,False,2015-03-31 16:33:30.000,2.0,10.0,essentia,,,,,276.0,263.0,https://pypi.org/project/essentia,2021-11-04 15:23:58.000,13.0,2487.0,2487.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +364,dtreeviz,parrt/dtreeviz,interpretability,,https://github.com/parrt/dtreeviz,https://github.com/parrt/dtreeviz,MIT,2018-08-13 21:45:15.000,2022-02-09 17:43:46.000000,2022-02-09 17:43:40,377.0,6.0,253,48.0,59.0,20.0,96.0,2012,A python library for decision tree visualization and model interpretation.,17.0,28,True,2022-02-09 17:43:46.000,1.3.3,26.0,dtreeviz,conda-forge/dtreeviz,,,,310.0,296.0,https://pypi.org/project/dtreeviz,2022-02-09 17:43:46.000,14.0,74693.0,75172.0,https://anaconda.org/conda-forge/dtreeviz,2021-12-03 09:30:09.144,7191.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +365,swifter,jmcarpenter2/swifter,data-containers,,https://github.com/jmcarpenter2/swifter,https://github.com/jmcarpenter2/swifter,MIT,2018-04-07 21:37:19.000,2022-02-07 17:34:57.000000,2022-02-07 17:34:52,441.0,14.0,87,27.0,67.0,23.0,85.0,1896,A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner.,15.0,28,True,2022-02-07 17:33:50.000,1.1.2,75.0,swifter,conda-forge/swifter,,,['pandas'],505.0,477.0,https://pypi.org/project/swifter,2022-02-07 17:33:50.000,28.0,142667.0,146397.0,https://anaconda.org/conda-forge/swifter,2021-06-26 01:03:15.021,126840.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +366,PyTextRank,DerwenAI/pytextrank,nlp,,https://github.com/DerwenAI/pytextrank,https://github.com/DerwenAI/pytextrank,MIT,2016-10-02 18:39:12.000,2022-02-06 22:36:09.000000,2022-02-04 20:26:33,413.0,10.0,321,62.0,126.0,23.0,60.0,1738,Python implementation of TextRank for phrase extraction and summarization of text documents.,18.0,28,True,2021-10-10 01:12:11.000,3.2.2,18.0,pytextrank,,,,,241.0,229.0,https://pypi.org/project/pytextrank,2021-10-10 01:12:11.000,12.0,20657.0,20657.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +367,streamparse,Parsely/streamparse,data-pipelines,,https://github.com/Parsely/streamparse,https://github.com/Parsely/streamparse,Apache-2.0,2014-05-02 20:33:50.000,2022-01-10 21:46:17.000000,2022-01-10 21:42:18,1069.0,10.0,217,102.0,167.0,70.0,263.0,1451,"Run Python in Apache Storm topologies. Pythonic API, CLI tooling, and a topology DSL.",42.0,28,True,2022-01-10 21:46:17.000,4.1.2,50.0,streamparse,,,,,80.0,53.0,https://pypi.org/project/streamparse,2022-01-10 21:43:49.000,27.0,2396.0,2396.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +368,lightning-flash,PyTorchLightning/lightning-flash,pytorch-utils,,https://github.com/PyTorchLightning/lightning-flash,https://github.com/PyTorchLightning/lightning-flash,Apache-2.0,2021-01-28 18:47:16.000,2022-02-10 14:17:59.000000,2022-02-10 14:17:58,806.0,131.0,142,29.0,720.0,46.0,375.0,1374,Your PyTorch AI Factory - Flash enables you to easily configure and run complex AI recipes for over 15 tasks across 7..,61.0,28,True,2021-12-13 17:53:06.000,0.6.0,29.0,lightning-flash,conda-forge/lightning-flash,,,['pytorch'],50.0,48.0,https://pypi.org/project/lightning-flash,2022-02-04 20:42:47.000,2.0,2403.0,2516.0,https://anaconda.org/conda-forge/lightning-flash,2021-12-13 21:40:44.990,682.0,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +369,petastorm,uber/petastorm,distributed-ml,,https://github.com/uber/petastorm,https://github.com/uber/petastorm,Apache-2.0,2018-06-15 23:15:29.000,2022-01-12 04:35:37.000000,2022-01-10 18:25:00,667.0,3.0,226,41.0,471.0,135.0,138.0,1351,Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets..,43.0,28,True,2021-09-04 05:47:24.000,0.11.3,75.0,petastorm,,,,,58.0,54.0,https://pypi.org/project/petastorm,2021-09-04 05:47:24.000,4.0,83944.0,83951.0,,,,,,,,2.0,309.0,,,,,,,,,,,,,,,,,,,, +370,ViZDoom,mwydmuch/ViZDoom,reinforcement-learning,,https://github.com/mwydmuch/ViZDoom,https://github.com/mwydmuch/ViZDoom,MIT,2015-06-26 18:38:23.000,2022-01-20 22:44:16.000000,2022-01-20 22:44:16,1529.0,13.0,312,52.0,71.0,89.0,345.0,1326,Doom-based AI Research Platform for Reinforcement Learning from Raw Visual Information.,46.0,28,True,2021-11-22 11:15:55.000,1.1.11,22.0,vizdoom,,,,,136.0,122.0,https://pypi.org/project/vizdoom,2021-11-22 11:16:41.000,14.0,903.0,1064.0,,,,,,,,2.0,11433.0,,,,,,,,,,,,,,,,,,,, +371,ogb,snap-stanford/ogb,graph,,https://github.com/snap-stanford/ogb,https://github.com/snap-stanford/ogb,MIT,2019-11-22 22:13:57.000,2022-01-14 16:02:29.000000,2022-01-14 16:01:44,579.0,5.0,254,38.0,30.0,1.0,184.0,1225,"Benchmark datasets, data loaders, and evaluators for graph machine learning.",18.0,28,True,2021-09-29 04:42:13.000,1.3.2,15.0,ogb,conda-forge/ogb,,,,233.0,220.0,https://pypi.org/project/ogb,2021-09-29 04:33:43.000,13.0,24514.0,24898.0,https://anaconda.org/conda-forge/ogb,2021-09-29 13:53:36.971,6536.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +372,pycm,sepandhaghighi/pycm,others,,https://github.com/sepandhaghighi/pycm,https://github.com/sepandhaghighi/pycm,MIT,2018-01-22 19:46:54.000,2022-02-07 13:39:59.000000,2022-01-26 10:23:11,2945.0,161.0,104,34.0,241.0,12.0,168.0,1205,Multi-class confusion matrix library in Python.,17.0,28,True,2022-01-26 10:42:57.000,3.4,38.0,pycm,,,,,139.0,127.0,https://pypi.org/project/pycm,2022-01-26 10:43:21.000,12.0,34769.0,34769.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +373,TF Recommenders,tensorflow/recommenders,recommender-systems,,https://github.com/tensorflow/recommenders,https://github.com/tensorflow/recommenders,Apache-2.0,2020-06-26 21:38:01.000,2022-02-07 09:52:21.000000,2022-01-28 04:51:42,289.0,11.0,163,48.0,223.0,124.0,105.0,1195,TensorFlow Recommenders is a library for building recommender system models using TensorFlow.,30.0,28,True,2021-08-23 23:29:59.000,0.6.0,12.0,tensorflow-recommenders,,,,['tensorflow'],72.0,71.0,https://pypi.org/project/tensorflow-recommenders,2021-08-23 23:29:59.000,1.0,266729.0,266729.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +374,PySAL,pysal/pysal,geospatial-data,,https://github.com/pysal/pysal,https://github.com/pysal/pysal,BSD-3-Clause,2013-02-19 17:27:42.000,2022-01-31 17:47:09.921000,2022-01-30 22:27:10,4173.0,36.0,273,76.0,624.0,11.0,597.0,970,PySAL: Python Spatial Analysis Library Meta-Package.,75.0,28,True,2022-01-30 19:38:41.000,2.6.0,28.0,pysal,conda-forge/pysal,,,,30.0,,https://pypi.org/project/pysal,2022-01-30 19:38:41.000,30.0,16621.0,23076.0,https://anaconda.org/conda-forge/pysal,2022-01-31 17:47:09.921,432535.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +375,pyjanitor,pyjanitor-devs/pyjanitor,others,,https://github.com/pyjanitor-devs/pyjanitor,https://github.com/pyjanitor-devs/pyjanitor,MIT,2018-03-04 22:43:33.000,2022-02-10 01:40:23.000000,2022-02-08 22:18:16,1333.0,33.0,135,23.0,570.0,97.0,346.0,823,Clean APIs for data cleaning. Python implementation of R package Janitor.,96.0,28,True,2021-11-21 02:25:32.000,0.22.0,53.0,pyjanitor,conda-forge/pyjanitor,,,,159.0,149.0,https://pypi.org/project/pyjanitor,2021-11-21 02:25:27.000,10.0,18222.0,20600.0,https://anaconda.org/conda-forge/pyjanitor,2021-11-22 17:28:45.154,111804.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +376,geojson,jazzband/geojson,geospatial-data,,https://github.com/jazzband/geojson,https://github.com/jazzband/geojson,BSD-3-Clause,2011-07-01 20:39:48.000,2022-01-17 09:28:09.000000,2022-01-03 20:57:51,456.0,1.0,90,29.0,97.0,22.0,58.0,687,Python bindings and utilities for GeoJSON.,46.0,28,True,2019-08-09 20:32:15.000,2.5.0,28.0,geojson,conda-forge/geojson,,,,9665.0,8547.0,https://pypi.org/project/geojson,2019-08-09 20:32:15.000,1118.0,763610.0,770297.0,https://anaconda.org/conda-forge/geojson,2019-08-11 12:10:34.426,474797.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +377,adapter-transformers,Adapter-Hub/adapter-transformers,others,,https://github.com/Adapter-Hub/adapter-transformers,https://github.com/Adapter-Hub/adapter-transformers,Apache-2.0,2020-04-21 16:21:43.000,2022-02-09 18:26:26.000000,2022-02-09 17:33:01,8764.0,29.0,109,14.0,145.0,33.0,104.0,662,Huggingface Transformers + Adapters =.,1065.0,28,True,2022-02-09 18:26:26.000,2.3.0,13.0,adapter-transformers,,,,['huggingface'],47.0,43.0,https://pypi.org/project/adapter-transformers,2022-02-09 18:26:26.000,4.0,50003.0,50003.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,True, +378,PyNNDescent,lmcinnes/pynndescent,nn-search,,https://github.com/lmcinnes/pynndescent,https://github.com/lmcinnes/pynndescent,BSD-2-Clause,2018-02-07 23:23:54.000,2022-02-10 00:30:09.000000,2022-02-10 00:30:09,571.0,42.0,76,12.0,74.0,45.0,52.0,583,A Python nearest neighbor descent for approximate nearest neighbors.,18.0,28,True,2022-01-21 03:32:05.000,0.5.6,25.0,pynndescent,conda-forge/pynndescent,,,,1228.0,1203.0,https://pypi.org/project/pynndescent,2022-01-21 03:32:05.000,25.0,1073968.0,1088304.0,https://anaconda.org/conda-forge/pynndescent,2022-01-22 20:10:32.647,458757.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +379,SALib,SALib/SALib,probabilistics,,https://github.com/SALib/SALib,https://github.com/SALib/SALib,MIT,2013-05-30 13:38:10.000,2022-02-06 04:55:37.000000,2022-02-06 03:12:48,1514.0,9.0,172,20.0,237.0,47.0,225.0,564,"Sensitivity Analysis Library in Python. Contains Sobol, Morris, FAST, and other methods.",35.0,28,True,2021-09-04 09:49:51.000,1.4.5,41.0,salib,conda-forge/salib,,,,54.0,,https://pypi.org/project/salib,2022-02-06 04:55:37.000,54.0,124914.0,126111.0,https://anaconda.org/conda-forge/salib,2021-09-04 07:03:28.179,75464.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +380,hvPlot,holoviz/hvplot,data-viz,,https://github.com/holoviz/hvplot,https://github.com/holoviz/hvplot,BSD-3-Clause,2018-03-19 14:22:41.000,2022-02-08 21:12:09.000000,2022-02-08 21:12:09,436.0,14.0,64,20.0,263.0,144.0,262.0,523,"A high-level plotting API for pandas, dask, xarray, and networkx built on HoloViews.",35.0,28,True,2021-07-26 16:25:50.000,0.7.3,39.0,hvplot,conda-forge/hvplot,,,,1074.0,1019.0,https://pypi.org/project/hvplot,2021-12-09 15:42:22.000,55.0,96241.0,99700.0,https://anaconda.org/conda-forge/hvplot,2021-07-23 14:04:28.244,145281.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +381,ml-metadata,google/ml-metadata,ml-experiments,,https://github.com/google/ml-metadata,https://github.com/google/ml-metadata,Apache-2.0,2019-01-15 21:02:09.000,2022-01-25 17:36:19.000000,2022-01-25 17:36:18,580.0,11.0,87,28.0,63.0,22.0,60.0,431,For recording and retrieving metadata associated with ML developer and data scientist workflows.,13.0,28,True,2022-01-21 02:25:26.000,1.6.0,33.0,ml-metadata,,,,,202.0,184.0,https://pypi.org/project/ml-metadata,2022-01-21 02:25:26.000,18.0,448572.0,448621.0,,,,,,,,3.0,1719.0,,,,,,,,,,,,,,,,,,,, +382,Cython BLIS,explosion/cython-blis,others,,https://github.com/explosion/cython-blis,https://github.com/explosion/cython-blis,BSD-3-Clause,2017-10-15 09:56:16.000,2022-01-27 18:30:25.000000,2022-01-27 18:18:39,533.0,2.0,31,10.0,36.0,6.0,23.0,182,Fast matrix-multiplication as a self-contained Python library no system dependencies!.,10.0,28,False,2021-10-27 09:16:31.000,0.7.5,36.0,blis,conda-forge/cython-blis,,,,15976.0,15751.0,https://pypi.org/project/blis,2021-10-22 08:50:51.000,225.0,3431786.0,3465589.0,https://anaconda.org/conda-forge/cython-blis,2021-11-04 20:09:22.632,1183126.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +383,Ciphey,Ciphey/Ciphey,nlp,,https://github.com/Ciphey/Ciphey,https://github.com/Ciphey/Ciphey,MIT,2019-07-16 20:20:39.000,2022-02-07 03:23:01.000000,2021-11-03 02:20:58,1873.0,,585,192.0,434.0,51.0,236.0,9423,"Automatically decrypt encryptions without knowing the key or cipher, decode encodings, and crack hashes.",46.0,27,True,2021-06-06 17:14:16.000,5.14.0,50.0,ciphey,,remnux/ciphey,,,,,https://pypi.org/project/ciphey,2021-06-06 17:13:48.000,,10854.0,11329.0,,,,https://hub.docker.com/r/remnux/ciphey,2022-02-05 15:31:24.752320,5.0,14733.0,2.0,,,,,,,,,,,,,,,,,,,,, +384,cortex,cortexlabs/cortex,model-serialisation,,https://github.com/cortexlabs/cortex,https://github.com/cortexlabs/cortex,Apache-2.0,2019-01-24 04:43:14.000,2022-02-06 23:26:20.000000,2022-02-06 23:25:14,2314.0,40.0,588,149.0,1344.0,105.0,979.0,7664,Production infrastructure for machine learning at scale.,24.0,27,True,2022-01-10 17:48:15.000,0.42.0,62.0,cortex,,,,,1.0,,https://pypi.org/project/cortex,2022-01-10 17:37:01.000,1.0,1240.0,1240.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +385,Facets Overview,pair-code/facets,data-viz,,https://github.com/PAIR-code/facets,https://github.com/PAIR-code/facets,Apache-2.0,2017-07-07 14:03:03.000,2021-11-29 10:48:23.000000,2021-05-06 12:01:05,264.0,,834,276.0,93.0,76.0,76.0,6772,Visualizations for machine learning datasets.,28.0,27,True,2019-07-24 15:57:06.000,1.0.0,4.0,facets-overview,,,,['jupyter'],105.0,101.0,https://pypi.org/project/facets-overview,2019-07-24 15:57:06.000,4.0,154544.0,154544.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +386,EfficientNet-PyTorch,lukemelas/EfficientNet-PyTorch,pytorch-utils,,https://github.com/lukemelas/EfficientNet-PyTorch,https://github.com/lukemelas/EfficientNet-PyTorch,Apache-2.0,2019-05-30 05:24:11.000,2021-11-02 08:10:31.000000,2021-04-15 15:16:36,162.0,,1348,127.0,50.0,133.0,134.0,6761,A PyTorch implementation of EfficientNet and EfficientNetV2 (coming soon!).,24.0,27,True,2021-04-15 15:17:23.000,0.7.1,13.0,efficientnet-pytorch,,,,['pytorch'],30.0,,https://pypi.org/project/efficientnet-pytorch,2021-04-15 15:17:23.000,30.0,788056.0,840245.0,,,,,,,,2.0,1200368.0,,,,,,,,,,,,,,,,,,,, +387,Trax,google/trax,others,,https://github.com/google/trax,https://github.com/google/trax,Apache-2.0,2019-10-05 15:09:14.000,2022-02-02 20:35:08.000000,2022-02-02 20:35:01,1592.0,4.0,678,150.0,1524.0,84.0,120.0,6757,Trax Deep Learning with Clear Code and Speed.,75.0,27,True,2021-10-26 20:29:38.000,1.4.1,24.0,trax,,,,,42.0,42.0,https://pypi.org/project/trax,2021-10-26 20:27:35.000,,3795.0,3795.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +388,Apex,NVIDIA/apex,gpu-utilities,,https://github.com/NVIDIA/apex,https://github.com/NVIDIA/apex,BSD-3-Clause,2018-04-23 16:28:52.000,2022-02-08 14:33:02.000000,2022-02-07 16:36:43,920.0,27.0,885,98.0,364.0,530.0,401.0,6064,A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch.,91.0,27,True,,,1.0,,conda-forge/nvidia-apex,,,['pytorch'],868.0,868.0,,,,,2622.0,https://anaconda.org/conda-forge/nvidia-apex,2021-04-22 16:13:47.237,73438.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +389,Face Alignment,1adrianb/face-alignment,image,,https://github.com/1adrianb/face-alignment,https://github.com/1adrianb/face-alignment,BSD-3-Clause,2017-09-15 20:32:44.000,2021-12-21 17:46:18.000000,2021-08-04 06:54:21,205.0,,1148,169.0,38.0,51.0,216.0,5518,2D and 3D Face alignment library build using pytorch.,23.0,27,True,2021-09-14 15:35:24.000,1.3.5,11.0,face-alignment,,,,['pytorch'],8.0,,https://pypi.org/project/face-alignment,2021-09-14 15:35:24.000,8.0,6974.0,6974.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +390,Augmentor,mdbloice/Augmentor,image,,https://github.com/mdbloice/Augmentor,https://github.com/mdbloice/Augmentor,MIT,2016-03-01 18:29:55.000,2021-10-15 05:38:50.000000,2021-10-15 05:38:50,537.0,,830,128.0,58.0,122.0,70.0,4626,Image augmentation library in Python for machine learning.,22.0,27,True,2021-10-14 08:49:48.000,0.2.9,21.0,Augmentor,,,,,433.0,404.0,https://pypi.org/project/Augmentor,2021-10-14 08:49:48.000,29.0,9780.0,9780.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +391,TensorTrade,tensortrade-org/tensortrade,financial-data,,https://github.com/tensortrade-org/tensortrade,https://github.com/tensortrade-org/tensortrade,Apache-2.0,2019-07-30 21:28:32.000,2022-02-10 08:20:50.000000,2022-02-10 08:20:50,997.0,66.0,843,238.0,181.0,25.0,185.0,3713,"An open source reinforcement learning framework for training, evaluating, and deploying robust trading agents.",60.0,27,True,2021-05-10 18:04:30.000,1.0.3,27.0,tensortrade,conda-forge/tensortrade,,,,31.0,30.0,https://pypi.org/project/tensortrade,2021-05-10 18:00:35.000,1.0,990.0,1083.0,https://anaconda.org/conda-forge/tensortrade,2021-05-10 20:10:14.115,939.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +392,pytorch-summary,sksq96/pytorch-summary,pytorch-utils,,https://github.com/sksq96/pytorch-summary,https://github.com/sksq96/pytorch-summary,MIT,2018-04-23 13:58:04.000,2021-06-20 09:40:21.000000,2021-05-10 18:34:53,57.0,,382,35.0,49.0,118.0,39.0,3391,Model summary in PyTorch similar to `model.summary()` in Keras.,11.0,27,True,2018-09-26 05:07:28.000,1.5.1,12.0,torchsummary,,,,['pytorch'],4295.0,4224.0,https://pypi.org/project/torchsummary,2018-09-26 05:07:28.000,71.0,63091.0,63091.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +393,vaderSentiment,cjhutto/vaderSentiment,nlp,,https://github.com/cjhutto/vaderSentiment,https://github.com/cjhutto/vaderSentiment,MIT,2014-11-17 16:31:45.000,2022-01-03 19:25:13.000000,2021-03-15 18:43:06,127.0,,834,142.0,28.0,33.0,74.0,3368,VADER Sentiment Analysis. VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based..,10.0,27,True,2020-05-22 15:07:00.000,3.3.2,15.0,vadersentiment,conda-forge/vadersentiment,,,,3631.0,3457.0,https://pypi.org/project/vadersentiment,2020-05-22 15:07:00.000,174.0,438183.0,438913.0,https://anaconda.org/conda-forge/vadersentiment,2021-03-22 07:41:03.629,8040.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +394,BentoML,bentoml/BentoML,model-serialisation,,https://github.com/bentoml/BentoML,https://github.com/bentoml/BentoML,Apache-2.0,2019-04-02 01:39:27.000,2022-02-10 13:02:55.000000,2022-02-08 17:29:17,1516.0,151.0,372,51.0,1595.0,46.0,488.0,3191,The Unified Model Serving Framework.,98.0,27,True,2021-07-13 10:52:52.000,0.13.1,57.0,bentoml,,,,,2.0,,https://pypi.org/project/bentoml,2022-01-28 09:45:10.000,2.0,12971.0,12998.0,,,,,,,,2.0,932.0,,,,,,,,-2.0,,,,,,,,,,,, +395,MMLSpark,microsoft/SynapseML,distributed-ml,,https://github.com/microsoft/SynapseML,https://github.com/microsoft/SynapseML,MIT,2017-06-05 08:23:44.000,2022-02-10 13:16:31.000000,2022-02-08 23:28:50,1040.0,70.0,635,133.0,881.0,231.0,304.0,3127,Simple and Distributed Machine Learning.,84.0,27,True,2022-01-12 22:42:34.000,0.9.5,23.0,mmlspark,,,,['spark'],,,https://pypi.org/project/mmlspark,2020-03-18 01:27:31.000,,46237.0,46237.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +396,TensorForce,tensorforce/tensorforce,reinforcement-learning,,https://github.com/tensorforce/tensorforce,https://github.com/tensorforce/tensorforce,Apache-2.0,2017-03-19 16:24:22.000,2022-02-10 08:43:13.000000,2022-02-10 08:43:04,2099.0,9.0,512,150.0,228.0,7.0,622.0,3086,Tensorforce: a TensorFlow library for applied reinforcement learning.,82.0,27,True,2021-08-30 20:20:58.000,0.6.5,14.0,tensorforce,,,,['tensorflow'],26.0,,https://pypi.org/project/tensorforce,2019-09-07 13:56:18.000,26.0,1905.0,1905.0,,,,,,,,3.0,,,,,,,,,-2.0,,,,,,,,,,,, +397,SHOGUN,shogun-toolbox/shogun,ml-frameworks,,https://github.com/shogun-toolbox/shogun,https://github.com/shogun-toolbox/shogun,BSD-3-Clause,2011-04-01 10:44:32.000,2022-01-18 22:03:55.000000,2020-12-08 16:56:38,17588.0,,1047,217.0,3648.0,437.0,1101.0,2868,Unified and efficient Machine Learning.,248.0,27,False,2019-07-05 10:23:31.000,shogun_6.1.4,10.0,,conda-forge/shogun,shogun/shogun,,,,,,,,,2019.0,https://anaconda.org/conda-forge/shogun,2018-06-25 20:49:17.070,110480.0,https://hub.docker.com/r/shogun/shogun,2019-01-31 13:45:10.435327,1.0,1477.0,3.0,,,,,,,,,,shogun,,,,,,,,,,, +398,Hummingbird,microsoft/hummingbird,model-serialisation,,https://github.com/microsoft/hummingbird,https://github.com/microsoft/hummingbird,MIT,2020-03-12 20:27:03.000,2022-02-09 19:44:18.000000,2022-02-09 19:28:35,365.0,10.0,209,48.0,336.0,54.0,181.0,2742,Hummingbird compiles trained ML models into tensor computation for faster inference.,28.0,27,True,2021-12-14 19:31:26.000,0.4.2,15.0,hummingbird-ml,conda-forge/hummingbird-ml,,,,20.0,20.0,https://pypi.org/project/hummingbird-ml,2021-12-14 19:28:14.000,,2033.0,2508.0,https://anaconda.org/conda-forge/hummingbird-ml,2021-12-14 21:22:58.497,5156.0,,,,,2.0,155.0,,,,,,,,,,,,,,,,,,,, +399,cuML,rapidsai/cuml,gpu-utilities,,https://github.com/rapidsai/cuml,https://github.com/rapidsai/cuml,Apache-2.0,2018-10-11 15:45:35.000,2022-02-10 06:57:53.000000,2022-02-10 00:20:46,14692.0,119.0,375,71.0,2630.0,656.0,1303.0,2562,cuML - RAPIDS Machine Learning Library.,146.0,27,True,2022-02-02 20:26:26.000,22.02.00,20.0,cuml,,,,,1.0,,https://pypi.org/project/cuml,2020-06-01 20:09:10.000,1.0,573.0,573.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +400,sklearn-pandas,scikit-learn-contrib/sklearn-pandas,data-containers,,https://github.com/scikit-learn-contrib/sklearn-pandas,https://github.com/scikit-learn-contrib/sklearn-pandas,Zlib,2013-04-22 22:55:20.000,2021-10-17 18:07:36.000000,2021-05-08 08:05:59,287.0,,393,94.0,103.0,25.0,127.0,2550,Pandas integration with sklearn.,37.0,27,False,2021-05-08 08:32:08.000,2.1.0,27.0,sklearn-pandas,conda-forge/sklearn-pandas,,,"['sklearn', 'pandas']",3670.0,3521.0,https://pypi.org/project/sklearn-pandas,2021-05-08 08:14:28.000,149.0,389244.0,389777.0,https://anaconda.org/conda-forge/sklearn-pandas,2021-05-08 14:16:36.778,8003.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +401,eli5,TeamHG-Memex/eli5,interpretability,,https://github.com/TeamHG-Memex/eli5,https://github.com/TeamHG-Memex/eli5,MIT,2016-09-15 01:04:57.000,2021-06-10 22:02:56.000000,2020-01-22 07:39:36,1198.0,,313,70.0,166.0,153.0,111.0,2498,A library for debugging/inspecting machine learning classifiers and explaining their predictions.,14.0,27,False,2021-01-23 14:25:24.000,0.11.0,28.0,eli5,conda-forge/eli5,,,,68.0,,https://pypi.org/project/eli5,2021-01-23 14:25:24.000,68.0,1063532.0,1065424.0,https://anaconda.org/conda-forge/eli5,2021-01-25 08:24:59.385,107847.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +402,neuralcoref,huggingface/neuralcoref,nlp,,https://github.com/huggingface/neuralcoref,https://github.com/huggingface/neuralcoref,MIT,2017-07-03 13:04:16.000,2022-01-09 22:09:47.000000,2021-06-22 10:51:48,116.0,,428,90.0,43.0,49.0,245.0,2478,Fast Coreference Resolution in spaCy with Neural Networks.,21.0,27,True,2019-04-08 11:28:27.000,4.0.0,5.0,neuralcoref,conda-forge/neuralcoref,,,,458.0,444.0,https://pypi.org/project/neuralcoref,2019-04-08 09:56:00.000,14.0,54635.0,55082.0,https://anaconda.org/conda-forge/neuralcoref,2020-02-21 22:10:40.453,10609.0,,,,,2.0,308.0,,,,,,,,,,,,,,,,,,,, +403,PARL,PaddlePaddle/PARL,reinforcement-learning,,https://github.com/PaddlePaddle/PARL,https://github.com/PaddlePaddle/PARL,Apache-2.0,2018-04-25 17:54:22.000,2022-02-09 08:13:50.000000,2022-02-09 07:27:47,421.0,12.0,618,55.0,493.0,71.0,236.0,2417,A high-performance distributed training framework for Reinforcement Learning.,29.0,27,True,2021-12-30 06:45:32.000,2.0.3,23.0,parl,,,,['paddle'],86.0,86.0,https://pypi.org/project/parl,2021-12-30 06:45:32.000,,534.0,534.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +404,TF Ranking,tensorflow/ranking,recommender-systems,,https://github.com/tensorflow/ranking,https://github.com/tensorflow/ranking,Apache-2.0,2018-12-03 20:48:57.000,2021-11-22 21:37:02.000000,2021-11-22 21:36:59,442.0,15.0,411,93.0,31.0,50.0,233.0,2410,Learning to Rank in TensorFlow.,25.0,27,True,2021-11-16 23:49:54.000,0.5.0,19.0,tensorflow_ranking,,,,['tensorflow'],11.0,,https://pypi.org/project/tensorflow_ranking,2021-11-16 01:31:58.000,11.0,44968.0,44968.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +405,Alphalens,quantopian/alphalens,financial-data,,https://github.com/quantopian/alphalens,https://github.com/quantopian/alphalens,Apache-2.0,2016-06-03 21:49:15.000,2021-12-05 06:35:06.000000,2020-04-27 18:40:41,522.0,,817,161.0,213.0,38.0,145.0,2189,Performance analysis of predictive (alpha) stock factors.,25.0,27,False,2020-04-30 15:42:52.000,0.4.0,10.0,alphalens,conda-forge/alphalens,,,,512.0,495.0,https://pypi.org/project/alphalens,2020-04-27 21:03:10.000,17.0,2321.0,2617.0,https://anaconda.org/conda-forge/alphalens,2020-05-16 13:52:44.922,14246.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +406,accelerate,huggingface/accelerate,pytorch-utils,,https://github.com/huggingface/accelerate,https://github.com/huggingface/accelerate,Apache-2.0,2020-10-30 13:27:12.000,2022-02-10 15:01:07.000000,2022-02-08 19:05:38,220.0,9.0,133,45.0,86.0,60.0,105.0,2181,"A simple way to train and use PyTorch models with multi-GPU, TPU, mixed-precision.",32.0,27,True,2021-09-27 15:05:40.000,0.5.1,8.0,accelerate,conda-forge/accelerate,,,['pytorch'],314.0,310.0,https://pypi.org/project/accelerate,2021-09-27 15:04:05.000,4.0,47994.0,48194.0,https://anaconda.org/conda-forge/accelerate,2021-10-11 19:33:56.979,803.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +407,vidgear,abhiTronix/vidgear,image,,https://github.com/abhiTronix/vidgear,https://github.com/abhiTronix/vidgear,Apache-2.0,2019-03-17 02:42:42.000,2022-02-10 09:28:28.000000,2021-12-05 10:14:09,826.0,26.0,159,51.0,84.0,5.0,193.0,2106,A High-performance cross-platform Video Processing Python framework powerpacked with unique trailblazing features.,9.0,27,True,2021-12-05 13:04:13.000,0.2.4,16.0,vidgear,,,,,170.0,167.0,https://pypi.org/project/vidgear,2021-12-05 13:04:13.000,3.0,4404.0,4418.0,,,,,,,,3.0,524.0,,,,,,,,,,,,,,,,,,,, +408,efficientnet,qubvel/efficientnet,tensorflow-utils,,https://github.com/qubvel/efficientnet,https://github.com/qubvel/efficientnet,Apache-2.0,2019-05-30 20:21:09.000,2022-01-14 10:29:02.172000,2021-07-16 09:03:20,66.0,,438,37.0,41.0,59.0,56.0,1937,Implementation of EfficientNet model. Keras and TensorFlow Keras.,10.0,27,True,2020-09-15 16:26:00.000,1.1.1,9.0,efficientnet,anaconda/efficientnet,,,['tensorflow'],892.0,885.0,https://pypi.org/project/efficientnet,2020-09-15 16:26:00.000,7.0,78794.0,84899.0,https://anaconda.org/anaconda/efficientnet,2022-01-14 10:29:02.172,15.0,,,,,3.0,201461.0,,,,,,,,,,,,,,,,,,,, +409,langid,saffsd/langid.py,nlp,,https://github.com/saffsd/langid.py,https://github.com/saffsd/langid.py,BSD-3-Clause,2011-04-29 00:16:56.000,2020-01-01 10:49:30.000000,2017-07-15 02:49:17,242.0,,277,65.0,14.0,26.0,45.0,1914,Stand-alone language identification system.,9.0,27,False,2016-04-05 22:34:15.000,1.1.6,8.0,langid,,,,,1073.0,909.0,https://pypi.org/project/langid,2016-04-05 22:34:15.000,164.0,332250.0,332250.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +410,mljar-supervised,mljar/mljar-supervised,hyperopt,,https://github.com/mljar/mljar-supervised,https://github.com/mljar/mljar-supervised,MIT,2018-11-05 12:58:04.000,2021-12-06 08:40:00.000000,2021-12-06 08:40:00,983.0,11.0,246,34.0,40.0,81.0,376.0,1774,"Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and..",14.0,27,True,2021-10-01 07:25:05.000,0.11.1,75.0,mljar-supervised,conda-forge/mljar-supervised,,,,36.0,36.0,https://pypi.org/project/mljar-supervised,2021-10-01 07:25:05.000,,25042.0,25167.0,https://anaconda.org/conda-forge/mljar-supervised,2021-12-03 11:27:41.724,1006.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +411,zenml,zenml-io/zenml,data-pipelines,,https://github.com/zenml-io/zenml,https://github.com/zenml-io/zenml,Apache-2.0,2020-11-19 09:25:46.000,2022-02-10 14:56:20.000000,2022-02-08 13:48:35,4212.0,1235.0,101,29.0,336.0,10.0,48.0,1647,ZenML : MLOps framework to create reproducible pipelines.,24.0,27,True,2022-02-07 14:51:21.000,0.6.1,46.0,zenml,,,,,,,https://pypi.org/project/zenml,2022-02-07 14:51:21.000,,1347.0,1347.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +412,tesserocr,sirfz/tesserocr,ocr,,https://github.com/sirfz/tesserocr,https://github.com/sirfz/tesserocr,MIT,2015-12-17 23:29:36.000,2021-11-09 18:12:48.000000,2021-11-09 18:12:47,178.0,,206,53.0,58.0,76.0,160.0,1592,A Python wrapper for the tesseract-ocr API.,26.0,27,True,2021-06-19 21:10:18.000,2.5.2,16.0,tesserocr,conda-forge/tesserocr,,,,671.0,610.0,https://pypi.org/project/tesserocr,2021-06-19 21:10:18.000,61.0,51905.0,54190.0,https://anaconda.org/conda-forge/tesserocr,2021-01-13 16:38:14.456,63986.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +413,TensorFlow Privacy,tensorflow/privacy,privacy-ml,,https://github.com/tensorflow/privacy,https://github.com/tensorflow/privacy,Apache-2.0,2018-12-21 18:46:46.000,2022-02-09 01:45:46.000000,2022-02-09 01:45:45,600.0,48.0,332,62.0,43.0,62.0,86.0,1545,Library for training machine learning models with privacy for training data.,44.0,27,True,2021-09-01 02:54:34.000,0.7.3,17.0,tensorflow-privacy,,,,['tensorflow'],6.0,,https://pypi.org/project/tensorflow-privacy,2021-09-01 02:54:34.000,6.0,31362.0,31364.0,,,,,,,,2.0,62.0,,,,,,,,,,,,,,,,,,,, +414,chainercv,chainer/chainercv,image,,https://github.com/chainer/chainercv,https://github.com/chainer/chainercv,MIT,2017-02-13 04:15:10.000,2021-07-01 16:54:50.000000,2020-01-07 11:48:31,4930.0,,318,74.0,742.0,54.0,168.0,1469,ChainerCV: a Library for Deep Learning in Computer Vision.,39.0,27,False,2019-06-12 11:55:02.000,0.13.1,24.0,chainercv,,,,,310.0,279.0,https://pypi.org/project/chainercv,2019-06-12 11:55:40.000,31.0,3017.0,3017.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +415,bt,pmorissette/bt,financial-data,,https://github.com/pmorissette/bt,https://github.com/pmorissette/bt,MIT,2014-06-19 16:06:28.000,2022-02-09 19:37:26.000000,2022-02-09 19:37:21,453.0,15.0,297,78.0,75.0,50.0,225.0,1304,bt - flexible backtesting for Python.,25.0,27,True,2021-04-21 02:52:26.000,0.2.9,25.0,bt,conda-forge/bt,,,,114.0,93.0,https://pypi.org/project/bt,2021-04-21 02:52:26.000,21.0,5845.0,6131.0,https://anaconda.org/conda-forge/bt,2022-01-18 18:09:55.903,2869.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +416,Optimus,hi-primus/optimus,data-pipelines,,https://github.com/hi-primus/optimus,https://github.com/hi-primus/optimus,Apache-2.0,2017-07-13 02:31:18.000,2022-02-09 23:29:11.000000,2022-02-07 14:02:59,6223.0,120.0,205,38.0,993.0,32.0,195.0,1181,"Agile Data Preparation Workflows madeeasy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark.",25.0,27,True,2020-07-19 03:05:40.000,2.2.32,85.0,optimuspyspark,,,,['spark'],,,https://pypi.org/project/optimuspyspark,2019-05-30 02:22:54.000,,21403.0,21403.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +417,Opacus,pytorch/opacus,privacy-ml,,https://github.com/pytorch/opacus,https://github.com/pytorch/opacus,Apache-2.0,2019-12-07 01:58:09.000,2022-02-10 13:52:50.948000,2022-02-10 01:50:23,585.0,165.0,176,40.0,222.0,26.0,113.0,1038,Training PyTorch models with differential privacy.,42.0,27,True,2022-02-09 23:25:58.000,1.0.2,13.0,opacus,conda-forge/opacus,,,['pytorch'],85.0,74.0,https://pypi.org/project/opacus,2022-02-09 23:25:58.000,11.0,4598.0,4682.0,https://anaconda.org/conda-forge/opacus,2022-02-10 13:52:50.948,82.0,,,,,2.0,42.0,,,,,,,,,,,,,,,,,,,, +418,pandera,pandera-dev/pandera,data-containers,,https://github.com/pandera-dev/pandera,https://github.com/pandera-dev/pandera,MIT,2018-11-01 02:18:34.000,2022-02-10 13:41:58.000000,2022-02-08 16:44:51,395.0,29.0,82,9.0,362.0,81.0,276.0,1037,"A light-weight, flexible, and expressive data validation library for dataframes.",48.0,27,True,2022-02-09 00:35:30.000,0.9.0,42.0,pandera,conda-forge/pandera-core,,,['pandas'],172.0,154.0,https://pypi.org/project/pandera,2022-02-09 00:35:30.000,18.0,163555.0,163919.0,https://anaconda.org/conda-forge/pandera-core,2021-12-31 23:43:50.285,5834.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, +419,kmodes,nicodv/kmodes,others,,https://github.com/nicodv/kmodes,https://github.com/nicodv/kmodes,MIT,2013-08-01 11:54:40.000,2022-01-26 20:23:36.261000,2021-12-15 19:40:41,472.0,2.0,365,53.0,30.0,16.0,122.0,966,"Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data.",20.0,27,True,2021-10-08 04:41:31.000,0.11.1,14.0,kmodes,conda-forge/kmodes,,,,1013.0,987.0,https://pypi.org/project/kmodes,2021-10-08 04:35:56.000,26.0,306963.0,307231.0,https://anaconda.org/conda-forge/kmodes,2022-01-26 20:23:36.261,5916.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +420,pyclustering,annoviko/pyclustering,others,,https://github.com/annoviko/pyclustering,https://github.com/annoviko/pyclustering,BSD-3-Clause,2014-02-25 18:59:03.000,2022-01-06 03:33:52.000000,2021-02-12 19:04:59,2079.0,,216,38.0,33.0,58.0,589.0,922,"pyclustring is a Python, C++ data mining library.",26.0,27,True,2020-11-25 22:33:07.000,0.10.1.2,46.0,pyclustering,conda-forge/pyclustering,,,,300.0,272.0,https://pypi.org/project/pyclustering,2020-11-25 22:41:20.000,28.0,42756.0,44056.0,https://anaconda.org/conda-forge/pyclustering,2021-09-13 14:29:08.300,33663.0,,,,,3.0,391.0,,,,,,,,,,,,,,,,,,,, +421,Madmom,CPJKU/madmom,audio,,https://github.com/CPJKU/madmom,https://github.com/CPJKU/madmom,BSD-3-Clause,2015-09-08 08:19:06.000,2022-01-26 19:41:50.000000,2022-01-06 15:08:19,1746.0,18.0,149,37.0,251.0,54.0,201.0,865,Python audio and music signal processing library.,20.0,27,True,2018-11-14 14:57:41.000,0.16.1,11.0,madmom,,,,,203.0,176.0,https://pypi.org/project/madmom,2018-11-14 14:56:22.000,27.0,7633.0,7633.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +422,mahotas,luispedro/mahotas,image,,https://github.com/luispedro/mahotas,https://github.com/luispedro/mahotas,MIT,2010-01-31 00:13:06.000,2021-12-07 00:42:53.000000,2021-12-07 00:42:43,1286.0,2.0,139,46.0,53.0,16.0,61.0,733,Computer Vision in Python.,32.0,27,True,2021-10-14 12:53:24.000,1.4.12,58.0,mahotas,conda-forge/mahotas,,,,864.0,753.0,https://pypi.org/project/mahotas,2021-10-14 12:53:24.000,111.0,10562.0,14941.0,https://anaconda.org/conda-forge/mahotas,2021-11-17 20:03:30.117,310969.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +423,SMAC3,automl/SMAC3,hyperopt,,https://github.com/automl/SMAC3,https://github.com/automl/SMAC3,BSD-3-Clause,2016-08-17 10:58:05.000,2022-02-10 10:33:15.000000,2021-11-05 09:44:04,2048.0,,170,41.0,459.0,67.0,292.0,659,Sequential Model-based Algorithm Configuration.,38.0,27,True,2022-01-27 08:26:44.000,1.1.1,34.0,smac,conda-forge/smac,,,,32.0,,https://pypi.org/project/smac,2021-11-05 10:44:49.000,32.0,22622.0,22824.0,https://anaconda.org/conda-forge/smac,2021-10-21 10:00:48.137,2222.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +424,mpi4py,mpi4py/mpi4py,distributed-ml,,https://github.com/mpi4py/mpi4py,https://github.com/mpi4py/mpi4py,BSD-2-Clause,2013-09-05 14:44:25.000,2022-02-01 14:40:15.000000,2022-01-26 02:00:28,2457.0,24.0,74,12.0,82.0,13.0,51.0,504,Python bindings for MPI.,20.0,27,True,2021-11-25 21:07:13.000,3.1.3,20.0,mpi4py,conda-forge/mpi4py,,,,582.0,,https://pypi.org/project/mpi4py,2021-12-15 13:48:39.969,582.0,162397.0,176660.0,https://anaconda.org/conda-forge/mpi4py,2021-11-25 23:30:14.783,915955.0,,,,,3.0,3286.0,,,,,,,,,,,,,,,,,,,, +425,tinytag,devsnd/tinytag,audio,,https://github.com/devsnd/tinytag,https://github.com/devsnd/tinytag,MIT,2014-01-27 15:27:01.000,2021-12-18 23:42:08.000000,2021-12-17 13:19:46,345.0,16.0,87,22.0,48.0,12.0,75.0,500,"Read audio and music meta data and duration of MP3, OGG, OPUS, MP4, M4A, FLAC, WMA, Wave and AIFF files with python 2..",21.0,27,True,2021-12-14 11:17:28.000,1.7.0,35.0,tinytag,,,,,544.0,477.0,https://pypi.org/project/tinytag,2021-12-14 11:17:28.000,67.0,26087.0,26087.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +426,Orion,Epistimio/orion,hyperopt,,https://github.com/Epistimio/orion,https://github.com/Epistimio/orion,BSD-3-Clause,2017-09-07 06:05:21.000,2022-02-09 23:21:15.000000,2022-02-09 15:28:44,3114.0,100.0,44,13.0,524.0,107.0,151.0,215,Asynchronous Distributed Hyperparameter Optimization.,25.0,27,False,2021-11-26 18:02:35.000,0.2.1,20.0,orion,,,,,57.0,51.0,https://pypi.org/project/orion,2021-11-26 18:02:35.000,6.0,4710.0,4710.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +427,PyStan,stan-dev/pystan,probabilistics,,https://github.com/stan-dev/pystan,https://github.com/stan-dev/pystan,ISC,2017-03-06 19:56:42.094,2022-02-03 10:06:49.622000,2021-10-21 11:47:11,189.0,,36,10.0,174.0,10.0,152.0,156,"PyStan, a Python interface to Stan, a platform for statistical modeling. Documentation: https://pystan.readthedocs.io.",10.0,27,False,2021-10-06 01:05:34.000,3.3.0,65.0,pystan,conda-forge/pystan,,,,243.0,,https://pypi.org/project/pystan,2021-10-06 01:05:34.000,243.0,2086899.0,2110212.0,https://anaconda.org/conda-forge/pystan,2022-02-03 10:06:49.622,1375477.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +428,english-words,dwyl/english-words,nlp,,https://github.com/dwyl/english-words,https://github.com/dwyl/english-words,Unlicense,2014-07-13 22:20:45.000,2022-01-31 12:20:23.000000,2021-10-20 08:05:51,85.0,,1287,182.0,50.0,45.0,28.0,6476,A text file containing 479k English words for all your dictionary/word-based projects e.g: auto-completion /..,26.0,26,True,2022-01-29 05:49:51.000,1.1.0,7.0,english-words,,,,,6.0,,https://pypi.org/project/english-words,2022-01-29 05:49:51.000,6.0,17354.0,17354.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +429,MMF,facebookresearch/mmf,image,,https://github.com/facebookresearch/mmf,https://github.com/facebookresearch/mmf,BSD-3-Clause,2018-06-27 04:52:40.000,2022-02-07 21:29:54.000000,2022-02-02 01:43:48,1025.0,47.0,793,111.0,620.0,189.0,418.0,4783,A modular framework for vision & language multimodal research from Facebook AI Research (FAIR).,90.0,26,True,2019-08-26 19:04:21.000,0.3.1,12.0,mmf,,,,['pytorch'],11.0,10.0,https://pypi.org/project/mmf,2020-06-12 22:15:02.000,1.0,578.0,578.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +430,Lucid,tensorflow/lucid,interpretability,,https://github.com/tensorflow/lucid,https://github.com/tensorflow/lucid,Apache-2.0,2018-01-25 17:41:44.000,2021-07-02 01:49:08.000000,2021-03-19 15:48:33,667.0,,592,160.0,127.0,70.0,100.0,4362,A collection of infrastructure and tools for research in neural network interpretability.,40.0,26,True,2021-03-19 16:01:00.000,0.3.10,17.0,lucid,,,,['tensorflow'],606.0,600.0,https://pypi.org/project/lucid,2021-03-19 16:01:00.000,6.0,1495.0,1495.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +431,AugLy,facebookresearch/AugLy,others,,https://github.com/facebookresearch/AugLy,https://github.com/facebookresearch/AugLy,MIT,2021-06-09 17:57:28.000,2022-02-10 13:00:20.000000,2022-02-01 11:00:57,151.0,43.0,217,60.0,139.0,14.0,42.0,4292,"A data augmentations library for audio, image, text, and video.",15.0,26,True,2021-12-17 11:57:25.000,0.2.1,16.0,augly,,,,,28.0,25.0,https://pypi.org/project/augly,2021-12-17 11:46:02.000,3.0,1864.0,1864.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +432,TensorFlowOnSpark,yahoo/TensorFlowOnSpark,distributed-ml,,https://github.com/yahoo/TensorFlowOnSpark,https://github.com/yahoo/TensorFlowOnSpark,Apache-2.0,2017-01-20 18:15:57.000,2022-01-20 15:05:09.000000,2022-01-10 17:58:10,629.0,1.0,959,286.0,220.0,6.0,354.0,3756,TensorFlowOnSpark brings TensorFlow programs to Apache Spark clusters.,34.0,26,True,2021-05-25 22:25:31.000,2.2.4,31.0,tensorflowonspark,conda-forge/tensorflowonspark,,,"['tensorflow', 'spark']",5.0,,https://pypi.org/project/tensorflowonspark,2021-05-25 20:44:29.000,5.0,440401.0,440772.0,https://anaconda.org/conda-forge/tensorflowonspark,2020-12-19 17:56:07.960,9665.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +433,ArrayFire,arrayfire/arrayfire,gpu-utilities,,https://github.com/arrayfire/arrayfire,https://github.com/arrayfire/arrayfire,BSD-3-Clause,2014-10-28 20:58:33.000,2022-02-08 19:40:46.000000,2022-02-07 20:20:56,5777.0,1.0,492,151.0,1715.0,232.0,1267.0,3745,ArrayFire: a general purpose GPU library.,81.0,26,True,2022-01-18 20:00:02.000,3.8.1,31.0,arrayfire,,,,,5.0,,https://pypi.org/project/arrayfire,2021-03-05 17:36:30.000,5.0,567.0,591.0,,,,,,,,2.0,1969.0,,,,,,,,,,,,,,,,,,,, +434,yellowbrick,DistrictDataLabs/yellowbrick,interpretability,,https://github.com/DistrictDataLabs/yellowbrick,https://github.com/DistrictDataLabs/yellowbrick,Apache-2.0,2016-05-18 14:12:17.000,2022-01-25 11:10:14.000000,2022-01-05 19:25:56,862.0,1.0,497,107.0,576.0,95.0,547.0,3498,Visual analysis and diagnostic tools to facilitate machine learning model selection.,102.0,26,True,2021-02-13 20:31:18.000,1.3.post1,22.0,yellowbrick,conda-forge/yellowbrick,,,['sklearn'],47.0,,https://pypi.org/project/yellowbrick,2021-02-13 20:42:26.000,47.0,349916.0,351026.0,https://anaconda.org/conda-forge/yellowbrick,2021-05-06 19:15:50.988,19990.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +435,SynapseML,microsoft/SynapseML,distributed-ml,,https://github.com/microsoft/SynapseML,https://github.com/microsoft/SynapseML,MIT,2017-06-05 08:23:44.000,2022-02-10 13:16:31.000000,2022-02-08 23:28:50,1040.0,70.0,635,133.0,881.0,231.0,304.0,3127,Simple and Distributed Machine Learning.,84.0,26,True,2022-01-12 22:50:41.000,0.9.5,23.0,synapseml,,,,,,,https://pypi.org/project/synapseml,2022-01-12 22:50:41.000,,5063.0,5063.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, +436,keras-vis,raghakot/keras-vis,interpretability,,https://github.com/raghakot/keras-vis,https://github.com/raghakot/keras-vis,MIT,2016-11-11 23:27:34.000,2022-02-07 16:06:07.000000,2020-04-20 01:03:12,195.0,,618,71.0,25.0,114.0,101.0,2912,Neural network visualization toolkit for keras.,10.0,26,False,2017-07-06 04:55:04.000,0.4.1,11.0,keras-vis,,,,['tensorflow'],1641.0,1612.0,https://pypi.org/project/keras-vis,2017-07-06 04:55:04.000,29.0,3273.0,3273.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +437,scikit-opt,guofei9987/scikit-opt,sklearn-utils,,https://github.com/guofei9987/scikit-opt,https://github.com/guofei9987/scikit-opt,MIT,2017-12-05 10:20:41.000,2022-01-18 06:34:34.000000,2022-01-16 06:34:19,314.0,11.0,696,35.0,22.0,30.0,101.0,2908,"Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization Algorithm,Immune..",14.0,26,True,2022-01-14 08:49:08.000,0.6.6,23.0,scikit-opt,,,,['sklearn'],65.0,59.0,https://pypi.org/project/scikit-opt,2022-01-14 08:49:08.000,6.0,1224.0,1224.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +438,DeepVariant,google/deepvariant,medical-data,,https://github.com/google/deepvariant,https://github.com/google/deepvariant,BSD-3-Clause,2017-11-23 01:56:22.000,2022-01-28 17:53:43.000000,2022-01-28 17:30:19,1842.0,37.0,584,161.0,51.0,7.0,457.0,2431,DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA..,21.0,26,True,2021-12-10 07:12:31.000,1.3.0,17.0,,bioconda/deepvariant,,,['tensorflow'],,,,,,,839.0,https://anaconda.org/bioconda/deepvariant,2021-12-16 06:56:52.044,37458.0,,,,,3.0,3778.0,,,,,,,,,,,,,,,,,,,, +439,scikit-plot,reiinakano/scikit-plot,interpretability,,https://github.com/reiinakano/scikit-plot,https://github.com/reiinakano/scikit-plot,MIT,2017-02-04 06:22:59.000,2021-08-11 23:58:11.000000,2018-08-19 12:37:47,130.0,,257,66.0,57.0,21.0,39.0,2173,An intuitive library to add plotting functionality to scikit-learn objects.,13.0,26,False,2018-08-19 12:21:01.000,0.3.7,27.0,scikit-plot,conda-forge/scikit-plot,,,['sklearn'],1716.0,1676.0,https://pypi.org/project/scikit-plot,2018-08-19 12:18:46.000,40.0,325990.0,327900.0,https://anaconda.org/conda-forge/scikit-plot,2019-06-05 14:23:59.043,105075.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +440,Hyperas,maxpumperla/hyperas,hyperopt,,https://github.com/maxpumperla/hyperas,https://github.com/maxpumperla/hyperas,MIT,2016-02-19 14:45:10.000,2021-11-19 13:23:59.000000,2021-11-19 13:23:56,211.0,2.0,305,61.0,37.0,92.0,158.0,2113,Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization.,21.0,26,True,2019-02-28 09:16:54.000,0.4.1,9.0,hyperas,,,,['tensorflow'],249.0,225.0,https://pypi.org/project/hyperas,2019-02-28 09:16:54.000,24.0,12452.0,12452.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +441,DDSP,magenta/ddsp,audio,,https://github.com/magenta/ddsp,https://github.com/magenta/ddsp,Apache-2.0,2020-01-14 18:38:27.000,2022-02-10 04:47:20.000000,2022-02-10 00:15:21,429.0,14.0,218,59.0,270.0,22.0,107.0,2060,DDSP: Differentiable Digital Signal Processing.,29.0,26,True,2022-02-10 03:10:14.000,3.1.0,40.0,ddsp,conda-forge/ddsp,,,['tensorflow'],20.0,19.0,https://pypi.org/project/ddsp,2021-12-24 01:00:12.000,1.0,2013.0,2517.0,https://anaconda.org/conda-forge/ddsp,2020-06-08 12:59:15.975,10098.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +442,PandaralΒ·lel,nalepae/pandarallel,data-containers,,https://github.com/nalepae/pandarallel,https://github.com/nalepae/pandarallel,BSD-3-Clause,2019-03-10 11:58:29.000,2022-02-06 21:20:11.447000,2022-02-06 17:22:28,131.0,3.0,131,21.0,23.0,79.0,67.0,2011,A simple and efficient tool to parallelize Pandas operations on all availableCPUs.,19.0,26,True,2022-02-06 17:25:48.000,1.5.5,32.0,pandarallel,conda-forge/pandarallel,,,"['pandas', 'jupyter']",414.0,395.0,https://pypi.org/project/pandarallel,2022-02-06 17:24:12.000,19.0,222571.0,222760.0,https://anaconda.org/conda-forge/pandarallel,2022-02-06 21:20:11.447,1512.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +443,PyFunctional,EntilZha/PyFunctional,data-pipelines,,https://github.com/EntilZha/PyFunctional,https://github.com/EntilZha/PyFunctional,MIT,2015-02-05 17:17:51.000,2021-11-26 14:50:52.000000,2021-11-05 18:58:53,520.0,,107,52.0,43.0,7.0,119.0,1968,Python library for creating data pipelines with chain functional programming.,25.0,26,True,2021-01-12 19:21:07.000,1.4.3,14.0,pyfunctional,,,,,404.0,392.0,https://pypi.org/project/pyfunctional,2021-01-12 19:14:48.000,12.0,86346.0,86346.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +444,polyglot,aboSamoor/polyglot,nlp,,https://github.com/aboSamoor/polyglot,https://github.com/aboSamoor/polyglot,GPL-3.0,2014-06-30 02:07:45.000,2021-04-28 03:41:03.000000,2020-09-22 22:35:28,271.0,,310,80.0,49.0,147.0,64.0,1954,Multilingual text (NLP) processing toolkit.,26.0,26,False,2016-07-03 20:05:42.000,16.7.4,9.0,polyglot,,,,,728.0,644.0,https://pypi.org/project/polyglot,2016-07-03 20:05:42.000,84.0,65769.0,65769.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +445,HyperTools,ContextLab/hypertools,data-viz,,https://github.com/ContextLab/hypertools,https://github.com/ContextLab/hypertools,MIT,2016-09-27 21:31:25.000,2022-02-09 01:58:35.000000,2022-02-09 01:58:35,1603.0,4.0,154,58.0,63.0,68.0,123.0,1688,A Python toolbox for gaining geometric insights into high-dimensional data.,21.0,26,True,2021-06-15 19:22:37.000,0.7.0,20.0,hypertools,,,,,172.0,163.0,https://pypi.org/project/hypertools,2021-06-15 19:22:37.000,9.0,1462.0,1462.0,,,,,,,,3.0,8.0,,,,,,,,,,,,,,,,,,,, +446,Talos,autonomio/talos,hyperopt,,https://github.com/autonomio/talos,https://github.com/autonomio/talos,MIT,2018-05-04 20:36:41.000,2022-01-28 21:40:46.000000,2022-01-28 20:18:57,568.0,9.0,247,29.0,163.0,35.0,365.0,1493,"Hyperparameter Optimization for TensorFlow, Keras and PyTorch.",21.0,26,True,2022-01-28 21:35:50.000,1.0.2,15.0,talos,,,,['tensorflow'],141.0,135.0,https://pypi.org/project/talos,2022-01-28 21:35:50.000,6.0,1087.0,1087.0,,,,,,,,2.0,,,,,,,,,4.0,,,,,,,,,,,, +447,lightly,lightly-ai/lightly,image,,https://github.com/lightly-ai/lightly,https://github.com/lightly-ai/lightly,MIT,2020-10-13 13:02:56.000,2022-02-10 09:55:27.000000,2022-02-10 08:54:37,622.0,95.0,97,24.0,393.0,65.0,235.0,1460,A python library for self-supervised learning on images.,14.0,26,True,2022-02-08 09:45:25.000,1.2.6,42.0,lightly,,,,['pytorch'],29.0,28.0,https://pypi.org/project/lightly,2022-02-08 09:47:14.000,1.0,2790.0,2790.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +448,metric-learn,scikit-learn-contrib/metric-learn,others,,https://github.com/scikit-learn-contrib/metric-learn,https://github.com/scikit-learn-contrib/metric-learn,MIT,2013-11-02 08:29:47.000,2021-12-29 13:03:59.000000,2021-11-17 13:54:36,280.0,1.0,216,49.0,177.0,52.0,117.0,1213,Metric learning algorithms in Python.,21.0,26,True,2020-07-02 12:59:23.000,0.6.2,10.0,metric-learn,conda-forge/metric-learn,,,['sklearn'],197.0,186.0,https://pypi.org/project/metric-learn,2020-07-02 12:59:23.000,11.0,9923.0,10153.0,https://anaconda.org/conda-forge/metric-learn,2020-07-02 13:51:25.681,5306.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +449,Paddle Graph Learning,PaddlePaddle/PGL,graph,,https://github.com/PaddlePaddle/PGL,https://github.com/PaddlePaddle/PGL,Apache-2.0,2019-06-11 03:23:28.000,2021-12-29 06:30:55.000000,2021-12-29 04:06:09,1035.0,104.0,195,25.0,266.0,38.0,67.0,1212,Paddle Graph Learning (PGL) is an efficient and flexible graph learning framework based on PaddlePaddle.,21.0,26,True,2021-12-29 04:02:35.000,2.2.2,16.0,pgl,,,,['paddle'],26.0,24.0,https://pypi.org/project/pgl,2021-12-20 02:21:36.000,2.0,981.0,981.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +450,Mesh,tensorflow/mesh,distributed-ml,,https://github.com/tensorflow/mesh,https://github.com/tensorflow/mesh,Apache-2.0,2018-09-20 20:23:34.000,2022-02-08 18:49:39.000000,2022-01-26 06:06:30,646.0,3.0,200,40.0,297.0,88.0,14.0,1195,Mesh TensorFlow: Model Parallelism Made Easier.,45.0,26,True,2021-03-24 19:03:46.000,0.1.19,25.0,mesh-tensorflow,,,,['tensorflow'],660.0,628.0,https://pypi.org/project/mesh-tensorflow,2021-03-24 19:03:46.000,32.0,52742.0,52742.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +451,fairlearn,fairlearn/fairlearn,interpretability,,https://github.com/fairlearn/fairlearn,https://github.com/fairlearn/fairlearn,MIT,2018-05-15 01:51:35.000,2022-02-10 11:59:23.000000,2022-01-31 10:13:56,666.0,10.0,283,34.0,661.0,134.0,200.0,1188,A Python package to assess and improve fairness of machine learning models.,63.0,26,True,2021-07-07 08:16:09.000,0.7.0,16.0,fairlearn,conda-forge/fairlearn,,,['sklearn'],9.0,,https://pypi.org/project/fairlearn,2021-07-07 05:54:23.000,9.0,55883.0,56584.0,https://anaconda.org/conda-forge/fairlearn,2021-07-07 15:56:16.605,16827.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +452,alibi-detect,SeldonIO/alibi-detect,others,,https://github.com/SeldonIO/alibi-detect,https://github.com/SeldonIO/alibi-detect,Apache-2.0,2019-10-07 13:29:13.000,2022-02-10 12:38:46.000000,2022-02-04 09:30:48,455.0,34.0,118,32.0,241.0,85.0,131.0,1139,"Algorithms for outlier, adversarial and drift detection.",15.0,26,True,2022-01-18 12:02:20.000,0.8.1,21.0,alibi-detect,,,,,63.0,58.0,https://pypi.org/project/alibi-detect,2022-01-18 11:59:16.000,5.0,11111.0,11111.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +453,spacy-transformers,explosion/spacy-transformers,nlp,,https://github.com/explosion/spacy-transformers,https://github.com/explosion/spacy-transformers,MIT,2019-07-26 19:12:34.000,2022-01-20 09:38:28.000000,2022-01-13 16:22:08,1387.0,7.0,136,27.0,154.0,,,1079,"Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy.",18.0,26,True,2022-01-14 07:37:40.000,1.1.4,58.0,spacy-transformers,conda-forge/spacy-transformers,,,['spacy'],401.0,388.0,https://pypi.org/project/spacy-transformers,2022-01-14 07:37:28.000,13.0,87328.0,87453.0,https://anaconda.org/conda-forge/spacy-transformers,2022-01-14 10:03:56.640,375.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +454,fancyimpute,iskandr/fancyimpute,sklearn-utils,,https://github.com/iskandr/fancyimpute,https://github.com/iskandr/fancyimpute,Apache-2.0,2015-11-05 23:39:34.000,2021-10-21 17:50:40.000000,2021-10-21 17:45:17,202.0,,167,24.0,35.0,1.0,111.0,1033,Multivariate imputation and matrix completion algorithms implemented in Python.,12.0,26,True,2021-10-21 17:50:40.000,0.7.0,29.0,fancyimpute,,,,['sklearn'],1153.0,1124.0,https://pypi.org/project/fancyimpute,2021-10-21 17:50:40.000,29.0,11881.0,11881.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +455,Streamz,python-streamz/streamz,time-series-data,,https://github.com/python-streamz/streamz,https://github.com/python-streamz/streamz,BSD-3-Clause,2017-04-04 21:45:49.000,2021-12-31 19:41:11.000000,2021-12-24 18:36:59,781.0,6.0,130,32.0,210.0,103.0,145.0,1028,Real-time stream processing for python.,45.0,26,True,2021-10-04 14:47:39.000,0.6.3,16.0,streamz,conda-forge/streamz,,,,293.0,264.0,https://pypi.org/project/streamz,2021-10-04 14:47:39.000,29.0,11061.0,15620.0,https://anaconda.org/conda-forge/streamz,2021-10-04 16:06:59.119,241668.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +456,stockstats,jealous/stockstats,financial-data,,https://github.com/jealous/stockstats,https://github.com/jealous/stockstats,BSD-3-Clause,2016-06-05 15:21:22.000,2022-01-07 14:52:00.000000,2022-01-07 14:51:56,41.0,15.0,249,49.0,34.0,3.0,76.0,954,Supply a wrapper ``StockDataFrame`` based on the ``pandas.DataFrame`` with inline stock statistics/indicators support.,8.0,26,True,2022-01-07 11:43:24.000,0.4.1,16.0,stockstats,,,,,425.0,396.0,https://pypi.org/project/stockstats,2022-01-07 11:43:24.000,29.0,9168.0,9168.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +457,bcolz,Blosc/bcolz,data-containers,,https://github.com/Blosc/bcolz,https://github.com/Blosc/bcolz,BSD-3-Clause,2010-08-18 15:27:02.000,2021-09-07 20:42:40.000000,2020-09-10 12:12:45,1280.0,,134,60.0,176.0,133.0,122.0,940,A columnar data container that can be compressed.,33.0,26,False,2018-04-13 07:44:26.000,1.2.1,23.0,bcolz,conda-forge/bcolz,,,,2204.0,1701.0,https://pypi.org/project/bcolz,2018-04-13 07:44:26.000,503.0,14153.0,18918.0,https://anaconda.org/conda-forge/bcolz,2019-11-05 21:09:48.045,285915.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +458,Neural Structured Learning,tensorflow/neural-structured-learning,tensorflow-utils,,https://github.com/tensorflow/neural-structured-learning,https://github.com/tensorflow/neural-structured-learning,Apache-2.0,2019-08-27 21:48:16.000,2022-02-10 00:12:12.000000,2022-02-01 19:01:07,505.0,11.0,167,44.0,52.0,3.0,58.0,901,Training neural models with structured signals.,32.0,26,True,2020-08-18 00:35:35.000,1.3.1,7.0,neural-structured-learning,,,,['tensorflow'],172.0,170.0,https://pypi.org/project/neural-structured-learning,2020-08-18 00:35:35.000,2.0,11076.0,11076.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +459,empyrical,quantopian/empyrical,financial-data,,https://github.com/quantopian/empyrical,https://github.com/quantopian/empyrical,Apache-2.0,2016-03-18 10:22:52.000,2020-10-14 13:28:13.625000,2020-10-14 13:22:39,167.0,,278,70.0,83.0,27.0,26.0,894,Common financial risk and performance metrics. Used by zipline and pyfolio.,22.0,26,False,2020-10-13 21:29:19.000,0.5.5,21.0,empyrical,conda-forge/empyrical,,,,929.0,795.0,https://pypi.org/project/empyrical,2020-10-13 21:29:19.000,134.0,57932.0,58239.0,https://anaconda.org/conda-forge/empyrical,2020-10-14 13:28:13.625,14767.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +460,PySwarms,ljvmiranda921/pyswarms,others,,https://github.com/ljvmiranda921/pyswarms,https://github.com/ljvmiranda921/pyswarms,MIT,2017-07-12 12:04:45.000,2021-12-03 19:52:38.000000,2021-06-23 11:19:05,409.0,,286,32.0,290.0,16.0,181.0,878,A research toolkit for particle swarm optimization in Python.,43.0,26,True,2021-01-03 21:34:15.000,1.3.0,20.0,pyswarms,,,,,155.0,149.0,https://pypi.org/project/pyswarms,2021-01-03 21:34:15.000,6.0,31556.0,31556.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +461,GPyOpt,SheffieldML/GPyOpt,hyperopt,,https://github.com/SheffieldML/GPyOpt,https://github.com/SheffieldML/GPyOpt,BSD-3-Clause,2014-08-13 09:58:25.000,2020-11-17 10:32:02.000000,2020-11-05 15:16:04,514.0,,242,42.0,72.0,99.0,186.0,793,Gaussian Process Optimization using GPy.,49.0,26,False,2020-03-19 21:21:18.000,1.2.6,11.0,gpyopt,,,,,277.0,245.0,https://pypi.org/project/gpyopt,2020-03-19 11:37:45.000,32.0,15877.0,15877.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +462,pythreejs,jupyter-widgets/pythreejs,data-viz,,https://github.com/jupyter-widgets/pythreejs,https://github.com/jupyter-widgets/pythreejs,BSD-3-Clause,2013-12-23 17:02:11.000,2021-12-06 21:48:19.000000,2021-12-06 21:48:19,1667.0,6.0,162,40.0,161.0,67.0,144.0,788,A Jupyter - Three.js bridge.,29.0,26,True,2021-02-26 14:01:21.000,2.3.0,43.0,pythreejs,conda-forge/pythreejs,,,['jupyter'],60.0,19.0,https://pypi.org/project/pythreejs,2021-02-26 14:01:21.000,34.0,38640.0,49483.0,https://anaconda.org/conda-forge/pythreejs,2021-03-02 13:32:39.505,363399.0,,,,,3.0,,,jupyter-threejs,https://www.npmjs.com/package/jupyter-threejs,2021-02-26 13:59:06.062,7.0,5577.0,,,,,,,,,,,,,, +463,lets-plot,JetBrains/lets-plot,data-viz,,https://github.com/JetBrains/lets-plot,https://github.com/JetBrains/lets-plot,MIT,2019-03-20 16:13:03.000,2022-02-10 10:50:53.000000,2022-02-10 08:58:38,2371.0,113.0,32,140.0,276.0,70.0,160.0,717,An open-source plotting library for statistical data.,16.0,26,True,2021-12-10 17:04:12.000,2.2.1,45.0,lets-plot,,,,,14.0,13.0,https://pypi.org/project/lets-plot,2021-12-10 16:26:26.000,1.0,2493.0,2500.0,,,,,,,,3.0,197.0,,,,,,,,,,,,,,,,,,,, +464,PyKEEN,pykeen/pykeen,graph,,https://github.com/pykeen/pykeen,https://github.com/pykeen/pykeen,MIT,2020-02-24 07:26:03.000,2022-02-10 13:15:35.000000,2022-02-06 19:44:04,2560.0,82.0,99,21.0,424.0,113.0,234.0,700,A Python library for learning and evaluating knowledge graph embeddings.,24.0,26,True,2022-01-11 14:57:28.000,1.7.0,38.0,pykeen,,,,,3.0,,https://pypi.org/project/pykeen,2022-01-11 14:55:50.000,3.0,1156.0,1160.0,,,,,,,,2.0,92.0,,,,,,,,,,,,,,,,,,,, +465,CellProfiler,CellProfiler/CellProfiler,image,,https://github.com/CellProfiler/CellProfiler,https://github.com/CellProfiler/CellProfiler,BSD-3-Clause,2011-04-05 12:10:12.000,2022-02-09 18:40:54.000000,2022-02-01 20:41:40,15372.0,14.0,300,43.0,1478.0,188.0,2837.0,646,An open-source application for biological image analysis.,125.0,26,True,2021-07-22 19:01:42.000,4.2.1,43.0,cellprofiler,,,,,7.0,7.0,https://pypi.org/project/cellprofiler,2017-09-04 18:03:36.000,,757.0,780.0,,,,,,,,3.0,2244.0,,,,,,,,,,,,,,,,,,,, +466,GeoViews,holoviz/geoviews,geospatial-data,,https://github.com/holoviz/geoviews,https://github.com/holoviz/geoviews,BSD-3-Clause,2016-04-19 16:27:01.000,2022-01-13 13:20:50.024000,2021-12-25 17:12:31,676.0,12.0,69,28.0,257.0,105.0,191.0,393,"Simple, concise geographical visualization in Python.",25.0,26,True,2021-12-25 18:09:47.000,1.9.3,32.0,geoviews,conda-forge/geoviews,,,,25.0,,https://pypi.org/project/geoviews,2021-12-25 17:22:46.000,25.0,13187.0,15161.0,https://anaconda.org/conda-forge/geoviews,2022-01-13 13:20:50.024,92824.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +467,EarthPy,earthlab/earthpy,geospatial-data,,https://github.com/earthlab/earthpy,https://github.com/earthlab/earthpy,BSD-3-Clause,2018-02-20 03:02:42.000,2022-02-04 18:04:52.000000,2021-12-20 23:24:01,1186.0,3.0,125,21.0,530.0,18.0,207.0,327,A package built to support working with spatial data using open source python.,40.0,26,True,2021-10-01 22:51:04.000,0.9.4,23.0,earthpy,conda-forge/earthpy,,,,134.0,127.0,https://pypi.org/project/earthpy,2021-10-01 22:51:04.000,7.0,4806.0,6000.0,https://anaconda.org/conda-forge/earthpy,2021-10-04 19:35:49.510,40596.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +468,StaticFrame,InvestmentSystems/static-frame,data-containers,,https://github.com/InvestmentSystems/static-frame,https://github.com/InvestmentSystems/static-frame,MIT,2018-01-03 15:07:52.000,2022-02-10 04:15:02.000000,2022-02-10 00:45:08,3569.0,353.0,24,11.0,61.0,41.0,333.0,260,Immutable and grow-only Pandas-like DataFrames with a more explicit and consistent interface.,16.0,26,False,2022-01-17 16:23:41.000,0.8.34,133.0,static-frame,conda-forge/static-frame,,,,13.0,11.0,https://pypi.org/project/static-frame,2022-01-17 15:09:40.000,2.0,1365.0,5086.0,https://anaconda.org/conda-forge/static-frame,2022-01-17 22:23:49.129,133972.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +469,dbnd,databand-ai/dbnd,data-pipelines,,https://github.com/databand-ai/dbnd,https://github.com/databand-ai/dbnd,Apache-2.0,2020-01-02 10:42:47.000,2022-02-09 12:46:43.000000,2022-02-09 11:37:04,2856.0,182.0,22,18.0,51.0,3.0,2.0,215,DBND is an agile pipeline framework that helps data engineering teams track and orchestrate their data processes.,55.0,26,False,2022-02-09 12:38:50.000,0.62.12,275.0,dbnd,,,,,47.0,25.0,https://pypi.org/project/dbnd,2022-02-09 12:38:50.000,22.0,125960.0,125960.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +470,snownlp,isnowfy/snownlp,chinese-nlp,,https://github.com/isnowfy/snownlp,https://github.com/isnowfy/snownlp,MIT,2013-11-26 11:46:56.000,2020-01-19 02:39:05.000000,2020-01-19 02:39:03,57.0,,1298,351.0,14.0,39.0,65.0,5688,Python library for processing Chinese text.,8.0,25,False,2015-09-27 16:35:23.000,0.12.3,17.0,snownlp,,,,,834.0,795.0,https://pypi.org/project/snownlp,2015-09-27 16:35:23.000,39.0,3725.0,3725.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +471,mmdnn,Microsoft/MMdnn,model-serialisation,,https://github.com/microsoft/MMdnn,https://github.com/microsoft/MMdnn,MIT,2017-08-16 08:03:52.000,2021-03-01 14:17:24.000000,2020-08-14 02:32:30,1083.0,,964,185.0,323.0,327.0,289.0,5507,MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion..,85.0,25,False,2020-07-24 06:34:39.000,0.3.1,12.0,mmdnn,,,,,73.0,70.0,https://pypi.org/project/mmdnn,2020-07-24 06:34:39.000,3.0,680.0,748.0,,,,,,,,3.0,3481.0,,,,,,,,,,,,,,,,,,,, +472,flashtext,vi3k6i5/flashtext,nlp,,https://github.com/vi3k6i5/flashtext,https://github.com/vi3k6i5/flashtext,MIT,2017-08-15 18:03:01.000,2021-07-26 20:38:52.000000,2020-05-03 07:13:22,108.0,,556,141.0,30.0,54.0,51.0,5048,Extract Keywords from sentence or Replace keywords in sentences.,7.0,25,False,,,18.0,flashtext,conda-forge/flashtext,,,,714.0,683.0,https://pypi.org/project/flashtext,2018-02-16 05:24:17.000,31.0,545286.0,545683.0,https://anaconda.org/conda-forge/flashtext,2020-07-16 16:37:59.996,7544.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +473,textgenrnn,minimaxir/textgenrnn,nlp,,https://github.com/minimaxir/textgenrnn,https://github.com/minimaxir/textgenrnn,MIT,2017-08-07 02:13:37.000,2021-12-17 04:03:09.000000,2020-07-14 02:41:10,174.0,,711,142.0,41.0,120.0,90.0,4632,Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines..,19.0,25,False,2020-02-03 01:07:00.000,2.0.0,14.0,textgenrnn,,,,['tensorflow'],974.0,959.0,https://pypi.org/project/textgenrnn,2020-02-02 21:16:15.000,15.0,661.0,674.0,,,,,,,,3.0,639.0,,,,,,,,,,,,,,,,,,,, +474,mace,XiaoMi/mace,ml-frameworks,,https://github.com/XiaoMi/mace,https://github.com/XiaoMi/mace,Apache-2.0,2018-06-27 03:50:12.000,2022-01-13 09:55:14.000000,2022-01-13 09:11:57,3324.0,28.0,779,229.0,103.0,41.0,612.0,4567,MACE is a deep learning inference framework optimized for mobile heterogeneous computing platforms.,63.0,25,True,2022-01-13 09:55:14.000,1.1.1,12.0,,,,,,,,,,,,33.0,,,,,,,,3.0,1400.0,,,,,,,,,,,,,,,,,,,, +475,torchdiffeq,rtqichen/torchdiffeq,pytorch-utils,,https://github.com/rtqichen/torchdiffeq,https://github.com/rtqichen/torchdiffeq,MIT,2018-11-14 17:51:25.000,2022-01-17 20:17:27.000000,2022-01-17 20:15:35,225.0,1.0,676,124.0,33.0,31.0,132.0,3924,Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.,20.0,25,True,2021-06-02 23:04:51.000,0.2.2,6.0,torchdiffeq,conda-forge/torchdiffeq,,,['pytorch'],199.0,193.0,https://pypi.org/project/torchdiffeq,2021-06-02 23:04:51.000,6.0,19446.0,19664.0,https://anaconda.org/conda-forge/torchdiffeq,2021-06-03 13:23:15.112,4598.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +476,FATE,FederatedAI/FATE,privacy-ml,,https://github.com/FederatedAI/FATE,https://github.com/FederatedAI/FATE,Apache-2.0,2019-01-24 10:32:43.000,2022-02-10 10:13:22.000000,2022-01-27 10:07:32,9841.0,618.0,1148,134.0,2607.0,347.0,721.0,3920,An Industrial Grade Federated Learning Framework.,69.0,25,True,2022-01-27 10:09:10.000,1.7.1.1,31.0,ETAF,,,,,,,https://pypi.org/project/ETAF,2020-05-06 09:35:40.000,,1.0,1.0,,,,,,,,3.0,,,,,,,,,-3.0,,,,,,,,,,,, +477,segmentation_models,qubvel/segmentation_models,image,,https://github.com/qubvel/segmentation_models,https://github.com/qubvel/segmentation_models,MIT,2018-06-05 13:27:56.000,2022-01-04 21:11:23.000000,2020-04-17 09:51:20,204.0,,853,94.0,56.0,204.0,255.0,3678,Segmentation models with pretrained backbones. Keras and TensorFlow Keras.,14.0,25,False,2020-01-10 11:36:02.000,1.0.1,8.0,segmentation_models,,,,['tensorflow'],24.0,,https://pypi.org/project/segmentation_models,2020-01-10 11:36:02.000,24.0,46680.0,46680.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +478,Snips NLU,snipsco/snips-nlu,nlp,,https://github.com/snipsco/snips-nlu,https://github.com/snipsco/snips-nlu,Apache-2.0,2017-02-08 16:16:36.000,2021-11-17 15:23:01.000000,2021-05-03 12:18:31,2154.0,,495,141.0,648.0,60.0,196.0,3612,Snips Python library to extract meaning from text.,22.0,25,True,2020-01-15 10:13:17.000,0.20.2,58.0,snips-nlu,,,,,11.0,,https://pypi.org/project/snips-nlu,2020-01-15 10:13:17.000,11.0,4223.0,4223.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +479,PyAlgoTrade,gbeced/pyalgotrade,financial-data,,https://github.com/gbeced/pyalgotrade,https://github.com/gbeced/pyalgotrade,Apache-2.0,2012-03-07 01:09:54.000,2022-02-01 17:04:10.000000,2018-08-21 02:42:52,1156.0,,1216,350.0,52.0,45.0,84.0,3609,Python Algorithmic Trading Library.,11.0,25,False,,,8.0,pyalgotrade,,,,,125.0,104.0,https://pypi.org/project/pyalgotrade,2018-08-21 01:48:25.000,21.0,868.0,868.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +480,Stable Baselines,hill-a/stable-baselines,reinforcement-learning,,https://github.com/hill-a/stable-baselines,https://github.com/hill-a/stable-baselines,MIT,2018-07-02 14:28:59.000,2021-08-25 09:25:32.000000,2021-08-25 09:25:32,838.0,,667,66.0,246.0,128.0,801.0,3440,"A fork of OpenAI Baselines, implementations of reinforcement learning algorithms.",112.0,25,True,2021-04-06 12:37:09.000,2.10.2,31.0,stable-baselines,,,,,34.0,,https://pypi.org/project/stable-baselines,2021-04-06 12:37:09.000,34.0,8531.0,8531.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +481,AdaNet,tensorflow/adanet,hyperopt,,https://github.com/tensorflow/adanet,https://github.com/tensorflow/adanet,Apache-2.0,2018-06-28 20:20:24.000,2021-08-30 19:33:24.000000,2021-08-30 19:33:24,440.0,,518,171.0,49.0,64.0,48.0,3357,Fast and flexible AutoML with learning guarantees.,27.0,25,True,2020-07-09 21:03:28.000,0.9.0,13.0,adanet,,,,['tensorflow'],44.0,42.0,https://pypi.org/project/adanet,2020-07-09 21:03:28.000,2.0,1108.0,1108.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +482,Chartify,spotify/chartify,data-viz,,https://github.com/spotify/chartify,https://github.com/spotify/chartify,Apache-2.0,2018-09-17 14:12:05.000,2022-01-31 12:20:49.000000,2021-02-05 18:49:02,195.0,,276,84.0,65.0,41.0,31.0,3090,Python library that makes it easy for data scientists to create charts.,21.0,25,True,2020-11-02 22:14:08.000,3.0.3,16.0,chartify,conda-forge/chartify,,,,66.0,61.0,https://pypi.org/project/chartify,2020-11-02 22:14:08.000,5.0,1769.0,2226.0,https://anaconda.org/conda-forge/chartify,2020-11-07 19:52:50.628,17841.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +483,xLearn,aksnzhy/xlearn,ml-frameworks,,https://github.com/aksnzhy/xlearn,https://github.com/aksnzhy/xlearn,Apache-2.0,2017-06-10 08:09:31.000,2021-01-28 14:17:44.000000,2020-03-03 10:12:35,1340.0,,528,109.0,70.0,193.0,114.0,2982,"High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization..",30.0,25,False,2019-04-25 02:10:05.000,0.4.4,15.0,xlearn,,,,,88.0,76.0,https://pypi.org/project/xlearn,2018-12-04 11:05:06.000,12.0,2541.0,2606.0,,,,,,,,3.0,3094.0,,,,,,,,,,,,,,,,,,,, +484,layout-parser,Layout-Parser/layout-parser,image,,https://github.com/Layout-Parser/layout-parser,https://github.com/Layout-Parser/layout-parser,Apache-2.0,2020-06-10 20:22:54.000,2022-02-06 18:49:57.000000,2022-02-02 15:28:59,171.0,5.0,269,55.0,39.0,38.0,38.0,2815,A Unified Toolkit for Deep Learning Based Document Image Analysis.,8.0,25,True,2021-09-23 17:37:22.000,0.3.2,9.0,layoutparser,,,,,44.0,43.0,https://pypi.org/project/layoutparser,2021-09-23 17:37:22.000,1.0,4752.0,4752.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +485,facenet-pytorch,timesler/facenet-pytorch,image,,https://github.com/timesler/facenet-pytorch,https://github.com/timesler/facenet-pytorch,MIT,2019-05-25 01:29:24.000,2021-12-13 14:59:32.000000,2021-12-13 12:07:11,235.0,1.0,567,39.0,44.0,56.0,89.0,2665,Pretrained Pytorch face detection (MTCNN) and facial recognition (InceptionResnet) models.,14.0,25,True,2021-03-10 01:00:20.000,2.5.2,31.0,facenet-pytorch,,,,['pytorch'],638.0,631.0,https://pypi.org/project/facenet-pytorch,2021-03-10 01:00:20.000,7.0,12782.0,20019.0,,,,,,,,3.0,195408.0,,,,,,,,,,,,,,,,,,,, +486,tensorflow-graphics,tensorflow/graphics,image,,https://github.com/tensorflow/graphics,https://github.com/tensorflow/graphics,Apache-2.0,2019-01-08 10:39:44.000,2022-02-02 15:24:48.000000,2022-02-02 15:24:43,749.0,16.0,338,89.0,521.0,131.0,90.0,2585,TensorFlow Graphics: Differentiable Graphics Layers for TensorFlow.,34.0,25,True,2021-12-03 22:33:39.000,2021.12.3,25.0,tensorflow-graphics,,,,['tensorflow'],4.0,,https://pypi.org/project/tensorflow-graphics,2021-12-03 22:33:39.000,4.0,2472.0,2472.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +487,fastNLP,fastnlp/fastNLP,nlp,,https://github.com/fastnlp/fastNLP,https://github.com/fastnlp/fastNLP,Apache-2.0,2018-03-07 13:30:20.000,2021-12-06 12:23:20.000000,2021-12-06 11:37:15,1769.0,8.0,404,80.0,224.0,35.0,144.0,2489,fastNLP: A Modularized and Extensible NLP Framework. Currently still in incubation.,54.0,25,True,2020-11-06 15:31:29.000,0.6.0,10.0,fastnlp,,,,,58.0,55.0,https://pypi.org/project/fastnlp,2019-02-04 02:35:37.000,3.0,1056.0,1057.0,,,,,,,,3.0,65.0,,,,,,,,-2.0,,,,,,,,,,,, +488,Mars,mars-project/mars,others,,https://github.com/mars-project/mars,https://github.com/mars-project/mars,Apache-2.0,2018-12-05 16:04:03.000,2022-02-10 12:16:12.000000,2022-02-10 11:22:57,1025.0,42.0,296,85.0,1728.0,155.0,808.0,2348,"Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and..",41.0,25,True,2022-02-03 08:27:20.000,0.8.1,103.0,pymars,,,,,1.0,,https://pypi.org/project/pymars,2022-02-03 08:35:15.000,1.0,4204.0,4204.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +489,vissl,facebookresearch/vissl,image,,https://github.com/facebookresearch/vissl,https://github.com/facebookresearch/vissl,MIT,2020-04-09 19:40:33.000,2022-02-01 16:56:15.000000,2022-02-01 16:55:20,339.0,47.0,228,52.0,396.0,44.0,88.0,2345,"VISSL is FAIRs library of extensible, modular and scalable components for SOTA Self-Supervised Learning with images.",30.0,25,True,2021-11-02 17:21:02.000,0.1.6,6.0,vissl,,,,['pytorch'],6.0,5.0,https://pypi.org/project/vissl,2021-11-02 15:36:07.000,1.0,189.0,189.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +490,Enigma Catalyst,scrtlabs/catalyst,financial-data,,https://github.com/scrtlabs/catalyst,https://github.com/scrtlabs/catalyst,Apache-2.0,2017-06-13 22:31:34.000,2021-09-22 15:32:01.000000,2021-09-22 15:31:55,6364.0,,685,165.0,93.0,134.0,358.0,2324,An Algorithmic Trading Library for Crypto-Assets in Python.,147.0,25,True,2018-11-11 16:46:28.000,0.5.21,52.0,enigma-catalyst,,,,,25.0,23.0,https://pypi.org/project/enigma-catalyst,2018-11-11 16:46:28.000,2.0,464.0,464.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +491,pytorch-nlp,PetrochukM/PyTorch-NLP,nlp,,https://github.com/PetrochukM/PyTorch-NLP,https://github.com/PetrochukM/PyTorch-NLP,BSD-3-Clause,2018-02-25 05:00:36.000,2022-01-22 00:08:57.000000,2021-07-10 15:56:42,447.0,,243,57.0,55.0,18.0,49.0,2018,Basic Utilities for PyTorch Natural Language Processing (NLP).,18.0,25,True,2019-11-04 05:16:00.000,0.5.0,19.0,pytorch-nlp,,,,['pytorch'],343.0,326.0,https://pypi.org/project/pytorch-nlp,2019-11-04 04:35:18.000,17.0,7108.0,7108.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +492,m2cgen,BayesWitnesses/m2cgen,model-serialisation,,https://github.com/BayesWitnesses/m2cgen,https://github.com/BayesWitnesses/m2cgen,MIT,2019-01-13 02:32:55.000,2022-02-09 23:52:49.000000,2022-02-08 22:36:03,343.0,18.0,169,44.0,416.0,36.0,65.0,2017,"Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart,..",12.0,25,True,2020-09-18 19:17:26.000,0.9.0,12.0,m2cgen,,,,,15.0,15.0,https://pypi.org/project/m2cgen,2020-09-18 19:16:17.000,,57596.0,57596.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +493,Spektral,danielegrattarola/spektral,graph,,https://github.com/danielegrattarola/spektral,https://github.com/danielegrattarola/spektral,MIT,2019-01-17 11:19:10.000,2022-02-01 13:53:46.000000,2021-10-26 09:35:54,1033.0,,267,47.0,46.0,36.0,167.0,1988,Graph Neural Networks with Keras and Tensorflow 2.,19.0,25,True,2021-08-23 13:15:21.000,1.0.8,31.0,spektral,,,,['tensorflow'],102.0,100.0,https://pypi.org/project/spektral,2021-08-23 13:15:21.000,2.0,4354.0,4354.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +494,scattertext,JasonKessler/scattertext,nlp,,https://github.com/JasonKessler/scattertext,https://github.com/JasonKessler/scattertext,Apache-2.0,2016-07-21 01:47:12.000,2021-11-15 13:11:26.058000,2021-11-15 03:48:32,356.0,3.0,243,54.0,11.0,17.0,68.0,1749,Beautiful visualizations of how language differs among document types.,12.0,25,True,2021-11-15 04:01:17.000,0.1.5,134.0,scattertext,conda-forge/scattertext,,,,265.0,255.0,https://pypi.org/project/scattertext,2021-11-15 04:01:17.000,10.0,3934.0,5038.0,https://anaconda.org/conda-forge/scattertext,2021-11-15 13:11:26.058,59644.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +495,mtcnn,ipazc/mtcnn,image,,https://github.com/ipazc/mtcnn,https://github.com/ipazc/mtcnn,MIT,2018-01-05 04:08:32.000,2021-11-22 17:31:06.000000,2021-07-09 11:06:18,56.0,,438,41.0,21.0,62.0,38.0,1716,"MTCNN face detection implementation for TensorFlow, as a PIP package.",15.0,25,True,2021-07-09 11:16:39.000,0.1.1,11.0,mtcnn,conda-forge/mtcnn,,,['tensorflow'],1952.0,1909.0,https://pypi.org/project/mtcnn,2021-07-09 11:16:39.000,43.0,27403.0,27579.0,https://anaconda.org/conda-forge/mtcnn,2021-08-17 17:36:21.436,4245.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +496,Neural Tangents,google/neural-tangents,ml-frameworks,,https://github.com/google/neural-tangents,https://github.com/google/neural-tangents,Apache-2.0,2019-04-08 16:48:48.000,2022-02-08 17:45:08.000000,2022-02-08 17:45:00,447.0,17.0,186,59.0,23.0,34.0,72.0,1686,Fast and Easy Infinite Neural Networks in Python.,21.0,25,True,2021-11-17 06:35:11.000,0.3.9,23.0,neural-tangents,,,,,30.0,29.0,https://pypi.org/project/neural-tangents,2021-11-17 06:30:38.000,1.0,486.0,495.0,,,,,,,,3.0,192.0,,,,,,,,,,,,,,,,,,,, +497,Fairness 360,Trusted-AI/AIF360,interpretability,,https://github.com/Trusted-AI/AIF360,https://github.com/Trusted-AI/AIF360,Apache-2.0,2018-08-22 20:47:15.000,2022-01-21 16:14:00.000000,2022-01-21 16:14:00,345.0,4.0,511,85.0,166.0,63.0,59.0,1632,"A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and..",48.0,25,True,2021-03-04 18:11:34.000,0.4.0,9.0,aif360,conda-forge/aif360,,,,145.0,137.0,https://pypi.org/project/aif360,2021-03-04 18:11:34.000,8.0,7927.0,8017.0,https://anaconda.org/conda-forge/aif360,2021-09-29 17:08:47.878,1544.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +498,RecBole,RUCAIBox/RecBole,recommender-systems,,https://github.com/RUCAIBox/RecBole,https://github.com/RUCAIBox/RecBole,MIT,2020-06-11 15:18:11.000,2022-02-08 22:22:50.000000,2022-01-25 15:41:42,3393.0,25.0,287,31.0,791.0,65.0,232.0,1605,"A unified, comprehensive and efficient recommendation library.",43.0,25,True,2021-09-16 13:45:46.000,1.0.0,6.0,recbole,aibox/recbole,,,['pytorch'],,,https://pypi.org/project/recbole,2021-09-16 13:45:46.000,,565.0,635.0,https://anaconda.org/aibox/recbole,2021-09-16 16:45:01.892,1054.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +499,checklist,marcotcr/checklist,interpretability,,https://github.com/marcotcr/checklist,https://github.com/marcotcr/checklist,MIT,2020-03-09 17:18:49.000,2022-01-14 09:08:25.000000,2021-09-28 21:55:38,247.0,,149,27.0,34.0,12.0,80.0,1583,Beyond Accuracy: Behavioral Testing of NLP models with CheckList.,12.0,25,True,2021-05-24 16:45:59.000,0.0.11,10.0,checklist,conda-forge/checklist,,,['jupyter'],83.0,80.0,https://pypi.org/project/checklist,2021-05-24 16:45:59.000,3.0,17642.0,17821.0,https://anaconda.org/conda-forge/checklist,2021-07-15 13:35:51.684,2329.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +500,Torchmeta,tristandeleu/pytorch-meta,pytorch-utils,,https://github.com/tristandeleu/pytorch-meta,https://github.com/tristandeleu/pytorch-meta,MIT,2018-12-04 23:36:45.000,2022-01-10 12:07:24.000000,2021-09-20 16:03:46,382.0,,195,40.0,30.0,35.0,89.0,1547,A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch.,12.0,25,True,2021-09-20 16:06:33.000,1.8.0,28.0,torchmeta,,,,['pytorch'],81.0,81.0,https://pypi.org/project/torchmeta,2021-09-20 16:06:33.000,,1899.0,1899.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +501,pygraphistry,graphistry/pygraphistry,graph,,https://github.com/graphistry/pygraphistry,https://github.com/graphistry/pygraphistry,BSD-3-Clause,2015-06-02 20:28:42.000,2022-02-10 09:24:26.000000,2021-12-22 01:54:09,820.0,12.0,147,44.0,118.0,75.0,111.0,1541,"PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated..",19.0,25,True,2021-12-07 07:06:16.000,0.20.5,126.0,graphistry,,,,['jupyter'],61.0,57.0,https://pypi.org/project/graphistry,2021-12-07 07:06:16.000,4.0,2192.0,2192.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +502,Elephas,maxpumperla/elephas,distributed-ml,,https://github.com/maxpumperla/elephas,https://github.com/maxpumperla/elephas,MIT,2015-08-13 12:09:19.000,2021-11-18 11:51:00.000000,2021-08-17 01:01:38,501.0,,290,104.0,46.0,25.0,137.0,1525,Distributed Deep learning with Keras & Spark.,27.0,25,True,2021-08-17 01:14:44.000,3.0.0,22.0,elephas,conda-forge/elephas,,,"['keras', 'spark']",55.0,52.0,https://pypi.org/project/elephas,2021-08-17 00:36:20.000,3.0,27886.0,28143.0,https://anaconda.org/conda-forge/elephas,2021-06-02 18:33:53.270,7732.0,,,,,3.0,,,,,,,,,-2.0,,,,,,,,,,,, +503,sklearn-contrib-lightning,scikit-learn-contrib/lightning,sklearn-utils,,https://github.com/scikit-learn-contrib/lightning,https://github.com/scikit-learn-contrib/lightning,BSD-3-Clause,2012-01-11 13:53:52.000,2022-01-30 01:28:10.000000,2022-01-30 01:22:30,743.0,15.0,198,40.0,110.0,51.0,41.0,1515,"Large-scale linear classification, regression and ranking in Python.",17.0,25,True,2022-01-30 01:10:13.000,0.6.2.post0,12.0,sklearn-contrib-lightning,conda-forge/sklearn-contrib-lightning,,,['sklearn'],105.0,99.0,https://pypi.org/project/sklearn-contrib-lightning,2022-01-30 00:43:43.000,6.0,3894.0,6313.0,https://anaconda.org/conda-forge/sklearn-contrib-lightning,2021-11-13 15:37:21.493,161154.0,,,,,2.0,119.0,,,,,,,,,,,,,,,,,,,, +504,bonobo,python-bonobo/bonobo,data-pipelines,,https://github.com/python-bonobo/bonobo,https://github.com/python-bonobo/bonobo,Apache-2.0,2016-12-09 04:03:23.000,2022-01-21 19:04:02.000000,2021-03-10 15:44:00,981.0,,123,61.0,234.0,95.0,108.0,1488,Extract Transform Load for Python 3.5+.,37.0,25,True,2019-05-16 13:19:48.000,0.6.4,38.0,bonobo,,,http://docs.bonobo-project.org/en/master/,,161.0,128.0,https://pypi.org/project/bonobo,2019-07-20 13:33:19.000,33.0,8572.0,8572.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +505,CausalNex,quantumblacklabs/causalnex,interpretability,,https://github.com/quantumblacklabs/causalnex,https://github.com/quantumblacklabs/causalnex,Apache-2.0,2019-12-12 15:26:09.000,2022-01-15 03:23:45.000000,2021-11-11 15:06:17,156.0,,159,42.0,46.0,15.0,87.0,1448,A Python library that helps data scientists to infer causation rather than observing correlation.,22.0,25,True,2021-11-11 15:15:32.000,0.11.0,16.0,causalnex,,,,"['pytorch', 'sklearn']",40.0,38.0,https://pypi.org/project/causalnex,2021-11-11 15:15:32.000,2.0,2153.0,2153.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +506,garage,rlworkgroup/garage,reinforcement-learning,,https://github.com/rlworkgroup/garage,https://github.com/rlworkgroup/garage,MIT,2018-06-10 21:31:23.000,2022-02-08 14:44:33.000000,2021-10-20 05:09:03,1217.0,,242,54.0,1305.0,205.0,799.0,1395,A toolkit for reproducible reinforcement learning research.,78.0,25,True,2021-03-23 22:18:36.000,2021.3.0,21.0,garage,,,,['tensorflow'],31.0,29.0,https://pypi.org/project/garage,2021-03-23 22:18:36.000,2.0,465.0,465.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +507,pytorch_geometric_temporal,benedekrozemberczki/pytorch_geometric_temporal,graph,,https://github.com/benedekrozemberczki/pytorch_geometric_temporal,https://github.com/benedekrozemberczki/pytorch_geometric_temporal,MIT,2020-06-27 01:11:33.000,2022-02-10 01:53:05.000000,2022-02-03 22:43:11,1850.0,60.0,193,39.0,56.0,1.0,80.0,1325,PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021).,18.0,25,True,2022-01-19 22:38:53.000,0.50.0,42.0,torch-geometric-temporal,,,,['pytorch'],1.0,,https://pypi.org/project/torch-geometric-temporal,2022-01-19 22:42:40.000,1.0,1337.0,1337.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +508,pyts,johannfaouzi/pyts,time-series-data,,https://github.com/johannfaouzi/pyts,https://github.com/johannfaouzi/pyts,BSD-3-Clause,2017-07-31 09:23:16.000,2021-12-09 13:27:33.000000,2021-12-09 13:27:29,379.0,2.0,117,21.0,67.0,33.0,24.0,1165,A Python package for time series classification.,10.0,25,True,2021-10-31 13:51:09.000,0.12.0,18.0,pyts,conda-forge/pyts,,,,178.0,167.0,https://pypi.org/project/pyts,2021-10-31 13:51:09.000,11.0,105743.0,106074.0,https://anaconda.org/conda-forge/pyts,2021-10-31 15:13:32.850,9958.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +509,livelossplot,stared/livelossplot,ml-experiments,,https://github.com/stared/livelossplot,https://github.com/stared/livelossplot,MIT,2018-03-10 17:51:43.000,2021-10-12 11:52:57.000000,2021-10-12 11:52:20,328.0,,138,26.0,61.0,4.0,70.0,1156,"Live training loss plot in Jupyter Notebook for Keras, PyTorch and others.",17.0,25,True,2021-02-03 16:25:47.000,0.5.4,24.0,livelossplot,,,,['jupyter'],731.0,723.0,https://pypi.org/project/livelossplot,2021-02-03 16:25:47.000,8.0,63888.0,63888.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +510,explainerdashboard,oegedijk/explainerdashboard,interpretability,,https://github.com/oegedijk/explainerdashboard,https://github.com/oegedijk/explainerdashboard,MIT,2019-10-30 08:26:16.000,2022-02-10 14:12:15.000000,2022-02-10 13:47:42,1228.0,8.0,134,14.0,25.0,12.0,133.0,1100,Quickly build Explainable AI dashboards that show the inner workings of so-called blackbox machine learning models.,12.0,25,True,2022-02-10 14:12:15.000,0.3.8,79.0,explainerdashboard,conda-forge/explainerdashboard,,,,60.0,58.0,https://pypi.org/project/explainerdashboard,2022-02-10 14:12:15.000,2.0,16305.0,17285.0,https://anaconda.org/conda-forge/explainerdashboard,2021-08-04 01:07:37.644,13727.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +511,SciSpacy,allenai/scispacy,nlp,,https://github.com/allenai/scispacy,https://github.com/allenai/scispacy,Apache-2.0,2018-09-24 21:45:52.000,2022-02-03 22:27:54.000000,2022-02-03 22:27:53,949.0,2.0,148,55.0,178.0,34.0,204.0,1089,A full spaCy pipeline and models for scientific/biomedical documents.,22.0,25,True,2021-02-12 22:56:06.000,0.4.0,10.0,scispacy,,,,,406.0,395.0,https://pypi.org/project/scispacy,2021-02-12 22:56:06.000,11.0,25853.0,25853.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +512,arq,samuelcolvin/arq,data-pipelines,,https://github.com/samuelcolvin/arq,https://github.com/samuelcolvin/arq,MIT,2016-07-21 18:24:42.000,2022-01-31 17:48:54.000000,2022-01-26 12:40:58,318.0,4.0,86,25.0,163.0,34.0,93.0,1088,Fast job queuing and RPC in python with asyncio and redis.,35.0,25,True,2021-09-02 12:45:02.000,0.22,55.0,arq,conda-forge/arq,,,,192.0,182.0,https://pypi.org/project/arq,2021-09-02 12:46:58.000,10.0,18330.0,18504.0,https://anaconda.org/conda-forge/arq,2021-09-03 10:08:17.446,1746.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +513,pandasql,yhat/pandasql,data-containers,,https://github.com/yhat/pandasql,https://github.com/yhat/pandasql,MIT,2013-02-18 01:53:56.000,2021-06-14 19:49:10.558000,2017-02-01 15:40:30,127.0,,148,45.0,27.0,44.0,23.0,1078,sqldf for pandas.,15.0,25,False,2016-04-20 21:52:36.000,0.7.3,31.0,pandasql,conda-forge/pandasql,,,['pandas'],1169.0,1105.0,https://pypi.org/project/pandasql,2016-04-20 21:52:36.000,64.0,1403796.0,1422105.0,https://anaconda.org/conda-forge/pandasql,2021-06-14 19:49:10.558,146472.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +514,ffn,pmorissette/ffn,financial-data,,https://github.com/pmorissette/ffn,https://github.com/pmorissette/ffn,MIT,2014-06-19 15:54:09.000,2022-02-09 19:11:08.000000,2022-02-09 19:11:08,354.0,3.0,200,58.0,64.0,16.0,80.0,1072,ffn - a financial function library for Python.,26.0,25,True,2021-04-21 02:47:21.000,0.3.6,27.0,ffn,conda-forge/ffn,,,,190.0,165.0,https://pypi.org/project/ffn,2021-04-21 02:47:21.000,25.0,27523.0,27587.0,https://anaconda.org/conda-forge/ffn,2021-04-22 14:02:56.125,640.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +515,Labml,labmlai/labml,ml-experiments,,https://github.com/labmlai/labml,https://github.com/labmlai/labml,MIT,2018-11-16 09:34:48.000,2022-02-05 10:39:45.000000,2022-02-05 10:39:42,1185.0,46.0,71,28.0,58.0,13.0,12.0,1005,Monitor deep learning model training and hardware usage from your mobile phone.,6.0,25,True,2022-01-18 11:14:34.000,0.4.144,121.0,labml,,,,,48.0,42.0,https://pypi.org/project/labml,2022-01-18 11:14:34.000,6.0,7599.0,7599.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +516,audiomentations,iver56/audiomentations,audio,,https://github.com/iver56/audiomentations,https://github.com/iver56/audiomentations,MIT,2019-02-12 16:36:24.000,2022-02-10 13:07:58.000000,2022-02-10 13:07:55,606.0,74.0,112,14.0,57.0,27.0,71.0,857,A Python library for audio data augmentation. Inspired by albumentations. Useful for machine learning.,21.0,25,True,2022-02-10 09:16:07.000,0.21.0,23.0,audiomentations,,,,,110.0,110.0,https://pypi.org/project/audiomentations,2022-02-10 09:16:07.000,,2808.0,2808.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +517,bambi,bambinos/bambi,probabilistics,,https://github.com/bambinos/bambi,https://github.com/bambinos/bambi,MIT,2016-05-16 03:21:00.000,2022-02-10 12:02:33.000000,2022-01-21 07:01:19,626.0,16.0,76,25.0,230.0,38.0,183.0,741,BAyesian Model-Building Interface (Bambi) in Python.,21.0,25,True,2022-01-15 01:38:30.000,0.7.1,19.0,bambi,conda-forge/bambi,,,,24.0,21.0,https://pypi.org/project/bambi,2022-01-15 01:38:30.000,3.0,2486.0,2696.0,https://anaconda.org/conda-forge/bambi,2022-01-18 20:23:31.895,6327.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +518,scikit-multilearn,scikit-multilearn/scikit-multilearn,sklearn-utils,,https://github.com/scikit-multilearn/scikit-multilearn,https://github.com/scikit-multilearn/scikit-multilearn,BSD-2-Clause,2014-04-30 13:05:44.000,2022-02-10 06:23:08.000000,2019-05-21 11:29:06,487.0,,137,35.0,61.0,76.0,94.0,720,A scikit-learn based module for multi-label et. al. classification.,15.0,25,False,2018-12-10 16:24:47.000,0.2.0,6.0,scikit-multilearn,,,,['sklearn'],669.0,651.0,https://pypi.org/project/scikit-multilearn,2018-12-10 16:24:47.000,18.0,63413.0,63413.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +519,NeuPy,itdxer/neupy,ml-frameworks,,https://github.com/itdxer/neupy,https://github.com/itdxer/neupy,MIT,2015-08-24 19:45:11.000,2022-01-13 00:49:03.000000,2019-09-02 19:02:38,1145.0,,149,33.0,22.0,32.0,234.0,701,NeuPy is a Tensorflow based python library for prototyping and building neural networks.,7.0,25,False,2019-04-04 19:44:59.000,0.8.2,34.0,neupy,,,,,135.0,123.0,https://pypi.org/project/neupy,2019-04-04 19:43:06.000,12.0,2244.0,2244.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +520,scikit-lego,koaning/scikit-lego,sklearn-utils,,https://github.com/koaning/scikit-lego,https://github.com/koaning/scikit-lego,MIT,2019-01-21 15:30:15.000,2021-12-21 18:05:34.000000,2021-12-21 08:08:48,421.0,6.0,77,16.0,264.0,32.0,205.0,696,Extra blocks for scikit-learn pipelines.,48.0,25,True,2021-12-09 11:34:28.000,0.6.9,35.0,scikit-lego,conda-forge/scikit-lego,,,['sklearn'],46.0,40.0,https://pypi.org/project/scikit-lego,2021-12-09 11:39:03.000,6.0,16533.0,17137.0,https://anaconda.org/conda-forge/scikit-lego,2021-12-09 15:20:11.388,16931.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +521,Guild AI,guildai/guildai,ml-experiments,,https://github.com/guildai/guildai,https://github.com/guildai/guildai,Apache-2.0,2017-09-27 18:57:50.000,2022-02-09 12:45:08.000000,2022-02-09 12:44:52,4689.0,126.0,59,13.0,23.0,116.0,182.0,657,"Experiment tracking, ML developer tools.",18.0,25,True,2022-02-07 16:31:34.000,0.7.5,178.0,guildai,,,,,42.0,42.0,https://pypi.org/project/guildai,2022-02-07 16:31:34.000,,3780.0,3780.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +522,icevision,airctic/icevision,image,,https://github.com/airctic/icevision,https://github.com/airctic/icevision,Apache-2.0,2020-05-04 01:57:02.000,2022-02-10 15:03:06.000000,2022-02-10 15:03:05,1207.0,44.0,86,19.0,549.0,136.0,486.0,578,"An Agnostic Computer Vision Framework - Pluggable to any Training Library: Fastai, Pytorch-Lightning with more to come.",36.0,25,True,2021-11-19 20:16:59.000,0.11.0,40.0,icevision,,,,,5.0,,https://pypi.org/project/icevision,2021-11-19 20:16:59.000,5.0,1853.0,1853.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, +523,Cornac,PreferredAI/cornac,recommender-systems,,https://github.com/PreferredAI/cornac,https://github.com/PreferredAI/cornac,Apache-2.0,2018-07-17 06:31:35.000,2022-01-03 09:48:49.000000,2021-09-30 10:13:24,1230.0,,86,22.0,380.0,8.0,77.0,528,A Comparative Framework for Multimodal Recommender Systems.,13.0,25,True,2021-09-26 07:01:44.000,1.14.1,45.0,cornac,conda-forge/cornac,,,,89.0,75.0,https://pypi.org/project/cornac,2021-09-26 07:12:34.000,14.0,9161.0,15220.0,https://anaconda.org/conda-forge/cornac,2021-11-15 19:24:15.089,199956.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +524,SKLL,EducationalTestingService/skll,ml-experiments,,https://github.com/EducationalTestingService/skll,https://github.com/EducationalTestingService/skll,BSD-1-Clause,2013-08-02 14:31:46.000,2021-12-29 21:39:23.000000,2021-12-21 20:03:06,3575.0,57.0,65,47.0,318.0,32.0,365.0,527,SciKit-Learn Laboratory (SKLL) makes it easy to run machine learning experiments.,36.0,25,False,2021-12-21 20:12:29.000,3.0,65.0,skll,conda-forge/skll,,,['sklearn'],53.0,35.0,https://pypi.org/project/skll,2021-12-21 20:08:55.000,18.0,619.0,671.0,https://anaconda.org/conda-forge/skll,2021-12-21 22:47:22.431,158.0,,,,,3.0,11.0,,,,,,,,,,,,,,,,,,,, +525,responsible-ai-widgets,microsoft/responsible-ai-toolbox,interpretability,,https://github.com/microsoft/responsible-ai-toolbox,https://github.com/microsoft/responsible-ai-toolbox,MIT,2020-07-06 20:46:53.000,2022-02-10 14:14:54.000000,2022-02-10 13:27:10,869.0,164.0,98,17.0,989.0,64.0,174.0,419,"This project provides responsible AI user interfaces for Fairlearn, interpret-community, and Error Analysis, as well..",24.0,25,True,2022-01-05 18:03:24.000,0.16.0,31.0,raiwidgets,,,,"['pytorch', 'tensorflow', 'jupyter']",22.0,20.0,https://pypi.org/project/raiwidgets,2022-01-05 15:23:45.000,2.0,5801.0,5801.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +526,sklearn-crfsuite,TeamHG-Memex/sklearn-crfsuite,sklearn-utils,,https://github.com/TeamHG-Memex/sklearn-crfsuite,https://github.com/TeamHG-Memex/sklearn-crfsuite,MIT,2015-11-26 21:15:41.000,2021-10-27 17:57:56.000000,2019-12-05 08:17:22,46.0,,177,21.0,14.0,37.0,23.0,390,scikit-learn inspired API for CRFsuite.,6.0,25,False,2017-06-22 18:49:27.000,0.3.6,9.0,sklearn-crfsuite,conda-forge/sklearn-crfsuite,,,['sklearn'],3760.0,3494.0,https://pypi.org/project/sklearn-crfsuite,2017-06-22 18:49:27.000,266.0,132424.0,133159.0,https://anaconda.org/conda-forge/sklearn-crfsuite,2020-04-03 10:45:56.342,16190.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +527,pyvips,libvips/pyvips,image,,https://github.com/libvips/pyvips,https://github.com/libvips/pyvips,MIT,2017-07-28 16:39:43.000,2021-12-30 09:47:00.631000,2021-12-15 10:05:34,411.0,5.0,37,7.0,34.0,102.0,164.0,387,python binding for libvips using cffi.,12.0,25,True,2021-11-20 11:46:55.000,2.1.16,22.0,pyvips,conda-forge/pyvips,,,,299.0,271.0,https://pypi.org/project/pyvips,2021-11-20 11:46:55.000,28.0,16774.0,17259.0,https://anaconda.org/conda-forge/pyvips,2021-12-30 09:47:00.631,14556.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +528,vega,vega/ipyvega,data-viz,,https://github.com/vega/ipyvega,https://github.com/vega/ipyvega,BSD-3-Clause,2015-08-04 03:22:47.000,2022-02-10 13:26:24.004000,2022-02-10 01:58:48,561.0,24.0,59,30.0,306.0,12.0,82.0,322,IPython/Jupyter notebook module for Vega and Vega-Lite.,11.0,25,True,2022-02-10 02:01:39.000,3.6.0,39.0,vega,conda-forge/vega,,,['jupyter'],84.0,,https://pypi.org/project/vega,2022-02-10 02:01:39.000,84.0,9603.0,16544.0,https://anaconda.org/conda-forge/vega,2022-02-10 13:26:24.004,472024.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +529,deep-daze,lucidrains/deep-daze,image,,https://github.com/lucidrains/deep-daze,https://github.com/lucidrains/deep-daze,MIT,2021-01-17 06:00:50.000,2022-01-26 17:14:40.000000,2022-01-26 17:13:56,230.0,1.0,290,73.0,37.0,86.0,72.0,4057,Simple command line tool for text to image generation using OpenAIs CLIP and Siren (Implicit neural representation..,13.0,24,True,2022-01-26 17:14:40.000,0.11.0,66.0,deep-daze,,,,,33.0,33.0,https://pypi.org/project/deep-daze,2022-01-26 17:14:40.000,,12809.0,12809.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +530,DALI,NVIDIA/DALI,gpu-utilities,,https://github.com/NVIDIA/DALI,https://github.com/NVIDIA/DALI,Apache-2.0,2018-06-01 22:18:01.000,2022-02-10 14:31:29.000000,2022-02-10 13:51:14,2347.0,118.0,464,83.0,2579.0,148.0,937.0,3698,A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to..,69.0,24,True,2022-01-25 10:44:54.000,1.10.0,48.0,,,,,,,,,,,,,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +531,MatchZoo,NTMC-Community/MatchZoo,nlp,,https://github.com/NTMC-Community/MatchZoo,https://github.com/NTMC-Community/MatchZoo,Apache-2.0,2017-06-08 08:55:22.000,2021-06-03 02:58:49.000000,2021-06-02 17:38:16,1810.0,,908,178.0,385.0,30.0,429.0,3590,"Facilitating the design, comparison and sharing of deep text matching models.",36.0,24,True,2019-10-24 13:09:11.000,2.2.0,5.0,matchzoo,,,,['tensorflow'],10.0,10.0,https://pypi.org/project/matchzoo,2019-10-24 13:09:11.000,,91.0,91.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +532,Image Super-Resolution,idealo/image-super-resolution,image,,https://github.com/idealo/image-super-resolution,https://github.com/idealo/image-super-resolution,Apache-2.0,2018-11-26 13:41:13.000,2022-01-23 11:27:35.000000,2021-06-02 09:45:13,150.0,,598,95.0,32.0,83.0,108.0,3406,Super-scale your images and run experiments with Residual Dense and Adversarial Networks.,10.0,24,True,2020-01-08 15:37:35.000,2.2.0,11.0,ISR,,idealo/image-super-resolution-gpu,,['tensorflow'],76.0,71.0,https://pypi.org/project/ISR,2020-01-08 15:37:35.000,5.0,4892.0,4897.0,,,,https://hub.docker.com/r/idealo/image-super-resolution-gpu,2019-04-01 13:48:45.697251,,199.0,3.0,,,,,,,,,,,,,,,,,,,,, +533,LIT,PAIR-code/lit,interpretability,,https://github.com/PAIR-code/lit,https://github.com/PAIR-code/lit,Apache-2.0,2020-07-28 13:07:26.000,2022-02-10 10:20:36.000000,2021-12-21 14:10:50,506.0,38.0,282,73.0,553.0,63.0,63.0,2812,The Language Interpretability Tool: Interactively analyze NLP models for model understanding in an extensible and..,18.0,24,True,2021-12-21 14:29:03.000,0.4.1,7.0,lit-nlp,conda-forge/lit-nlp,,,,7.0,7.0,https://pypi.org/project/lit-nlp,2021-12-21 14:20:06.000,,1126.0,3015.0,https://anaconda.org/conda-forge/lit-nlp,2021-11-09 18:19:30.401,32120.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +534,pytorchvideo,facebookresearch/pytorchvideo,image,,https://github.com/facebookresearch/pytorchvideo,https://github.com/facebookresearch/pytorchvideo,Apache-2.0,2021-03-09 20:39:13.000,2022-02-08 19:52:04.000000,2022-02-08 19:52:01,117.0,8.0,218,48.0,58.0,53.0,75.0,2258,A deep learning library for video understanding research.,25.0,24,True,2022-01-20 00:16:35.000,0.1.5,9.0,pytorchvideo,,,,['pytorch'],5.0,,https://pypi.org/project/pytorchvideo,2022-01-20 00:16:35.000,5.0,14459.0,14459.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +535,HiPlot,facebookresearch/hiplot,data-viz,,https://github.com/facebookresearch/hiplot,https://github.com/facebookresearch/hiplot,MIT,2019-11-08 13:06:41.000,2022-02-07 21:50:08.000000,2022-02-07 21:22:08,180.0,3.0,109,28.0,158.0,12.0,61.0,2251,HiPlot makes understanding high dimensional data easy.,7.0,24,True,2021-11-04 14:37:14.000,0.1.32,94.0,hiplot,conda-forge/hiplot,,,,12.0,3.0,https://pypi.org/project/hiplot,2021-11-05 18:07:40.000,9.0,10922.0,14109.0,https://anaconda.org/conda-forge/hiplot,2021-11-05 06:41:13.441,76495.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +536,python_speech_features,jameslyons/python_speech_features,audio,,https://github.com/jameslyons/python_speech_features,https://github.com/jameslyons/python_speech_features,MIT,2013-10-31 02:42:08.000,2021-10-20 10:08:48.000000,2020-12-31 13:27:01,120.0,,582,87.0,29.0,23.0,51.0,2032,This library provides common speech features for ASR including MFCCs and filterbank energies.,19.0,24,False,2020-01-14 14:12:10.000,0.6.1,6.0,python_speech_features,,,,,161.0,,https://pypi.org/project/python_speech_features,2017-08-16 01:46:13.000,161.0,104534.0,104534.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +537,SRU,asappresearch/sru,pytorch-utils,,https://github.com/asappresearch/sru,https://github.com/asappresearch/sru,MIT,2017-08-28 20:37:41.000,2022-01-04 21:17:53.000000,2021-05-19 15:52:48,400.0,,295,68.0,78.0,54.0,67.0,2020,Training RNNs as Fast as CNNs (https://arxiv.org/abs/1709.02755).,21.0,24,True,2021-05-18 16:13:10.000,2.6.0,32.0,sru,,,,['pytorch'],20.0,17.0,https://pypi.org/project/sru,2021-06-17 23:33:37.000,3.0,4204.0,4204.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +538,PyFlux,RJT1990/pyflux,time-series-data,,https://github.com/RJT1990/pyflux,https://github.com/RJT1990/pyflux,BSD-3-Clause,2016-02-16 20:12:02.000,2019-03-19 10:45:02.000000,2018-12-16 15:30:13,118.0,,219,70.0,20.0,82.0,65.0,1944,Open source time series library for Python.,6.0,24,False,2017-11-21 16:27:06.000,0.4.16,35.0,pyflux,,,,,226.0,210.0,https://pypi.org/project/pyflux,2017-11-21 16:27:06.000,16.0,38202.0,38202.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +539,Multicore-TSNE,DmitryUlyanov/Multicore-TSNE,data-viz,,https://github.com/DmitryUlyanov/Multicore-TSNE,https://github.com/DmitryUlyanov/Multicore-TSNE,BSD-3-Clause,2016-10-19 05:46:52.000,2021-11-09 17:22:51.512000,2020-08-19 14:58:00,113.0,,200,40.0,34.0,37.0,21.0,1675,Parallel t-SNE implementation with Python and Torch wrappers.,15.0,24,False,2017-11-08 13:32:20.000,0.0.1,3.0,MulticoreTSNE,conda-forge/multicore-tsne,,,['pytorch'],298.0,275.0,https://pypi.org/project/MulticoreTSNE,2019-01-09 07:23:04.000,23.0,8111.0,8430.0,https://anaconda.org/conda-forge/multicore-tsne,2021-11-09 17:22:51.512,12445.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +540,modAL,modAL-python/modAL,others,,https://github.com/modAL-python/modAL,https://github.com/modAL-python/modAL,MIT,2017-11-14 14:01:15.000,2022-02-07 09:11:55.000000,2021-01-07 09:40:40,648.0,,234,42.0,32.0,65.0,54.0,1602,A modular active learning framework for Python.,14.0,24,False,2021-01-07 09:47:49.000,0.4.1,12.0,modAL,,,,['sklearn'],121.0,114.0,https://pypi.org/project/modAL,2021-01-07 09:47:49.000,7.0,3816.0,3816.0,,,,,,,,3.0,20.0,,,,,,,,,,,,,,,,,,,, +541,TabNet,dreamquark-ai/tabnet,pytorch-utils,,https://github.com/dreamquark-ai/tabnet,https://github.com/dreamquark-ai/tabnet,MIT,2019-10-17 11:17:32.000,2022-02-08 10:53:27.000000,2021-12-27 18:05:53,170.0,5.0,323,36.0,173.0,38.0,170.0,1569,PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf.,19.0,24,True,2021-02-02 08:05:11.000,3.1.1,17.0,pytorch-tabnet,conda-forge/pytorch-tabnet,,,['pytorch'],7.0,,https://pypi.org/project/pytorch-tabnet,2021-02-02 08:05:11.000,7.0,22997.0,23056.0,https://anaconda.org/conda-forge/pytorch-tabnet,2021-12-30 20:05:02.340,119.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +542,Karate Club,benedekrozemberczki/karateclub,graph,,https://github.com/benedekrozemberczki/karateclub,https://github.com/benedekrozemberczki/karateclub,GPL-3.0,2019-12-05 17:35:56.000,2022-01-28 14:45:25.910000,2022-01-22 19:25:00,2206.0,6.0,182,39.0,18.0,1.0,65.0,1509,Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020).,13.0,24,False,2022-01-22 19:35:55.000,_10203,102.0,karateclub,conda-forge/karateclub,,,,74.0,72.0,https://pypi.org/project/karateclub,2022-01-22 19:34:31.000,2.0,6326.0,6736.0,https://anaconda.org/conda-forge/karateclub,2022-01-28 14:45:25.910,7792.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +543,fklearn,nubank/fklearn,ml-frameworks,,https://github.com/nubank/fklearn,https://github.com/nubank/fklearn,Apache-2.0,2019-02-27 14:32:57.000,2022-02-08 19:36:06.000000,2022-02-04 14:13:36,135.0,8.0,157,87.0,146.0,21.0,21.0,1380,fklearn: Functional Machine Learning.,41.0,24,True,2021-12-30 01:18:22.000,2.0.0,24.0,fklearn,,,,,11.0,11.0,https://pypi.org/project/fklearn,2021-12-30 01:18:22.000,,4019.0,4019.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +544,sense2vec,explosion/sense2vec,nlp,,https://github.com/explosion/sense2vec,https://github.com/explosion/sense2vec,MIT,2016-01-23 22:15:49.000,2021-08-16 11:44:51.000000,2021-08-16 11:44:51,454.0,,220,44.0,41.0,19.0,88.0,1339,Contextually-keyed word vectors.,17.0,24,True,2021-04-19 07:05:28.000,3.0.0,22.0,sense2vec,conda-forge/sense2vec,,,,126.0,118.0,https://pypi.org/project/sense2vec,2021-04-19 07:05:28.000,8.0,9288.0,10662.0,https://anaconda.org/conda-forge/sense2vec,2021-07-14 13:20:19.752,24247.0,,,,,3.0,24788.0,,,,,,,,,,,,,,,,,,,, +545,Orbit,uber/orbit,probabilistics,,https://github.com/uber/orbit,https://github.com/uber/orbit,Apache-2.0,2020-01-07 18:20:37.000,2022-02-09 23:42:05.000000,2022-01-27 02:03:13,779.0,38.0,83,29.0,362.0,51.0,280.0,1225,A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.,16.0,24,True,2022-01-12 00:42:13.000,1.1.0,16.0,orbit-ml,,,,,7.0,6.0,https://pypi.org/project/orbit-ml,2022-01-12 00:42:13.000,1.0,5978.0,5978.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +546,graph4nlp,graph4ai/graph4nlp,graph,,https://github.com/graph4ai/graph4nlp,https://github.com/graph4ai/graph4nlp,Apache-2.0,2020-07-16 03:28:48.000,2022-02-10 14:52:14.000000,2022-01-20 17:33:52,1922.0,81.0,143,26.0,389.0,8.0,97.0,1184,Graph4nlp is the library for the easy use of Graph Neural Networks for NLP. Welcome to visit our DLG4NLP website..,23.0,24,True,2022-01-20 18:07:32.000,0.5.5,11.0,graph4nlp,,,,['pytorch'],,,https://pypi.org/project/graph4nlp,2022-01-20 15:18:44.000,,153.0,153.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +547,Sockeye,awslabs/sockeye,nlp,,https://github.com/awslabs/sockeye,https://github.com/awslabs/sockeye,Apache-2.0,2017-06-08 07:44:30.000,2022-02-09 19:37:45.000000,2022-02-09 19:36:56,789.0,23.0,304,49.0,742.0,10.0,263.0,1044,Sequence-to-sequence framework with a focus on Neural Machine Translation based on PyTorch.,55.0,24,True,2022-02-09 19:16:10.000,3.0.15,72.0,sockeye,,,,['mxnet'],2.0,,https://pypi.org/project/sockeye,2022-02-09 19:16:10.000,2.0,1257.0,1257.0,,,,,,,,3.0,14.0,,,,,,,,,,,,,,,,,,,, +548,TFEncrypted,tf-encrypted/tf-encrypted,privacy-ml,,https://github.com/tf-encrypted/tf-encrypted,https://github.com/tf-encrypted/tf-encrypted,Apache-2.0,2018-03-21 18:22:13.000,2022-01-09 02:02:33.000000,2020-08-19 16:56:56,595.0,,170,56.0,440.0,169.0,243.0,974,A Framework for Encrypted Machine Learning in TensorFlow.,28.0,24,False,2019-09-27 20:00:01.000,0.5.9,35.0,tf-encrypted,,,,['tensorflow'],68.0,59.0,https://pypi.org/project/tf-encrypted,2019-10-21 18:05:53.000,9.0,671.0,671.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +549,openTSNE,pavlin-policar/openTSNE,data-viz,,https://github.com/pavlin-policar/openTSNE,https://github.com/pavlin-policar/openTSNE,BSD-3-Clause,2018-06-08 18:42:09.000,2021-11-13 15:59:24.399000,2021-10-25 08:00:42,578.0,,103,25.0,104.0,6.0,95.0,944,"Extensible, parallel implementations of t-SNE.",10.0,24,True,2021-10-25 08:35:29.000,0.6.1,22.0,opentsne,conda-forge/opentsne,,,,293.0,285.0,https://pypi.org/project/opentsne,2021-10-25 08:35:29.000,8.0,22913.0,26329.0,https://anaconda.org/conda-forge/opentsne,2021-11-13 15:59:24.399,129831.0,,,,,3.0,,,,,,,,,-2.0,,,,,,,,,,,, +550,cuGraph,rapidsai/cugraph,gpu-utilities,,https://github.com/rapidsai/cugraph,https://github.com/rapidsai/cugraph,Apache-2.0,2018-11-15 18:07:11.000,2022-02-10 14:30:46.000000,2022-02-10 14:30:45,5180.0,96.0,174,41.0,1324.0,87.0,671.0,917,cuGraph - RAPIDS Graph Analytics Library.,75.0,24,True,2022-02-02 20:27:08.000,22.02.00,17.0,cugraph,conda-forge/libcugraph,,,,1.0,,https://pypi.org/project/cugraph,2020-06-01 20:09:06.000,1.0,174.0,792.0,https://anaconda.org/conda-forge/libcugraph,2021-04-29 03:53:20.856,6186.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +551,scikit-cuda,lebedov/scikit-cuda,gpu-utilities,,https://github.com/lebedov/scikit-cuda,https://github.com/lebedov/scikit-cuda,BSD-3-Clause,2010-09-27 02:02:07.000,2021-07-13 12:58:06.000000,2021-07-13 12:58:06,1032.0,,168,46.0,110.0,50.0,168.0,876,Python interface to GPU-powered libraries.,45.0,24,True,2019-05-27 00:29:00.000,0.5.3,7.0,scikit-cuda,,,,,206.0,162.0,https://pypi.org/project/scikit-cuda,2019-05-27 00:29:00.000,44.0,866.0,866.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +552,Node2Vec,eliorc/node2vec,graph,,https://github.com/eliorc/node2vec,https://github.com/eliorc/node2vec,MIT,2017-12-08 13:30:06.000,2021-12-30 15:36:37.000000,2021-10-09 06:09:16,64.0,,188,17.0,13.0,,71.0,847,Implementation of the node2vec algorithm.,9.0,24,True,2021-10-09 06:10:48.000,0.4.4,15.0,node2vec,conda-forge/node2vec,,,,14.0,,https://pypi.org/project/node2vec,2021-10-09 06:07:52.000,14.0,541177.0,541618.0,https://anaconda.org/conda-forge/node2vec,2020-04-25 22:41:13.714,19865.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +553,kapre,keunwoochoi/kapre,audio,,https://github.com/keunwoochoi/kapre,https://github.com/keunwoochoi/kapre,MIT,2016-12-14 18:36:36.000,2022-01-21 20:10:47.000000,2022-01-21 20:08:28,194.0,4.0,140,21.0,44.0,12.0,82.0,801,kapre: Keras Audio Preprocessors.,13.0,24,True,2022-01-21 20:10:47.000,Kapre-0.3.7,23.0,kapre,,,,['tensorflow'],1367.0,1353.0,https://pypi.org/project/kapre,2022-01-21 20:09:21.000,14.0,2172.0,2172.0,,,,,,,,3.0,19.0,,,,,,,,,,,,,,,,,,,, +554,avalanche,ContinualAI/avalanche,others,,https://github.com/ContinualAI/avalanche,https://github.com/ContinualAI/avalanche,MIT,2020-03-05 11:32:13.000,2022-02-09 09:09:16.000000,2022-02-09 09:09:16,2376.0,185.0,113,26.0,324.0,71.0,391.0,729,Avalanche: an End-to-End Library for Continual Learning.,49.0,24,True,2021-12-16 14:35:52.000,0.1.0,2.0,avalanche-lib,,,,,,,https://pypi.org/project/avalanche-lib,2021-12-16 14:35:52.000,,244.0,244.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +555,gmaps,pbugnion/gmaps,geospatial-data,,https://github.com/pbugnion/gmaps,https://github.com/pbugnion/gmaps,BSD-3-Clause,2014-12-01 09:12:06.000,2021-12-15 15:42:57.506000,2019-07-22 06:22:45,1380.0,,146,26.0,153.0,67.0,136.0,728,Google maps for Jupyter notebooks.,16.0,24,False,2019-07-21 08:49:48.715,0.9.0,95.0,gmaps,conda-forge/gmaps,,,['jupyter'],45.0,1.0,https://pypi.org/project/gmaps,2021-12-15 15:42:57.506,44.0,15247.0,20601.0,https://anaconda.org/conda-forge/gmaps,2019-08-02 11:56:50.940,251879.0,,,,,3.0,,,jupyter-gmaps,https://www.npmjs.com/package/jupyter-gmaps,2019-07-21 08:49:48.715,,936.0,,,,,,,,,,,,,, +556,AutoViz,AutoViML/AutoViz,data-viz,,https://github.com/AutoViML/AutoViz,https://github.com/AutoViML/AutoViz,Apache-2.0,2019-07-17 17:14:06.000,2022-02-05 14:11:44.000000,2022-02-05 14:11:33,124.0,19.0,92,28.0,15.0,6.0,41.0,633,"Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators..",11.0,24,True,2021-12-25 14:36:42.000,0.1.35,47.0,autoviz,conda-forge/autoviz,,,,136.0,133.0,https://pypi.org/project/autoviz,2021-12-25 14:36:42.000,3.0,36610.0,36959.0,https://anaconda.org/conda-forge/autoviz,2021-12-25 18:54:44.874,2094.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +557,Mapbox GL,mapbox/mapboxgl-jupyter,geospatial-data,,https://github.com/mapbox/mapboxgl-jupyter,https://github.com/mapbox/mapboxgl-jupyter,MIT,2017-08-08 15:10:51.000,2022-01-11 05:18:07.000000,2021-04-19 05:00:36,221.0,,126,104.0,91.0,35.0,67.0,599,Use Mapbox GL JS to visualize data in a Python Jupyter notebook.,21.0,24,True,2019-06-03 21:24:10.000,0.10.2,20.0,mapboxgl,,,,['jupyter'],139.0,125.0,https://pypi.org/project/mapboxgl,2019-06-02 15:18:57.000,14.0,16997.0,16997.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +558,sahi,obss/sahi,image,,https://github.com/obss/sahi,https://github.com/obss/sahi,MIT,2021-01-30 12:54:53.000,2022-02-07 19:43:13.000000,2022-02-07 19:43:11,293.0,85.0,83,16.0,281.0,8.0,83.0,535,A lightweight vision library for performing large scale object detection/ instance segmentation.,8.0,24,True,2022-01-13 08:26:35.000,0.8.22,71.0,sahi,conda-forge/sahi,,,,23.0,19.0,https://pypi.org/project/sahi,2022-01-13 08:26:35.000,4.0,11723.0,12041.0,https://anaconda.org/conda-forge/sahi,2022-01-13 11:03:28.978,1272.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, +559,python-soundfile,bastibe/python-soundfile,audio,,https://github.com/bastibe/python-soundfile,https://github.com/bastibe/python-soundfile,BSD-3-Clause,2013-08-27 13:36:52.000,2022-02-09 13:02:35.000000,2022-01-28 08:07:58,503.0,2.0,59,17.0,163.0,63.0,99.0,434,"SoundFile is an audio library based on libsndfile, CFFI, and NumPy.",23.0,24,True,2019-12-04 10:03:39.000,0.10.3post1,8.0,soundfile,anaconda/pysoundfile,,,,539.0,,https://pypi.org/project/soundfile,2019-11-27 12:16:19.000,539.0,884839.0,884869.0,https://anaconda.org/anaconda/pysoundfile,,,,,,,3.0,2880.0,,,,,,,,,,,,,,,,,,,, +560,findspark,minrk/findspark,others,,https://github.com/minrk/findspark,https://github.com/minrk/findspark,BSD-3-Clause,2015-06-12 21:34:06.000,2022-01-19 10:22:18.339000,2022-01-17 12:56:54,72.0,1.0,66,8.0,16.0,12.0,10.0,428,Find pyspark to make it importable.,14.0,24,True,2022-01-17 12:57:58.000,2.0.0,13.0,findspark,conda-forge/findspark,,,['spark'],2361.0,2225.0,https://pypi.org/project/findspark,2022-01-17 12:57:58.000,136.0,2209829.0,2218770.0,https://anaconda.org/conda-forge/findspark,2022-01-19 10:22:18.339,607997.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +561,TensorFlow Cloud,tensorflow/cloud,tensorflow-utils,,https://github.com/tensorflow/cloud,https://github.com/tensorflow/cloud,Apache-2.0,2020-02-10 18:51:59.000,2022-01-11 21:12:58.000000,2022-01-04 23:14:55,567.0,2.0,66,23.0,301.0,55.0,26.0,324,The TensorFlow Cloud repository provides APIs that will allow to easily go from debugging and training your Keras and..,26.0,24,True,2021-06-17 01:15:10.000,0.1.16,19.0,tensorflow-cloud,,,,['tensorflow'],125.0,124.0,https://pypi.org/project/tensorflow-cloud,2021-06-17 01:15:10.000,1.0,263622.0,263622.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +562,NIPY,nipy/nipy,medical-data,,https://github.com/nipy/nipy,https://github.com/nipy/nipy,BSD-3-Clause,2010-05-02 10:00:33.000,2021-12-05 02:53:17.000000,2021-03-29 16:56:48,6427.0,,130,36.0,341.0,45.0,111.0,315,Neuroimaging in Python FMRI analysis package.,63.0,24,True,2018-02-19 14:14:08.000,0.4.2,6.0,nipy,conda-forge/nipy,,,,47.0,,https://pypi.org/project/nipy,2018-02-19 14:14:08.000,47.0,2859.0,4497.0,https://anaconda.org/conda-forge/nipy,2020-05-04 19:38:04.112,90112.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +563,Image Deduplicator,idealo/imagededup,image,,https://github.com/idealo/imagededup,https://github.com/idealo/imagededup,Apache-2.0,2019-04-05 12:10:54.000,2021-12-28 20:14:53.000000,2020-11-23 17:40:40,460.0,,342,60.0,73.0,31.0,59.0,3951,Finding duplicate images made easy!.,10.0,23,False,2020-11-23 17:55:24.000,0.2.4,9.0,imagededup,,,,['tensorflow'],24.0,22.0,https://pypi.org/project/imagededup,2020-11-22 21:09:36.000,2.0,2098.0,2098.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +564,neon,NervanaSystems/neon,ml-frameworks,,https://github.com/NervanaSystems/neon,https://github.com/NervanaSystems/neon,Apache-2.0,2014-10-16 01:00:17.000,2022-01-20 12:14:16.807000,2019-05-22 18:27:54,1118.0,,832,334.0,89.0,90.0,306.0,3855,Intel Nervana reference deep learning framework committed to best performance on all hardware.,109.0,23,False,2018-01-05 23:25:04.000,2.6.0,32.0,nervananeon,anaconda/neon,,,,1.0,,https://pypi.org/project/nervananeon,2018-01-05 23:25:04.000,1.0,119.0,135.0,https://anaconda.org/anaconda/neon,2022-01-20 12:14:16.807,894.0,,,,,3.0,317.0,,,,,,,,,,,,,,,,,,,, +565,PyTorch-BigGraph,facebookresearch/PyTorch-BigGraph,graph,,https://github.com/facebookresearch/PyTorch-BigGraph,https://github.com/facebookresearch/PyTorch-BigGraph,BSD-3-Clause,2018-10-01 20:41:16.000,2022-02-07 16:58:07.000000,2022-02-07 16:58:04,160.0,2.0,402,90.0,74.0,56.0,119.0,2999,Generate embeddings from large-scale graph-structured data.,25.0,23,True,2019-10-14 16:45:11.000,1.0.0,3.0,torchbiggraph,,,,['pytorch'],3.0,,https://pypi.org/project/torchbiggraph,2019-05-01 21:31:13.000,3.0,12993.0,12996.0,,,,,,,,3.0,122.0,,,,,,,,,,,,,,,,,,,, +566,PandasGUI,adamerose/pandasgui,data-viz,,https://github.com/adamerose/PandasGUI,https://github.com/adamerose/PandasGUI,MIT-0,2019-06-12 02:19:42.000,2022-01-27 16:45:09.000000,2022-01-17 19:49:10,713.0,7.0,165,50.0,30.0,35.0,115.0,2550,A GUI for Pandas DataFrames.,12.0,23,False,2021-08-14 09:14:51.000,0.2.13,43.0,pandasgui,conda-forge/pandasgui,,,['pandas'],134.0,129.0,https://pypi.org/project/pandasgui,2021-08-14 09:14:51.000,5.0,4838.0,5574.0,https://anaconda.org/conda-forge/pandasgui,2021-02-13 06:39:51.463,9571.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +567,knockknock,huggingface/knockknock,ml-experiments,,https://github.com/huggingface/knockknock,https://github.com/huggingface/knockknock,MIT,2019-03-20 13:08:55.000,2021-09-22 02:27:34.000000,2020-03-16 04:26:47,75.0,,198,54.0,36.0,14.0,23.0,2358,Knock Knock: Get notified when your training ends with only two additional lines of code.,18.0,23,False,2020-03-04 04:15:47.000,0.1.8,10.0,knockknock,conda-forge/knockknock,,,,244.0,241.0,https://pypi.org/project/knockknock,2020-03-16 14:30:23.000,3.0,1258.0,1561.0,https://anaconda.org/conda-forge/knockknock,2020-03-17 01:52:16.317,8484.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +568,Kashgari,BrikerMan/Kashgari,nlp,,https://github.com/BrikerMan/Kashgari,https://github.com/BrikerMan/Kashgari,Apache-2.0,2019-01-19 01:53:28.000,2021-07-09 03:57:16.000000,2021-07-09 03:57:16,955.0,,428,67.0,122.0,37.0,326.0,2256,Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-..,21.0,23,True,2021-07-04 10:44:36.000,2.0.2,24.0,kashgari-tf,,,,['tensorflow'],52.0,50.0,https://pypi.org/project/kashgari-tf,2019-10-18 07:57:55.000,2.0,105.0,105.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +569,lightseq,bytedance/lightseq,nlp,,https://github.com/bytedance/lightseq,https://github.com/bytedance/lightseq,Apache-2.0,2019-12-06 08:25:24.000,2022-02-10 07:13:09.000000,2022-02-09 10:40:06,185.0,11.0,209,43.0,119.0,79.0,70.0,1993,LightSeq: A High Performance Library for Sequence Processing and Generation.,8.0,23,True,2021-11-30 07:39:10.000,2.2.1,19.0,lightseq,,,,,,,https://pypi.org/project/lightseq,2022-01-26 08:26:27.000,,1679.0,1700.0,,,,,,,,3.0,564.0,,,,,,,,,,,,,,,,,,,, +570,auto_ml,ClimbsRocks/auto_ml,hyperopt,,https://github.com/ClimbsRocks/auto_ml,https://github.com/ClimbsRocks/auto_ml,MIT,2016-08-07 21:35:08.000,2021-02-10 07:52:35.000000,2018-03-25 19:46:25,1149.0,,298,95.0,45.0,185.0,216.0,1561,[UNMAINTAINED] Automated machine learning for analytics & production.,13.0,23,False,2018-02-22 01:13:03.000,2.9.10,78.0,auto_ml,,,,,3.0,,https://pypi.org/project/auto_ml,2018-02-22 01:13:03.000,3.0,2316.0,2316.0,,,,,,,,3.0,38.0,,,,,,,,,,,,,,,,,,,, +571,Magnitude,plasticityai/magnitude,nn-search,,https://github.com/plasticityai/magnitude,https://github.com/plasticityai/magnitude,MIT,2018-02-24 07:28:16.000,2021-02-23 18:10:43.000000,2020-07-17 20:19:46,350.0,,104,37.0,9.0,29.0,51.0,1506,"A fast, efficient universal vector embedding utility package.",4.0,23,False,2020-05-25 11:26:36.000,0.1.143,128.0,pymagnitude,,,,,228.0,217.0,https://pypi.org/project/pymagnitude,2020-05-25 11:26:36.000,11.0,5924.0,5924.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +572,EfficientNets,rwightman/gen-efficientnet-pytorch,pytorch-utils,,https://github.com/rwightman/gen-efficientnet-pytorch,https://github.com/rwightman/gen-efficientnet-pytorch,Apache-2.0,2019-05-11 19:35:56.000,2021-07-08 19:05:05.000000,2021-07-08 19:03:55,108.0,,192,45.0,11.0,1.0,50.0,1430,"Pretrained EfficientNet, EfficientNet-Lite, MixNet, MobileNetV3 / V2, MNASNet A1 and B1, FBNet, Single-Path NAS.",5.0,23,True,2021-07-08 19:05:05.000,1.0.2,10.0,geffnet,,,,['pytorch'],94.0,93.0,https://pypi.org/project/geffnet,2021-07-08 19:05:05.000,1.0,8976.0,8976.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +573,TNT,pytorch/tnt,ml-experiments,,https://github.com/pytorch/tnt,https://github.com/pytorch/tnt,BSD-3-Clause,2016-12-10 11:49:58.000,2021-01-22 09:14:29.000000,2021-01-05 19:36:17,156.0,,190,45.0,79.0,30.0,35.0,1361,"Simple tools for logging and visualizing, loading and training.",35.0,23,False,2019-11-15 12:57:59.000,0.0.5.1,3.0,torchnet,,,,['pytorch'],36.0,,https://pypi.org/project/torchnet,2018-07-29 23:16:03.000,36.0,17186.0,17186.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +574,Higher,facebookresearch/higher,pytorch-utils,,https://github.com/facebookresearch/higher,https://github.com/facebookresearch/higher,Apache-2.0,2019-09-06 18:58:36.000,2022-01-06 16:58:33.000000,2021-10-26 07:08:33,31.0,,94,28.0,30.0,48.0,50.0,1335,higher is a pytorch library allowing users to obtain higher order gradients over losses spanning training loops rather..,9.0,23,True,2020-07-14 12:20:32.000,0.2.1,2.0,higher,,,,['pytorch'],111.0,109.0,https://pypi.org/project/higher,2020-07-14 12:20:32.000,2.0,10029.0,10029.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +575,Pypeline,cgarciae/pypeln,data-pipelines,,https://github.com/cgarciae/pypeln,https://github.com/cgarciae/pypeln,MIT,2018-09-01 13:43:31.000,2022-01-06 18:29:36.168000,2022-01-06 15:29:14,238.0,3.0,77,38.0,34.0,15.0,42.0,1318,Concurrent data pipelines in Python .,12.0,23,True,2022-01-06 15:32:49.000,0.4.9,36.0,pypeln,conda-forge/pypeln,,,,9.0,,https://pypi.org/project/pypeln,2022-01-06 15:32:39.000,9.0,10382.0,10623.0,https://anaconda.org/conda-forge/pypeln,2022-01-06 18:29:36.168,4590.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +576,NiftyNet,NifTK/NiftyNet,medical-data,,https://github.com/NifTK/NiftyNet,https://github.com/NifTK/NiftyNet,Apache-2.0,2017-08-30 07:55:43.000,2020-04-21 19:54:52.000000,2020-04-21 19:54:51,3284.0,,389,89.0,165.0,102.0,224.0,1297,[unmaintained] An open-source convolutional neural networks platform for research in medical image analysis and image-..,59.0,23,False,2019-10-10 10:59:33.000,0.6.0,11.0,niftynet,,,,['tensorflow'],39.0,38.0,https://pypi.org/project/niftynet,2019-10-10 10:59:33.000,1.0,127.0,127.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +577,MLBox,AxeldeRomblay/MLBox,hyperopt,,https://github.com/AxeldeRomblay/MLBox,https://github.com/AxeldeRomblay/MLBox,BSD-1-Clause,2017-06-01 16:59:24.000,2022-02-10 00:14:04.000000,2020-08-25 09:26:27,1121.0,,257,64.0,44.0,18.0,74.0,1282,MLBox is a powerful Automated Machine Learning python library.,9.0,23,False,2020-08-25 09:32:37.000,0.8.5,21.0,mlbox,,,,,28.0,28.0,https://pypi.org/project/mlbox,2020-08-25 09:32:37.000,,1878.0,1878.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +578,TaskTiger,closeio/tasktiger,data-pipelines,,https://github.com/closeio/tasktiger,https://github.com/closeio/tasktiger,MIT,2015-05-14 00:26:32.000,2022-02-07 22:59:21.000000,2022-02-07 22:59:19,274.0,3.0,62,44.0,146.0,33.0,35.0,1102,Python task queue using Redis.,25.0,23,True,2021-12-02 17:42:13.000,0.16,26.0,tasktiger,,,,,32.0,22.0,https://pypi.org/project/tasktiger,2021-12-02 18:08:25.000,10.0,2242.0,2242.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +579,gplearn,trevorstephens/gplearn,others,,https://github.com/trevorstephens/gplearn,https://github.com/trevorstephens/gplearn,BSD-3-Clause,2015-03-26 01:01:14.000,2021-12-15 16:04:40.206000,2021-10-18 05:33:29,148.0,,189,51.0,76.0,46.0,129.0,1081,"Genetic Programming in Python, with a scikit-learn inspired API.",11.0,23,True,2019-06-01 02:04:52.000,0.4.1,6.0,gplearn,conda-forge/gplearn,,,['sklearn'],228.0,218.0,https://pypi.org/project/gplearn,2019-06-01 02:04:52.000,10.0,2717.0,2807.0,https://anaconda.org/conda-forge/gplearn,2020-06-18 15:08:21.371,1804.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +580,Explainability 360,Trusted-AI/AIX360,interpretability,,https://github.com/Trusted-AI/AIX360,https://github.com/Trusted-AI/AIX360,Apache-2.0,2019-07-11 07:17:48.000,2022-01-09 05:14:20.000000,2021-10-12 06:35:26,316.0,,216,50.0,84.0,38.0,25.0,1053,Interpretability and explainability of data and machine learning models.,29.0,23,True,2020-10-28 09:32:21.000,0.2.1,4.0,aix360,,,,,38.0,37.0,https://pypi.org/project/aix360,2020-10-28 09:18:17.000,1.0,1476.0,1476.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +581,ChainerRL,chainer/chainerrl,reinforcement-learning,,https://github.com/chainer/chainerrl,https://github.com/chainer/chainerrl,MIT,2017-01-30 04:58:15.000,2021-08-10 18:25:48.000000,2021-04-17 06:02:30,3471.0,,211,73.0,415.0,75.0,147.0,1029,ChainerRL is a deep reinforcement learning library built on top of Chainer.,29.0,23,True,2020-02-14 05:35:56.000,0.8.0,10.0,chainerrl,,,,,117.0,109.0,https://pypi.org/project/chainerrl,2020-02-14 05:35:56.000,8.0,533.0,533.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +582,minisom,JustGlowing/minisom,others,,https://github.com/JustGlowing/minisom,https://github.com/JustGlowing/minisom,CC-BY-3.0,2013-07-03 10:10:06.000,2022-01-25 08:28:57.000000,2022-01-25 08:28:57,461.0,2.0,311,30.0,35.0,10.0,89.0,1004,MiniSom is a minimalistic implementation of the Self Organizing Maps.,23.0,23,False,2021-04-24 17:22:39.000,2.2.9,1.0,minisom,,,,,231.0,226.0,https://pypi.org/project/minisom,2021-04-24 17:21:29.000,5.0,11883.0,11883.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +583,CrypTen,facebookresearch/CrypTen,privacy-ml,,https://github.com/facebookresearch/CrypTen,https://github.com/facebookresearch/CrypTen,MIT,2019-08-15 00:00:31.000,2022-01-31 18:49:12.000000,2022-01-31 18:49:10,318.0,9.0,155,34.0,231.0,32.0,107.0,991,A framework for Privacy Preserving Machine Learning.,25.0,23,True,2021-09-09 15:15:11.000,0.4.0,2.0,crypten,,,,['pytorch'],12.0,12.0,https://pypi.org/project/crypten,2021-09-09 15:15:11.000,,251.0,251.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +584,keract,philipperemy/keract,interpretability,,https://github.com/philipperemy/keract,https://github.com/philipperemy/keract,MIT,2017-05-17 04:50:57.000,2022-01-24 10:17:05.000000,2022-01-24 10:17:05,385.0,3.0,183,33.0,66.0,3.0,81.0,961,Layers Outputs and Gradients in Keras. Made easy.,16.0,23,True,2021-06-19 16:14:57.000,4.5.0,38.0,keract,,,,['tensorflow'],119.0,114.0,https://pypi.org/project/keract,2021-06-19 16:14:15.000,5.0,1222.0,1222.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +585,rubrix,recognai/rubrix,nlp,,https://github.com/recognai/rubrix,https://github.com/recognai/rubrix,Apache-2.0,2021-04-28 14:37:42.000,2022-02-10 15:00:36.000000,2022-02-10 15:00:32,805.0,282.0,72,13.0,680.0,74.0,342.0,842,Python framework for data-centric NLP.,18.0,23,True,2022-02-04 10:51:34.000,0.9.0,51.0,rubrix,conda-forge/rubrix,,,,,,https://pypi.org/project/rubrix,2022-02-02 22:03:59.000,,1376.0,1463.0,https://anaconda.org/conda-forge/rubrix,2022-02-03 07:15:30.949,174.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, +586,GPUtil,anderskm/gputil,gpu-utilities,,https://github.com/anderskm/gputil,https://github.com/anderskm/gputil,MIT,2017-01-16 11:57:43.000,2020-10-01 05:42:49.000000,2019-08-16 09:00:15,140.0,,90,11.0,17.0,11.0,14.0,823,A Python module for getting the GPU status from NVIDA GPUs using nvidia-smi programmically in Python.,13.0,23,False,2018-12-18 09:12:13.000,1.4.0,8.0,gputil,,,,,1845.0,1749.0,https://pypi.org/project/gputil,2018-12-18 09:12:13.000,96.0,465890.0,465890.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +587,AstroML,astroML/astroML,others,,https://github.com/astroML/astroML,https://github.com/astroML/astroML,BSD-2-Clause,2012-10-17 22:33:50.000,2022-01-26 16:44:10.982000,2022-01-25 22:01:32,555.0,7.0,277,95.0,112.0,58.0,87.0,798,"Machine learning, statistics, and data mining for astronomy and astrophysics.",30.0,23,True,2019-10-02 06:32:58.000,0.4.1,12.0,astroML,conda-forge/astroml,,,['sklearn'],33.0,,https://pypi.org/project/astroML,2022-01-25 21:56:31.000,33.0,2654.0,3159.0,https://anaconda.org/conda-forge/astroml,2022-01-26 16:44:10.982,27305.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +588,Pandas-Bokeh,PatrikHlobil/Pandas-Bokeh,data-viz,,https://github.com/PatrikHlobil/Pandas-Bokeh,https://github.com/PatrikHlobil/Pandas-Bokeh,MIT,2018-11-23 20:49:14.000,2022-01-11 12:46:13.000000,2022-01-11 12:44:45,291.0,1.0,95,23.0,27.0,29.0,66.0,757,Bokeh Plotting Backend for Pandas and GeoPandas.,13.0,23,True,2021-04-11 17:43:13.000,0.5.5,16.0,pandas-bokeh,,,,['pandas'],294.0,283.0,https://pypi.org/project/pandas-bokeh,2021-04-11 17:43:13.000,11.0,15814.0,15814.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +589,Prince,MaxHalford/prince,others,,https://github.com/MaxHalford/prince,https://github.com/MaxHalford/prince,MIT,2016-10-22 12:36:06.000,2021-12-28 17:01:09.000000,2021-12-28 17:01:09,209.0,13.0,133,20.0,22.0,35.0,68.0,756,"Python factor analysis library (PCA, CA, MCA, MFA, FAMD).",12.0,23,True,2020-10-06 11:26:47.000,0.7.1,41.0,prince,conda-forge/prince-factor-analysis,,,['sklearn'],182.0,177.0,https://pypi.org/project/prince,2020-10-06 11:26:47.000,5.0,17769.0,18112.0,https://anaconda.org/conda-forge/prince-factor-analysis,2021-04-30 17:46:15.443,9281.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +590,whylogs,whylabs/whylogs,data-pipelines,,https://github.com/whylabs/whylogs,https://github.com/whylabs/whylogs,Apache-2.0,2020-08-14 23:25:32.000,2022-02-10 14:27:30.000000,2022-02-09 18:12:09,886.0,60.0,39,21.0,339.0,48.0,63.0,750,Open standard for end-to-end data and ML monitoring for any scale in any infrastructure.,26.0,23,True,2022-02-08 17:20:19.000,0.6.26,117.0,whylogs,,,,,2.0,,https://pypi.org/project/whylogs,2022-02-08 17:22:52.000,2.0,7963.0,7965.0,,,,,,,,3.0,49.0,,,,,,,,,,,,,,,,,,,, +591,Objax,google/objax,ml-frameworks,,https://github.com/google/objax,https://github.com/google/objax,Apache-2.0,2020-08-20 06:20:40.000,2022-02-01 00:17:20.000000,2022-02-01 00:02:21,424.0,10.0,59,25.0,140.0,45.0,57.0,675,Objax is a machine learning framework that provides an Object Oriented layer for JAX.,22.0,23,True,2022-02-01 00:17:20.000,1.6.0,9.0,objax,,,,['jax'],20.0,18.0,https://pypi.org/project/objax,2022-01-31 23:28:27.000,2.0,486.0,486.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +592,pdpipe,pdpipe/pdpipe,data-pipelines,,https://github.com/pdpipe/pdpipe,https://github.com/pdpipe/pdpipe,MIT,2017-01-24 20:37:22.000,2022-02-05 09:29:23.000000,2022-01-30 10:53:15,387.0,26.0,32,17.0,40.0,14.0,27.0,651,Easy pipelines for pandas DataFrames.,9.0,23,True,2022-01-30 08:14:18.000,0.1.6,74.0,pdpipe,conda-forge/pdpipe,,,['pandas'],45.0,40.0,https://pypi.org/project/pdpipe,2022-01-30 08:12:29.000,5.0,2889.0,3090.0,https://anaconda.org/conda-forge/pdpipe,2021-12-26 22:22:36.689,3028.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +593,pickleDB,patx/pickledb,data-containers,,https://github.com/patx/pickledb,https://github.com/patx/pickledb,BSD-3-Clause,2011-10-28 00:04:40.000,2022-02-10 09:36:27.000000,2019-11-15 03:38:30,105.0,,107,12.0,30.0,22.0,39.0,635,pickleDB is an open source key-value store using Pythons json module.,12.0,23,False,2019-01-14 18:48:25.000,0.9.2,20.0,pickledb,,,,,916.0,833.0,https://pypi.org/project/pickledb,2019-01-14 18:48:25.000,83.0,16406.0,16406.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +594,PyTorch Sparse,rusty1s/pytorch_sparse,pytorch-utils,,https://github.com/rusty1s/pytorch_sparse,https://github.com/rusty1s/pytorch_sparse,MIT,2018-07-28 18:46:53.000,2022-02-09 03:51:20.000000,2022-02-09 03:51:20,656.0,7.0,77,9.0,40.0,60.0,136.0,564,PyTorch Extension Library of Optimized Autograd Sparse Matrix Operations.,21.0,23,True,2021-09-08 09:32:15.000,0.6.12,24.0,torch-sparse,conda-forge/pytorch_sparse,,,['pytorch'],32.0,,https://pypi.org/project/torch-sparse,2021-09-08 09:27:37.000,32.0,20263.0,24195.0,https://anaconda.org/conda-forge/pytorch_sparse,2021-06-29 21:27:02.635,78642.0,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +595,docarray,jina-ai/docarray,data-containers,,https://github.com/jina-ai/docarray,https://github.com/jina-ai/docarray,Apache-2.0,2021-12-14 15:26:24.000,2022-02-10 14:41:03.000000,2022-02-10 13:32:12,231.0,231.0,30,24.0,84.0,8.0,19.0,515,The data structure for unstructured data.,14.0,23,True,2022-02-10 13:32:46.000,0.6.1,126.0,docarray,conda-forge/docarray,,,,7.0,7.0,https://pypi.org/project/docarray,2022-02-10 13:32:10.000,,51768.0,51809.0,https://anaconda.org/conda-forge/docarray,2022-01-10 17:43:29.016,41.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, +596,python-ternary,marcharper/python-ternary,data-viz,,https://github.com/marcharper/python-ternary,https://github.com/marcharper/python-ternary,MIT,2012-08-07 23:48:55.000,2021-12-17 13:03:20.000000,2021-10-21 03:04:53,393.0,,131,15.0,69.0,24.0,91.0,513,Ternary plotting library for python with matplotlib.,27.0,23,True,2021-02-17 18:38:15.000,1.0.8,11.0,python-ternary,conda-forge/python-ternary,,,,105.0,84.0,https://pypi.org/project/python-ternary,2021-02-17 18:38:15.000,21.0,16153.0,17021.0,https://anaconda.org/conda-forge/python-ternary,2021-02-17 22:38:55.625,60808.0,,,,,3.0,17.0,,,,,,,,,,,,,,,,,,,, +597,pivottablejs,nicolaskruchten/jupyter_pivottablejs,data-viz,,https://github.com/nicolaskruchten/jupyter_pivottablejs,https://github.com/nicolaskruchten/jupyter_pivottablejs,MIT,2015-09-09 13:39:18.000,2022-01-20 12:21:54.512000,2018-12-04 14:43:25,32.0,,61,21.0,7.0,17.0,40.0,456,"Dragndrop Pivot Tables and Charts for Jupyter/IPython Notebook, care of PivotTable.js.",3.0,23,False,2018-01-15 18:14:37.000,0.9.0,10.0,pivottablejs,anaconda/pivottablejs,,,['jupyter'],236.0,214.0,https://pypi.org/project/pivottablejs,2018-01-15 18:14:37.000,22.0,13384.0,13398.0,https://anaconda.org/anaconda/pivottablejs,2022-01-20 12:21:54.512,1059.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +598,pySBD,nipunsadvilkar/pySBD,nlp,,https://github.com/nipunsadvilkar/pySBD,https://github.com/nipunsadvilkar/pySBD,MIT,2017-06-11 06:15:20.000,2022-01-21 12:46:21.000000,2021-02-11 16:40:18,279.0,,48,11.0,43.0,12.0,48.0,413,pySBD (Python Sentence Boundary Disambiguation) is a rule-based sentence boundary detection that works out-of-the-box.,6.0,23,True,2021-02-11 16:42:37.000,0.3.4,15.0,pysbd,conda-forge/pysbd,,,,283.0,280.0,https://pypi.org/project/pysbd,2021-02-11 16:36:33.000,3.0,44834.0,44886.0,https://anaconda.org/conda-forge/pysbd,2021-10-11 20:47:46.408,210.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +599,joypy,leotac/joypy,data-viz,,https://github.com/leotac/joypy,https://github.com/leotac/joypy,MIT,2017-07-30 17:18:50.000,2021-12-21 20:58:11.000000,2021-12-19 09:41:43,133.0,22.0,44,11.0,19.0,11.0,37.0,398,Joyplots in Python with matplotlib & pandas.,6.0,23,True,2021-12-19 09:42:50.000,0.2.6,17.0,joypy,conda-forge/joypy,,,,128.0,123.0,https://pypi.org/project/joypy,2021-12-19 09:42:50.000,5.0,35541.0,35892.0,https://anaconda.org/conda-forge/joypy,2020-12-28 14:07:53.760,12291.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +600,Hyperactive,SimonBlanke/Hyperactive,hyperopt,,https://github.com/SimonBlanke/Hyperactive,https://github.com/SimonBlanke/Hyperactive,MIT,2018-11-01 08:53:30.000,2022-01-18 12:40:05.000000,2022-01-18 12:40:04,2059.0,64.0,32,10.0,6.0,7.0,36.0,363,An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.,4.0,23,True,2021-12-05 15:03:12.000,4.0.2,63.0,hyperactive,,,,,14.0,11.0,https://pypi.org/project/hyperactive,2021-12-05 15:03:12.000,3.0,531.0,533.0,,,,,,,,3.0,98.0,,,,,,,,,,,,,,,,,,,, +601,MONAILabel,Project-MONAI/MONAILabel,others,,https://github.com/Project-MONAI/MONAILabel,https://github.com/Project-MONAI/MONAILabel,Apache-2.0,2021-03-26 15:25:10.000,2022-02-10 07:54:33.000000,2022-02-09 22:31:27,521.0,71.0,42,14.0,378.0,46.0,172.0,201,MONAI Label is an intelligent open source image labeling and learning tool.,22.0,23,False,2021-12-29 20:15:14.000,0.3.1,31.0,monailabel-weekly,,,,,,,https://pypi.org/project/monailabel-weekly,2022-02-06 02:30:53.000,,641.0,1534.0,,,,,,,,3.0,6256.0,,,,,,,,,,,,,,,,,,,True, +602,whoosh,mchaput/whoosh,nlp,,https://github.com/mchaput/whoosh,https://github.com/mchaput/whoosh,BSD-1-Clause,2015-04-17 19:34:47.000,2022-01-15 18:08:37.000000,2022-01-15 18:08:37,1718.0,1.0,37,8.0,7.0,12.0,2.0,194,Pure-Python full-text search library.,42.0,23,False,2016-04-04 01:19:40.000,2.7.4,141.0,whoosh,conda-forge/whoosh,,,,3658.0,,https://pypi.org/project/whoosh,2016-04-04 01:19:40.000,3658.0,184101.0,185544.0,https://anaconda.org/conda-forge/whoosh,2021-11-05 17:24:41.315,92358.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, +603,Dejavu,worldveil/dejavu,audio,,https://github.com/worldveil/dejavu,https://github.com/worldveil/dejavu,MIT,2013-11-19 02:50:35.000,2020-10-29 17:40:17.000000,2020-06-03 05:58:03,146.0,,1250,264.0,64.0,84.0,129.0,5646,Audio fingerprinting and recognition in Python.,23.0,22,False,2015-04-19 21:20:16.000,0.1.3,4.0,PyDejavu,,,,,23.0,20.0,https://pypi.org/project/PyDejavu,2015-04-19 21:20:16.000,3.0,97.0,97.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +604,TTS,mozilla/TTS,audio,,https://github.com/mozilla/TTS,https://github.com/mozilla/TTS,MPL-2.0,2018-01-23 14:22:06.000,2022-01-06 13:56:03.000000,2021-02-12 10:36:31,2184.0,,866,157.0,208.0,16.0,510.0,5617,Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts).,56.0,22,True,2021-01-29 00:03:56.000,0.0.9,1.0,,,,,,,,,,,,135.0,,,,,,,,3.0,1756.0,,,,,,,,,,,,,,,,,,,, +605,ReAgent,facebookresearch/ReAgent,reinforcement-learning,,https://github.com/facebookresearch/ReAgent,https://github.com/facebookresearch/ReAgent,BSD-3-Clause,2017-07-27 17:53:21.000,2022-02-10 06:43:51.000000,2022-02-10 06:43:35,1404.0,48.0,430,144.0,503.0,41.0,75.0,3112,"A platform for Reasoning systems (Reinforcement Learning, Contextual Bandits, etc.).",123.0,22,True,2020-01-27 22:06:00.000,0.0.0,2.0,reagent,,,,['pytorch'],,,https://pypi.org/project/reagent,2020-05-27 20:58:01.000,,17.0,17.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +606,TRFL,deepmind/trfl,reinforcement-learning,,https://github.com/deepmind/trfl,https://github.com/deepmind/trfl,Apache-2.0,2018-08-08 14:44:11.000,2021-08-16 12:19:16.000000,2021-08-16 11:45:18,123.0,,372,212.0,8.0,6.0,16.0,3109,TensorFlow Reinforcement Learning.,13.0,22,True,2021-08-16 12:19:16.000,1.2.0,5.0,trfl,,,,['tensorflow'],74.0,71.0,https://pypi.org/project/trfl,2021-08-16 12:19:16.000,3.0,4239.0,4239.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +607,gpt-2-simple,minimaxir/gpt-2-simple,nlp,,https://github.com/minimaxir/gpt-2-simple,https://github.com/minimaxir/gpt-2-simple,MIT,2019-04-13 20:00:52.000,2022-01-18 06:06:38.000000,2021-10-18 01:45:21,143.0,,591,75.0,50.0,151.0,93.0,2865,Python package to easily retrain OpenAIs GPT-2 text-generating model on new texts.,18.0,22,True,2021-10-18 02:38:39.000,0.8.1,18.0,gpt-2-simple,,,,['tensorflow'],5.0,,https://pypi.org/project/gpt-2-simple,2021-10-18 01:47:20.000,5.0,5463.0,5471.0,,,,,,,,3.0,289.0,,,,,,,,,,,,,,,,,,,, +608,NLP Architect,IntelLabs/nlp-architect,nlp,,https://github.com/IntelLabs/nlp-architect,https://github.com/IntelLabs/nlp-architect,Apache-2.0,2018-05-17 21:00:13.000,2022-02-10 02:53:48.000000,2021-09-12 08:29:06,954.0,,437,168.0,108.0,21.0,112.0,2799,A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language..,37.0,22,True,2020-11-17 12:32:37.000,0.5.5.1,13.0,nlp-architect,,,,,8.0,8.0,https://pypi.org/project/nlp-architect,2020-04-12 11:34:38.000,,290.0,290.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +609,dpark,douban/dpark,data-pipelines,,https://github.com/douban/dpark,https://github.com/douban/dpark,BSD-3-Clause,2012-04-11 08:35:06.000,2020-12-25 10:36:06.000000,2020-12-25 10:36:05,1467.0,,554,267.0,30.0,,60.0,2672,"Python clone of Spark, a MapReduce alike framework in Python.",35.0,22,False,2018-07-27 04:11:36.000,0.5.0,19.0,dpark,,,,['spark'],6.0,5.0,https://pypi.org/project/dpark,2018-07-27 04:11:36.000,1.0,64.0,64.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +610,StreamAlert,airbnb/streamalert,others,,https://github.com/airbnb/streamalert,https://github.com/airbnb/streamalert,Apache-2.0,2017-01-22 01:10:56.000,2021-12-06 17:56:08.000000,2021-11-04 18:52:02,1900.0,,322,105.0,985.0,84.0,257.0,2658,"StreamAlert is a serverless, realtime data analysis framework which empowers you to ingest, analyze, and alert on data..",33.0,22,True,2021-11-04 19:07:51.000,3.5.0,28.0,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +611,cleanlab,cleanlab/cleanlab,others,,https://github.com/cleanlab/cleanlab,https://github.com/cleanlab/cleanlab,AGPL-3.0,2018-05-11 01:55:21.000,2022-02-02 12:35:36.000000,2022-02-02 12:25:29,704.0,13.0,257,59.0,18.0,40.0,47.0,2649,"The standard package for machine learning with label errors, finding mislabeled data, and uncertainty quantification...",7.0,22,False,2021-04-18 19:52:49.000,1.0,15.0,cleanlab,conda-forge/cleanlab,,,,30.0,28.0,https://pypi.org/project/cleanlab,2020-02-17 07:33:06.000,2.0,5326.0,5460.0,https://anaconda.org/conda-forge/cleanlab,2021-11-17 13:19:56.123,2961.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +612,Texthero,jbesomi/texthero,nlp,,https://github.com/jbesomi/texthero,https://github.com/jbesomi/texthero,MIT,2020-04-06 15:16:05.000,2021-07-19 13:56:08.000000,2021-07-19 13:56:08,269.0,,210,44.0,105.0,76.0,59.0,2431,"Text preprocessing, representation and visualization from zero to hero.",18.0,22,True,2021-07-01 17:11:02.000,1.1.0,10.0,texthero,,,,,4.0,,https://pypi.org/project/texthero,2021-07-01 17:11:02.000,4.0,23752.0,23755.0,,,,,,,,3.0,87.0,,,,,,,,,,,,,,,,,,,, +613,Luminoth,tryolabs/luminoth,image,,https://github.com/tryolabs/luminoth,https://github.com/tryolabs/luminoth,BSD-3-Clause,2017-02-16 15:07:46.000,2022-02-10 01:50:51.000000,2020-01-07 20:53:25,838.0,,413,132.0,131.0,60.0,128.0,2382,Deep Learning toolkit for Computer Vision.,15.0,22,False,2018-11-09 21:35:17.000,0.2.3,10.0,luminoth,,,,['tensorflow'],41.0,39.0,https://pypi.org/project/luminoth,2018-11-09 21:35:17.000,2.0,765.0,997.0,,,,,,,,3.0,12090.0,,,,,,,,,,,,,,,,,,,, +614,Texar,asyml/texar,nlp,,https://github.com/asyml/texar,https://github.com/asyml/texar,Apache-2.0,2017-07-22 19:02:05.000,2021-08-26 09:49:50.000000,2020-07-29 00:38:30,1719.0,,359,78.0,144.0,33.0,126.0,2243,"Toolkit for Machine Learning, Natural Language Processing, and Text Generation, in TensorFlow. This is part of the..",43.0,22,False,2019-11-19 04:11:18.000,0.2.4,6.0,texar,,,,['tensorflow'],19.0,17.0,https://pypi.org/project/texar,2019-11-19 04:11:18.000,2.0,125.0,125.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +615,Coach,IntelLabs/coach,reinforcement-learning,,https://github.com/IntelLabs/coach,https://github.com/IntelLabs/coach,Apache-2.0,2017-10-01 19:27:43.000,2021-12-27 09:52:12.000000,2021-06-28 07:40:53,521.0,,414,131.0,225.0,87.0,183.0,2106,Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning..,35.0,22,True,2019-10-10 14:17:10.000,1.0.1,13.0,rl_coach,,,,,2.0,,https://pypi.org/project/rl_coach,2019-10-10 14:17:10.000,2.0,150.0,150.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +616,Sweetviz,fbdesignpro/sweetviz,data-viz,,https://github.com/fbdesignpro/sweetviz,https://github.com/fbdesignpro/sweetviz,MIT,2020-05-09 15:25:47.000,2021-10-01 14:11:39.000000,2021-07-08 14:31:20,102.0,,191,48.0,10.0,27.0,70.0,1906,"Visualize and compare datasets, target values and associations, with one line of code.",6.0,22,True,2021-07-08 14:32:09.000,2.1.3,31.0,sweetviz,conda-forge/sweetviz,,,,5.0,,https://pypi.org/project/sweetviz,2021-07-08 14:32:09.000,5.0,65802.0,66522.0,https://anaconda.org/conda-forge/sweetviz,2021-07-09 00:00:54.236,8644.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +617,fast-bert,utterworks/fast-bert,nlp,,https://github.com/utterworks/fast-bert,https://github.com/utterworks/fast-bert,Apache-2.0,2019-04-18 22:01:20.000,2022-01-11 01:58:54.000000,2022-01-10 14:57:25,302.0,2.0,334,42.0,62.0,152.0,94.0,1701,Super easy library for BERT based NLP models.,35.0,22,True,2022-01-10 14:21:11.000,1.9.15,49.0,fast-bert,,,,,2.0,,https://pypi.org/project/fast-bert,2022-01-10 14:21:11.000,2.0,1487.0,1487.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +618,BlazingSQL,BlazingDB/blazingsql,gpu-utilities,,https://github.com/BlazingDB/blazingsql,https://github.com/BlazingDB/blazingsql,Apache-2.0,2018-09-24 18:25:45.000,2022-01-21 23:34:24.000000,2021-09-30 21:51:09,8208.0,,164,50.0,893.0,129.0,586.0,1699,"BlazingSQL is a lightweight, GPU accelerated, SQL engine for Python. Built on RAPIDS cuDF.",47.0,22,True,2021-08-16 15:40:43.000,21.08.00,19.0,,blazingsql/blazingsql-protocol,,,,,,,,,,32.0,https://anaconda.org/blazingsql/blazingsql-protocol,2019-11-11 19:54:17.621,940.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +619,AmpliGraph,Accenture/AmpliGraph,graph,,https://github.com/Accenture/AmpliGraph,https://github.com/Accenture/AmpliGraph,Apache-2.0,2019-01-09 14:52:05.000,2021-09-24 18:27:27.000000,2021-05-25 16:49:48,947.0,,194,59.0,58.0,20.0,181.0,1685,Python library for Representation Learning on Knowledge Graphs https://docs.ampligraph.org.,19.0,22,True,2021-05-25 16:57:42.000,1.4.0,12.0,ampligraph,,,,['tensorflow'],17.0,17.0,https://pypi.org/project/ampligraph,2021-05-25 16:47:29.000,,761.0,761.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +620,lore,instacart/lore,ml-experiments,,https://github.com/instacart/lore,https://github.com/instacart/lore,MIT,2017-10-19 21:51:45.000,2022-02-02 23:30:10.000000,2022-02-02 23:21:53,271.0,1.0,128,102.0,146.0,26.0,18.0,1537,Lore makes machine learning approachable for Software Engineers and maintainable for Machine Learning Researchers.,23.0,22,True,2022-02-02 23:30:10.000,0.8.5,232.0,lore,,,,,18.0,17.0,https://pypi.org/project/lore,2022-02-02 23:30:10.000,1.0,2513.0,2513.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +621,FARM,deepset-ai/FARM,nlp,,https://github.com/deepset-ai/FARM,https://github.com/deepset-ai/FARM,Apache-2.0,2019-07-17 14:51:12.000,2021-11-23 16:56:58.000000,2021-11-23 16:56:58,592.0,1.0,210,52.0,441.0,38.0,388.0,1466,Fast & easy transfer learning for NLP. Harvesting language models for the industry. Focus on Question Answering.,37.0,22,True,2021-06-10 09:45:12.000,0.8.0,24.0,farm,conda-forge/farm,,,['pytorch'],2.0,,https://pypi.org/project/farm,2021-06-10 09:41:53.000,2.0,8091.0,8180.0,https://anaconda.org/conda-forge/farm,2021-06-14 12:34:06.874,890.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +622,FinTA,peerchemist/finta,financial-data,,https://github.com/peerchemist/finta,https://github.com/peerchemist/finta,LGPL-3.0,2016-09-01 21:02:46.000,2021-10-19 18:06:53.000000,2021-10-19 18:06:53,392.0,,468,77.0,46.0,18.0,63.0,1450,Common financial technical indicators implemented in Pandas.,27.0,22,False,2021-04-03 08:51:49.000,1.3,19.0,finta,,,,,164.0,158.0,https://pypi.org/project/finta,2020-10-21 11:39:44.000,6.0,7156.0,7156.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +623,anaGo,Hironsan/anago,nlp,,https://github.com/Hironsan/anago,https://github.com/Hironsan/anago,MIT,2017-06-26 21:28:36.000,2022-02-09 23:29:07.000000,2021-04-01 12:34:50,298.0,,362,65.0,38.0,37.0,72.0,1428,"Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition, Part-of-Speech Tagging and so on.",11.0,22,True,2018-07-17 01:59:21.000,1.0.8,14.0,anago,,,,['tensorflow'],32.0,27.0,https://pypi.org/project/anago,2018-07-17 01:59:21.000,5.0,508.0,508.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +624,Classy Vision,facebookresearch/ClassyVision,image,,https://github.com/facebookresearch/ClassyVision,https://github.com/facebookresearch/ClassyVision,MIT,2019-09-13 22:54:44.000,2022-01-20 12:36:03.000000,2021-12-28 18:38:43,397.0,5.0,240,50.0,702.0,53.0,61.0,1406,An end-to-end PyTorch framework for image and video classification.,67.0,22,True,2021-07-19 20:08:51.000,0.6.0,17.0,classy_vision,conda-forge/classy_vision,,,['pytorch'],2.0,,https://pypi.org/project/classy_vision,2021-07-09 22:58:06.000,2.0,824.0,1271.0,https://anaconda.org/conda-forge/classy_vision,2020-12-11 20:08:25.437,11186.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +625,ecco,jalammar/ecco,interpretability,,https://github.com/jalammar/ecco,https://github.com/jalammar/ecco,BSD-3-Clause,2020-11-07 10:06:34.000,2022-01-18 08:05:49.000000,2022-01-18 08:05:49,304.0,59.0,82,19.0,24.0,13.0,21.0,1316,"Explain, analyze, and visualize NLP language models. Ecco creates interactive visualizations directly in Jupyter..",10.0,22,True,2022-01-09 21:17:53.000,0.1.2,18.0,ecco,conda-forge/ecco,,,['pytorch'],4.0,3.0,https://pypi.org/project/ecco,2022-01-09 21:14:50.000,1.0,438.0,504.0,https://anaconda.org/conda-forge/ecco,2022-01-10 22:03:30.223,133.0,,,,,3.0,12.0,,,,,,,,,,,,,,,,,,,, +626,DLTK,DLTK/DLTK,medical-data,,https://github.com/DLTK/DLTK,https://github.com/DLTK/DLTK,Apache-2.0,2017-05-02 15:40:36.000,2022-02-09 23:26:32.000000,2019-01-21 14:01:28,379.0,,390,101.0,29.0,11.0,24.0,1293,Deep Learning Toolkit for Medical Image Analysis.,9.0,22,False,2018-02-26 17:43:57.000,0.2.1,5.0,dltk,,,,['tensorflow'],23.0,23.0,https://pypi.org/project/dltk,2018-02-26 17:43:57.000,,180.0,180.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +627,Pytorch Toolbelt,BloodAxe/pytorch-toolbelt,pytorch-utils,,https://github.com/BloodAxe/pytorch-toolbelt,https://github.com/BloodAxe/pytorch-toolbelt,MIT,2019-03-15 16:02:49.000,2022-02-10 09:38:03.000000,2022-02-10 09:37:58,822.0,34.0,88,25.0,45.0,5.0,18.0,1195,PyTorch extensions for fast R&D prototyping and Kaggle farming.,7.0,22,True,2021-08-12 07:49:51.000,0.4.4,22.0,pytorch_toolbelt,,,,['pytorch'],6.0,,https://pypi.org/project/pytorch_toolbelt,2021-08-12 07:49:51.000,6.0,15180.0,15180.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +628,tensorrec,jfkirk/tensorrec,recommender-systems,,https://github.com/jfkirk/tensorrec,https://github.com/jfkirk/tensorrec,Apache-2.0,2017-02-28 18:51:11.000,2022-01-13 00:49:18.000000,2020-02-04 21:10:25,334.0,,218,65.0,45.0,35.0,90.0,1173,A TensorFlow recommendation algorithm and framework in Python.,9.0,22,False,2019-04-02 00:53:47.000,0.26.2,30.0,tensorrec,,,,['tensorflow'],29.0,26.0,https://pypi.org/project/tensorrec,2019-04-02 00:53:47.000,3.0,350.0,350.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +629,DALEX,ModelOriented/DALEX,interpretability,,https://github.com/ModelOriented/DALEX,https://github.com/ModelOriented/DALEX,GPL-3.0,2018-02-18 03:24:12.000,2022-01-25 11:13:18.000000,2022-01-25 10:58:33,600.0,6.0,123,43.0,146.0,14.0,319.0,996,moDel Agnostic Language for Exploration and eXplanation.,20.0,22,False,2021-11-08 12:22:11.000,1.4.1,23.0,dalex,conda-forge/dalex,,,,33.0,30.0,https://pypi.org/project/dalex,2021-11-08 12:22:11.000,3.0,4397.0,4611.0,https://anaconda.org/conda-forge/dalex,2021-07-17 15:59:19.192,2792.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +630,fastFM,ibayer/fastFM,recommender-systems,,https://github.com/ibayer/fastFM,https://github.com/ibayer/fastFM,BSD-3-Clause,2014-10-27 12:25:51.000,2021-12-06 14:42:35.000000,2021-03-24 12:22:31,297.0,,190,30.0,60.0,46.0,60.0,964,fastFM: A Library for Factorization Machines.,20.0,22,True,2017-11-23 06:59:56.000,0.2.11,10.0,fastfm,,,,,101.0,93.0,https://pypi.org/project/fastfm,2017-11-23 06:59:56.000,8.0,607.0,612.0,,,,,,,,3.0,427.0,,,,,,,,,,,,,,,,,,,, +631,tf-explain,sicara/tf-explain,interpretability,,https://github.com/sicara/tf-explain,https://github.com/sicara/tf-explain,MIT,2019-07-15 08:26:24.000,2021-11-30 09:54:42.000000,2021-11-30 09:54:40,206.0,3.0,91,51.0,93.0,39.0,51.0,900,Interpretability Methods for tf.keras models with Tensorflow 2.x.,16.0,22,True,2021-11-18 20:57:29.000,0.3.1,8.0,tf-explain,,,,['tensorflow'],104.0,98.0,https://pypi.org/project/tf-explain,2021-11-18 20:57:29.000,6.0,2257.0,2257.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +632,calamari,Calamari-OCR/calamari,ocr,,https://github.com/Calamari-OCR/calamari,https://github.com/Calamari-OCR/calamari,Apache-2.0,2018-03-20 15:22:29.000,2022-02-09 14:34:55.000000,2022-02-09 14:34:55,428.0,11.0,188,56.0,71.0,39.0,193.0,896,Line based ATR Engine based on OCRopy.,19.0,22,True,2021-10-02 07:50:30.000,2.1.4,30.0,calamari_ocr,,,,,2.0,,https://pypi.org/project/calamari_ocr,2018-11-13 11:24:45.000,2.0,651.0,651.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +633,torch-scatter,rusty1s/pytorch_scatter,pytorch-utils,,https://github.com/rusty1s/pytorch_scatter,https://github.com/rusty1s/pytorch_scatter,MIT,2017-12-16 16:34:23.000,2022-02-04 13:28:05.000000,2022-02-03 10:20:16,971.0,2.0,97,12.0,31.0,22.0,217.0,887,PyTorch Extension Library of Optimized Scatter Operations.,19.0,22,True,2021-10-22 11:01:13.000,2.0.9,29.0,torch-scatter,conda-forge/pytorch_scatter,,,['pytorch'],40.0,,https://pypi.org/project/torch-scatter,2021-10-22 11:01:13.000,40.0,31596.0,34956.0,https://anaconda.org/conda-forge/pytorch_scatter,2021-08-18 21:47:12.421,67216.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +634,nude.py,hhatto/nude.py,image,,https://github.com/hhatto/nude.py,https://github.com/hhatto/nude.py,MIT,2013-06-09 06:55:55.000,2020-11-23 13:49:32.000000,2020-11-23 13:49:02,79.0,,133,34.0,16.0,7.0,3.0,834,Nudity detection with Python.,12.0,22,False,2020-11-23 13:49:17.000,0.5.1,10.0,nudepy,,,,,1788.0,1778.0,https://pypi.org/project/nudepy,2020-11-23 13:49:17.000,10.0,10351.0,10351.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +635,YouTokenToMe,vkcom/youtokentome,nlp,,https://github.com/VKCOM/YouTokenToMe,https://github.com/VKCOM/YouTokenToMe,MIT,2019-06-06 11:38:28.000,2021-11-09 18:21:25.187000,2021-01-28 19:04:09,79.0,,57,23.0,42.0,28.0,23.0,787,Unsupervised text tokenizer focused on computational efficiency.,6.0,22,False,2020-02-13 09:57:47.000,1.0.6,14.0,youtokentome,conda-forge/youtokentome,,,,227.0,212.0,https://pypi.org/project/youtokentome,2020-02-12 18:24:46.000,15.0,31945.0,33029.0,https://anaconda.org/conda-forge/youtokentome,2021-11-09 18:21:25.187,5422.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +636,DiCE,interpretml/DiCE,interpretability,,https://github.com/interpretml/DiCE,https://github.com/interpretml/DiCE,MIT,2019-05-02 09:51:02.000,2022-02-08 15:43:13.000000,2022-02-08 15:27:42,499.0,38.0,105,16.0,168.0,46.0,54.0,770,Generate Diverse Counterfactual Explanations for any machine learning model.,12.0,22,True,2021-09-27 06:59:57.000,0.7.2,8.0,dice-ml,,,,"['tensorflow', 'pytorch']",3.0,,https://pypi.org/project/dice-ml,2021-09-27 06:59:57.000,3.0,34195.0,34195.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +637,TreeInterpreter,andosa/treeinterpreter,interpretability,,https://github.com/andosa/treeinterpreter,https://github.com/andosa/treeinterpreter,BSD-3-Clause,2015-08-02 20:26:21.000,2021-02-28 18:33:06.000000,2021-02-28 18:33:06,37.0,,132,26.0,17.0,24.0,4.0,696,Package for interpreting scikit-learns decision tree and random forest predictions.,11.0,22,True,2021-01-10 20:12:39.000,0.2.3,5.0,treeinterpreter,conda-forge/treeinterpreter,,,['sklearn'],214.0,204.0,https://pypi.org/project/treeinterpreter,2021-01-10 20:12:39.000,10.0,211060.0,211120.0,https://anaconda.org/conda-forge/treeinterpreter,2020-10-03 05:29:07.840,968.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +638,PDPbox,SauceCat/PDPbox,data-viz,,https://github.com/SauceCat/PDPbox,https://github.com/SauceCat/PDPbox,MIT,2017-06-26 08:01:54.000,2021-06-24 15:32:01.000000,2021-03-14 16:01:01,227.0,,106,17.0,23.0,20.0,38.0,651,python partial dependence plot toolbox.,7.0,22,True,2021-03-14 16:21:17.000,0.2.1,3.0,pdpbox,conda-forge/pdpbox,,,,498.0,473.0,https://pypi.org/project/pdpbox,2021-03-14 16:21:17.000,25.0,58434.0,58778.0,https://anaconda.org/conda-forge/pdpbox,2021-03-14 19:37:51.465,10666.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +639,What-If Tool,PAIR-code/what-if-tool,interpretability,,https://github.com/PAIR-code/what-if-tool,https://github.com/PAIR-code/what-if-tool,Apache-2.0,2018-09-07 20:26:10.000,2022-01-14 02:13:30.000000,2022-01-05 20:19:46,328.0,4.0,124,25.0,97.0,57.0,47.0,636,Source code/webpage/demos for the What-If Tool.,20.0,22,True,2021-10-12 17:42:50.869,1.8.1,40.0,witwidget,conda-forge/tensorboard-plugin-wit,,,,3.0,,https://pypi.org/project/witwidget,2021-10-12 17:42:30.000,3.0,7499.0,53591.0,https://anaconda.org/conda-forge/tensorboard-plugin-wit,2022-01-06 08:51:02.032,846936.0,,,,,3.0,,,wit-widget,https://www.npmjs.com/package/wit-widget,2021-10-12 17:42:50.869,,3746.0,,,,,,,,,,,,,, +640,iterative-stratification,trent-b/iterative-stratification,sklearn-utils,,https://github.com/trent-b/iterative-stratification,https://github.com/trent-b/iterative-stratification,BSD-3-Clause,2018-02-04 00:32:10.000,2021-11-11 01:20:14.000000,2021-11-11 01:20:14,55.0,,57,7.0,4.0,4.0,15.0,628,scikit-learn cross validators for iterative stratification of multilabel data.,6.0,22,True,2021-10-03 18:49:49.000,0.1.7,6.0,iterative-stratification,,,,['sklearn'],193.0,185.0,https://pypi.org/project/iterative-stratification,2021-10-03 18:49:49.000,8.0,154650.0,154650.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +641,HpBandSter,automl/HpBandSter,hyperopt,,https://github.com/automl/HpBandSter,https://github.com/automl/HpBandSter,BSD-3-Clause,2017-12-17 20:28:20.000,2021-01-31 10:05:37.000000,2019-03-26 09:26:28,187.0,,107,24.0,22.0,57.0,35.0,519,a distributed Hyperband implementation on Steroids.,11.0,22,False,2019-07-30 12:47:43.000,1.0,8.0,hpbandster,conda-forge/hpbandster,,,,204.0,194.0,https://pypi.org/project/hpbandster,2018-11-06 12:56:55.000,10.0,14186.0,14251.0,https://anaconda.org/conda-forge/hpbandster,2020-12-11 15:57:39.186,910.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +642,Neuraxle,Neuraxio/Neuraxle,hyperopt,,https://github.com/Neuraxio/Neuraxle,https://github.com/Neuraxio/Neuraxle,Apache-2.0,2019-03-26 21:01:54.000,2022-02-08 22:42:21.000000,2021-11-01 21:10:39,1593.0,,53,19.0,210.0,142.0,204.0,496,A Sklearn-like Framework for Hyperparameter Tuning and AutoML in Deep Learning projects. Finally have the right..,7.0,22,True,2021-10-17 21:12:29.000,0.6.1,22.0,neuraxle,,,,,27.0,26.0,https://pypi.org/project/neuraxle,2021-10-17 21:07:02.000,1.0,316.0,316.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +643,random-forest-importances,parrt/random-forest-importances,interpretability,,https://github.com/parrt/random-forest-importances,https://github.com/parrt/random-forest-importances,MIT,2018-03-22 19:20:13.000,2021-01-30 21:50:08.000000,2021-01-30 21:50:02,249.0,,110,21.0,18.0,6.0,28.0,492,Code to compute permutation and drop-column importances in Python scikit-learn models.,14.0,22,False,2021-01-28 23:23:17.000,1.3.7,22.0,rfpimp,,,,['sklearn'],94.0,89.0,https://pypi.org/project/rfpimp,2021-01-28 23:19:33.000,5.0,12986.0,12986.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +644,imodels,csinva/imodels,interpretability,,https://github.com/csinva/imodels,https://github.com/csinva/imodels,MIT,2019-07-04 15:38:48.000,2022-02-10 03:32:22.000000,2022-02-10 03:32:20,544.0,110.0,49,16.0,66.0,6.0,20.0,490,"Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compatible).",8.0,22,True,2022-01-29 03:59:40.000,1.2.3,19.0,imodels,,,,,12.0,12.0,https://pypi.org/project/imodels,2022-01-29 03:46:50.000,,1253.0,1253.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +645,optunity,claesenm/optunity,hyperopt,,https://github.com/claesenm/optunity,https://github.com/claesenm/optunity,BSD-3-Clause,2014-05-28 17:29:11.000,2020-05-11 14:32:39.000000,2020-05-11 14:32:38,782.0,,73,24.0,9.0,48.0,48.0,380,optimization routines for hyperparameter tuning.,9.0,22,False,2015-09-30 05:02:00.000,1.1.1,6.0,optunity,,,,,86.0,72.0,https://pypi.org/project/optunity,2015-09-30 05:02:00.000,14.0,11912.0,11912.0,,,,,,,,3.0,67.0,,,,,,,,,,,,,,,,,,,, +646,Studio.ml,studioml/studio,ml-experiments,,https://github.com/studioml/studio,https://github.com/studioml/studio,Apache-2.0,2017-05-15 01:49:28.000,2021-09-14 22:55:51.000000,2021-09-14 22:26:21,2409.0,,52,25.0,229.0,57.0,195.0,374,Studio: Simplify and expedite model building process.,21.0,22,True,2021-09-14 22:55:51.000,0.0.49,208.0,studioml,,,,,5.0,5.0,https://pypi.org/project/studioml,2021-09-14 22:55:51.000,,709.0,709.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +647,lazypredict,shankarpandala/lazypredict,hyperopt,,https://github.com/shankarpandala/lazypredict,https://github.com/shankarpandala/lazypredict,MIT,2019-11-16 09:56:35.000,2022-01-29 18:05:02.000000,2022-01-29 18:05:02,217.0,2.0,44,7.0,303.0,29.0,33.0,289,Lazy Predict help build a lot of basic models without much code and helps understand which models works better without..,17.0,22,False,2021-02-17 15:38:45.000,0.2.9,11.0,lazypredict,conda-forge/lazypredict,,,['sklearn'],238.0,238.0,https://pypi.org/project/lazypredict,2021-02-17 15:38:45.000,,8385.0,8428.0,https://anaconda.org/conda-forge/lazypredict,2021-08-24 21:49:02.096,260.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +648,happy-transformer,EricFillion/happy-transformer,nlp,,https://github.com/EricFillion/happy-transformer,https://github.com/EricFillion/happy-transformer,Apache-2.0,2019-10-06 22:02:12.000,2022-02-06 06:58:53.000000,2022-02-06 06:56:50,963.0,28.0,29,5.0,189.0,11.0,82.0,256,A package built on top of Hugging Faces transformers library that makes it easy to utilize state-of-the-art NLP models.,13.0,22,False,2022-02-06 06:58:53.000,2.4.1,39.0,happytransformer,,,,['huggingface'],35.0,34.0,https://pypi.org/project/happytransformer,2022-02-06 06:54:52.000,1.0,5628.0,5628.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, +649,pysparkling,svenkreiss/pysparkling,data-pipelines,,https://github.com/svenkreiss/pysparkling,https://github.com/svenkreiss/pysparkling,MIT,2015-05-09 19:23:20.000,2021-10-31 16:40:25.000000,2021-02-22 17:29:11,1527.0,,45,6.0,136.0,7.0,21.0,244,A pure Python implementation of Apache Sparks RDD and DStream interfaces.,10.0,22,False,2021-01-10 21:15:26.000,0.6.1,68.0,pysparkling,conda-forge/pysparkling,,,,102.0,94.0,https://pypi.org/project/pysparkling,2021-01-10 21:15:26.000,8.0,13004.0,13074.0,https://anaconda.org/conda-forge/pysparkling,2021-03-23 19:51:42.850,779.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +650,py3nvml,fbcotter/py3nvml,gpu-utilities,,https://github.com/fbcotter/py3nvml,https://github.com/fbcotter/py3nvml,BSD-3-Clause,2016-11-21 01:07:37.000,2021-11-22 14:30:25.000000,2021-09-06 14:45:26,83.0,,31,11.0,9.0,3.0,10.0,200,Python 3 Bindings for NVML library. Get NVIDIA GPU status inside your program.,8.0,22,False,2021-11-22 14:30:25.000,0.2.7,14.0,py3nvml,conda-forge/py3nvml,,,,417.0,379.0,https://pypi.org/project/py3nvml,2021-11-22 14:30:25.000,38.0,78885.0,79862.0,https://anaconda.org/conda-forge/py3nvml,2021-11-19 20:12:42.962,24441.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +651,stop-words,Alir3z4/python-stop-words,nlp,,https://github.com/Alir3z4/python-stop-words,https://github.com/Alir3z4/python-stop-words,BSD-3-Clause,2014-05-26 06:44:03.000,2021-12-28 13:59:30.000000,2018-07-23 21:04:09,90.0,,25,6.0,18.0,3.0,9.0,135,Get list of common stop words in various languages in Python.,8.0,22,False,2018-07-23 20:58:34.000,2018.7.23,8.0,stop-words,,,,,1581.0,1435.0,https://pypi.org/project/stop-words,2018-07-23 20:55:55.000,146.0,358179.0,358179.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +652,DeepMatcher,anhaidgroup/deepmatcher,nlp,,https://github.com/anhaidgroup/deepmatcher,https://github.com/anhaidgroup/deepmatcher,BSD-3-Clause,2017-12-01 19:01:11.000,2021-06-13 01:13:43.000000,2021-06-13 00:22:13,176.0,,1488,15.0,16.0,54.0,22.0,4026,Python package for performing Entity and Text Matching using Deep Learning.,7.0,21,True,2021-05-27 22:28:29.000,0.1.2,13.0,deepmatcher,,,,,14.0,14.0,https://pypi.org/project/deepmatcher,2021-06-13 01:13:24.000,,530.0,530.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +653,Crypto Signals,CryptoSignal/crypto-signal,financial-data,,https://github.com/CryptoSignal/Crypto-Signal,https://github.com/CryptoSignal/Crypto-Signal,MIT,2017-09-16 23:49:24.000,2021-10-19 20:21:49.000000,2021-06-28 16:44:17,564.0,,993,301.0,193.0,54.0,198.0,3810,"Github.com/CryptoSignal - #1 Quant Trading & Technical Analysis Bot - 3,100+ stars, 900+ forks.",28.0,21,True,,,,,,shadowreaver/crypto-signal,,,,,,,,,2670.0,,,,https://hub.docker.com/r/shadowreaver/crypto-signal,2020-09-03 13:00:35.801133,7.0,141526.0,3.0,,,,,,,,,,,,,,,,,,,,, +654,TensorWatch,microsoft/tensorwatch,ml-experiments,,https://github.com/microsoft/tensorwatch,https://github.com/microsoft/tensorwatch,MIT,2019-05-15 08:29:34.000,2021-04-13 09:44:02.000000,2021-01-15 19:46:05,112.0,,334,104.0,14.0,51.0,15.0,3205,"Debugging, monitoring and visualization for Python Machine Learning and Data Science.",13.0,21,False,2020-03-04 07:26:22.000,0.9.1,14.0,tensorwatch,,,,,72.0,66.0,https://pypi.org/project/tensorwatch,2020-03-04 07:26:22.000,6.0,1977.0,1977.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +655,tf-quant-finance,google/tf-quant-finance,financial-data,,https://github.com/google/tf-quant-finance,https://github.com/google/tf-quant-finance,Apache-2.0,2019-07-24 16:09:50.000,2022-02-09 22:40:52.000000,2022-02-09 22:40:45,843.0,25.0,402,160.0,31.0,19.0,19.0,2984,High-performance TensorFlow library for quantitative finance.,36.0,21,True,,,26.0,tf-quant-finance,,,,['tensorflow'],2.0,,https://pypi.org/project/tf-quant-finance,2022-01-07 21:15:09.000,2.0,1043.0,1043.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +656,DeepWalk,phanein/deepwalk,graph,,https://github.com/phanein/deepwalk,https://github.com/phanein/deepwalk,GPL-3.0,2014-08-23 03:38:20.000,2021-09-16 12:01:08.000000,2020-04-02 01:05:35,46.0,,785,88.0,26.0,37.0,80.0,2391,DeepWalk - Deep Learning for Graphs.,10.0,21,False,2018-04-29 21:05:18.000,1.0.3,4.0,deepwalk,,,,,55.0,48.0,https://pypi.org/project/deepwalk,2018-04-29 21:05:18.000,7.0,2371.0,2371.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +657,reformer-pytorch,lucidrains/reformer-pytorch,pytorch-utils,,https://github.com/lucidrains/reformer-pytorch,https://github.com/lucidrains/reformer-pytorch,MIT,2020-01-09 20:42:37.000,2021-11-06 23:09:00.000000,2021-11-06 23:08:22,245.0,,220,51.0,32.0,13.0,104.0,1675,"Reformer, the efficient Transformer, in Pytorch.",10.0,21,True,2021-11-06 23:09:00.000,1.4.4,139.0,reformer-pytorch,,,,['pytorch'],,,https://pypi.org/project/reformer-pytorch,2021-11-06 23:09:00.000,,5494.0,5494.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +658,hiddenlayer,waleedka/hiddenlayer,ml-experiments,,https://github.com/waleedka/hiddenlayer,https://github.com/waleedka/hiddenlayer,MIT,2018-05-18 22:34:51.000,2021-10-16 05:29:37.000000,2020-04-24 06:58:09,58.0,,222,47.0,11.0,47.0,34.0,1576,"Neural network graphs and training metrics for PyTorch, Tensorflow, and Keras.",6.0,21,False,2018-12-03 04:33:29.000,0.2,3.0,hiddenlayer,,,,"['pytorch', 'tensorflow', 'jupyter']",106.0,97.0,https://pypi.org/project/hiddenlayer,2020-04-24 07:32:11.000,9.0,2613.0,2613.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +659,DELTA,Delta-ML/delta,nlp,,https://github.com/Delta-ML/delta,https://github.com/Delta-ML/delta,Apache-2.0,2019-05-29 08:33:57.000,2022-02-09 23:26:38.000000,2020-12-17 06:57:15,932.0,,292,66.0,189.0,5.0,74.0,1493,DELTA is a deep learning based natural language and speech processing platform.,41.0,21,False,2020-07-16 09:31:45.000,0.3.3,4.0,delta-nlp,,zh794390558/delta,,['tensorflow'],,,https://pypi.org/project/delta-nlp,2020-03-27 04:46:19.000,,8.0,404.0,,,,https://hub.docker.com/r/zh794390558/delta,2021-08-03 14:50:00.516864,,13075.0,3.0,,,,,,,,,,,,,,,,,,,,, +660,greykite,linkedin/greykite,time-series-data,,https://github.com/linkedin/greykite,https://github.com/linkedin/greykite,BSD-2-Clause,2021-04-27 17:05:53.000,2021-12-22 19:04:12.000000,2021-12-15 21:44:21,18.0,3.0,64,35.0,12.0,7.0,51.0,1455,"A flexible, intuitive and fast forecasting library.",7.0,21,True,2021-12-22 19:04:12.000,0.1.1,7.0,greykite,,,,,8.0,8.0,https://pypi.org/project/greykite,2021-12-15 01:42:19.000,,19667.0,19667.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +661,jiant,nyu-mll/jiant,nlp,,https://github.com/nyu-mll/jiant,https://github.com/nyu-mll/jiant,MIT,2018-06-18 18:12:47.000,2022-02-03 22:19:07.000000,2022-02-03 22:19:07,1923.0,2.0,262,45.0,791.0,63.0,485.0,1371,jiant is an nlp toolkit.,56.0,21,True,2021-05-10 18:56:39.000,2.2.0,19.0,jiant,,,,,2.0,2.0,https://pypi.org/project/jiant,2021-05-10 18:56:39.000,,109.0,109.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +662,ThunderSVM,Xtra-Computing/thundersvm,ml-frameworks,,https://github.com/Xtra-Computing/thundersvm,https://github.com/Xtra-Computing/thundersvm,Apache-2.0,2014-12-11 04:24:04.000,2022-01-07 08:19:34.000000,2021-02-10 05:12:44,902.0,,185,52.0,50.0,59.0,145.0,1370,ThunderSVM: A Fast SVM Library on GPUs and CPUs.,33.0,21,True,2020-03-13 12:36:30.000,0.3.12,9.0,thundersvm,,,,,,,https://pypi.org/project/thundersvm,2020-03-13 12:36:30.000,,830.0,866.0,,,,,,,,3.0,2323.0,,,,,,,,,,,,,,,,,,,, +663,OpenPrompt,thunlp/OpenPrompt,nlp,,https://github.com/thunlp/OpenPrompt,https://github.com/thunlp/OpenPrompt,Apache-2.0,2021-09-30 09:38:45.000,2022-01-24 08:46:14.000000,2022-01-24 08:43:23,191.0,57.0,111,19.0,24.0,19.0,72.0,1132,An Open-Source Framework for Prompt-Learning.,10.0,21,True,2021-12-09 10:03:18.000,0.1.2,3.0,openprompt,,,,,6.0,6.0,https://pypi.org/project/openprompt,2021-12-09 09:57:22.000,,328.0,328.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, +664,TensorNets,taehoonlee/tensornets,tensorflow-utils,,https://github.com/taehoonlee/tensornets,https://github.com/taehoonlee/tensornets,MIT,2017-09-19 05:19:01.000,2021-01-02 06:28:10.000000,2021-01-02 06:26:24,284.0,,185,52.0,12.0,16.0,42.0,1000,High level network definitions with pre-trained weights in TensorFlow.,6.0,21,False,2020-03-31 04:38:27.000,0.4.6,12.0,tensornets,,,,['tensorflow'],48.0,44.0,https://pypi.org/project/tensornets,2020-03-31 04:35:15.000,4.0,165.0,165.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +665,advertorch,BorealisAI/advertorch,adversarial,,https://github.com/BorealisAI/advertorch,https://github.com/BorealisAI/advertorch,GPL-3.0,2018-11-29 22:17:33.000,2021-12-09 19:16:53.000000,2021-07-30 15:59:28,273.0,,163,31.0,52.0,16.0,33.0,999,A Toolbox for Adversarial Robustness Research.,18.0,21,False,2020-06-15 01:20:07.000,0.2.3,10.0,advertorch,,,,['pytorch'],71.0,67.0,https://pypi.org/project/advertorch,2020-06-15 01:20:07.000,4.0,537.0,537.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +666,luminol,linkedin/luminol,time-series-data,,https://github.com/linkedin/luminol,https://github.com/linkedin/luminol,Apache-2.0,2015-11-18 23:16:33.000,2020-12-27 09:54:35.000000,2018-01-09 07:46:55,69.0,,194,66.0,27.0,31.0,12.0,995,Anomaly Detection and Correlation library.,8.0,21,False,2016-01-20 01:01:44.000,0.3.1,5.0,luminol,,,,,65.0,50.0,https://pypi.org/project/luminol,2017-12-11 06:04:15.000,15.0,39515.0,39515.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +667,keras-ocr,faustomorales/keras-ocr,ocr,,https://github.com/faustomorales/keras-ocr,https://github.com/faustomorales/keras-ocr,MIT,2019-09-20 23:08:50.000,2022-01-14 10:29:35.968000,2021-11-24 10:01:11,184.0,2.0,240,40.0,35.0,53.0,106.0,969,A packaged and flexible version of the CRAFT text detector and Keras CRNN recognition model.,12.0,21,True,2021-11-24 10:05:08.000,0.8.9,29.0,keras-ocr,anaconda/keras-ocr,,,['tensorflow'],2.0,,https://pypi.org/project/keras-ocr,2021-11-24 10:05:08.000,2.0,6036.0,19178.0,https://anaconda.org/anaconda/keras-ocr,2022-01-14 10:29:35.968,19.0,,,,,3.0,223402.0,,,,,,,,,,,,,,,,,,,, +668,geoplotlib,andrea-cuttone/geoplotlib,geospatial-data,,https://github.com/andrea-cuttone/geoplotlib,https://github.com/andrea-cuttone/geoplotlib,MIT,2015-02-24 13:13:07.000,2021-10-20 12:00:24.000000,2019-05-06 07:06:50,159.0,,155,55.0,13.0,30.0,19.0,951,python toolbox for visualizing geographical data and making maps.,8.0,21,False,2016-07-27 14:55:01.000,0.3.2,4.0,geoplotlib,conda-forge/geoplotlib,,,,140.0,128.0,https://pypi.org/project/geoplotlib,2016-07-27 14:55:01.000,12.0,1207.0,1266.0,https://anaconda.org/conda-forge/geoplotlib,2021-05-31 16:11:51.234,535.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +669,Hivemind,learning-at-home/hivemind,distributed-ml,,https://github.com/learning-at-home/hivemind,https://github.com/learning-at-home/hivemind,MIT,2020-02-27 13:50:19.000,2022-02-09 13:57:27.000000,2022-02-09 13:57:26,486.0,40.0,59,47.0,340.0,42.0,74.0,913,Decentralized deep learning in PyTorch. Built to train models on thousands of volunteers across the world.,20.0,21,True,2022-02-07 10:06:24.000,1.0.1,15.0,hivemind,,,,,5.0,4.0,https://pypi.org/project/hivemind,2021-12-20 12:53:27.000,1.0,240.0,240.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +670,torchsde,google-research/torchsde,pytorch-utils,,https://github.com/google-research/torchsde,https://github.com/google-research/torchsde,Apache-2.0,2020-07-06 23:13:11.000,2021-07-26 13:59:41.000000,2021-07-26 13:59:38,157.0,,102,31.0,66.0,7.0,37.0,910,Differentiable SDE solvers with GPU support and efficient sensitivity analysis.,5.0,21,True,2021-07-20 07:09:56.000,0.2.5,4.0,torchsde,conda-forge/torchsde,,,['pytorch'],11.0,11.0,https://pypi.org/project/torchsde,2021-07-20 07:09:56.000,,14105.0,14756.0,https://anaconda.org/conda-forge/torchsde,2021-07-12 23:43:34.083,8465.0,,,,,3.0,,,,,,,,,5.0,,,,,,,,,,,, +671,attention-ocr,emedvedev/attention-ocr,ocr,,https://github.com/emedvedev/attention-ocr,https://github.com/emedvedev/attention-ocr,MIT,2017-07-21 18:35:19.000,2021-10-29 14:44:11.000000,2021-10-29 14:44:08,205.0,,243,47.0,45.0,23.0,126.0,887,A Tensorflow model for text recognition (CNN + seq2seq with visual attention) available as a Python package and..,27.0,21,True,2020-10-12 06:56:40.000,0.7.6,21.0,aocr,,,,['tensorflow'],18.0,18.0,https://pypi.org/project/aocr,2019-04-19 05:28:27.000,,246.0,246.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +672,mrq,pricingassistant/mrq,data-pipelines,,https://github.com/pricingassistant/mrq,https://github.com/pricingassistant/mrq,MIT,2014-02-13 09:32:40.000,2021-12-13 19:45:34.000000,2020-12-13 18:58:15,709.0,,113,64.0,64.0,59.0,119.0,861,Mr. Queue - A distributed worker task queue in Python using Redis & gevent.,38.0,21,False,2018-08-31 16:03:04.000,0.9.10,70.0,mrq,,,,,40.0,28.0,https://pypi.org/project/mrq,2018-08-31 16:03:04.000,12.0,361.0,361.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +673,tffm,geffy/tffm,tensorflow-utils,,https://github.com/geffy/tffm,https://github.com/geffy/tffm,MIT,2016-05-02 17:06:07.000,2022-01-17 20:39:04.000000,2022-01-17 20:38:58,107.0,1.0,188,34.0,15.0,18.0,22.0,776,TensorFlow implementation of an arbitrary order Factorization Machine.,10.0,21,True,2022-01-17 20:35:57.000,1.0.2,3.0,tffm,,,,['tensorflow'],12.0,11.0,https://pypi.org/project/tffm,2022-01-17 20:35:57.000,1.0,2121.0,2121.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +674,TensorFrames,databricks/tensorframes,distributed-ml,,https://github.com/databricks/tensorframes,https://github.com/databricks/tensorframes,Apache-2.0,2016-03-04 19:25:19.000,2022-02-09 23:38:50.000000,2019-11-15 21:43:53,221.0,,157,72.0,94.0,51.0,43.0,761,[DEPRECATED] Tensorflow wrapper for DataFrames on Apache Spark.,16.0,21,False,2018-11-16 20:50:02.000,0.6.0,6.0,tensorframes,,,,"['tensorflow', 'spark']",1.0,,https://pypi.org/project/tensorframes,2018-05-16 14:20:28.000,1.0,23234.0,23234.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +675,RLax,deepmind/rlax,reinforcement-learning,,https://github.com/deepmind/rlax,https://github.com/deepmind/rlax,Apache-2.0,2020-02-18 07:14:59.000,2022-02-04 10:12:10.000000,2022-02-04 10:12:05,147.0,14.0,57,28.0,41.0,9.0,9.0,739,A library of reinforcement learning building blocks in JAX.,16.0,21,True,2021-11-19 12:34:30.000,0.1.1,6.0,rlax,,,,['jax'],37.0,37.0,https://pypi.org/project/rlax,2021-11-19 12:34:30.000,,2950.0,2950.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +676,mlens,flennerhag/mlens,others,,https://github.com/flennerhag/mlens,https://github.com/flennerhag/mlens,MIT,2017-01-10 20:53:47.000,2020-02-25 14:32:48.000000,2020-02-25 14:31:53,879.0,,94,29.0,56.0,11.0,74.0,714,ML-Ensemble high performance ensemble learning.,7.0,21,False,2018-10-30 22:34:35.000,0.2.3,14.0,mlens,,,,,180.0,177.0,https://pypi.org/project/mlens,2018-10-30 22:30:43.000,3.0,1590.0,1590.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +677,NearPy,pixelogik/NearPy,nn-search,,https://github.com/pixelogik/NearPy,https://github.com/pixelogik/NearPy,MIT,2013-04-25 09:10:26.000,2021-09-26 01:44:54.000000,2018-10-21 17:54:28,159.0,,139,41.0,32.0,24.0,38.0,703,"Python framework for fast (approximated) nearest neighbour search in large, high-dimensional data sets using different..",18.0,21,False,2016-09-27 13:04:44.000,1.0.0,8.0,NearPy,,,,,80.0,64.0,https://pypi.org/project/NearPy,2016-09-27 13:03:12.000,16.0,3224.0,3224.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +678,nnAudio,KinWaiCheuk/nnAudio,audio,,https://github.com/KinWaiCheuk/nnAudio,https://github.com/KinWaiCheuk/nnAudio,MIT,2019-09-02 04:31:14.000,2021-12-24 09:38:22.000000,2021-12-24 09:32:42,281.0,9.0,62,18.0,66.0,12.0,37.0,653,Audio processing by using pytorch 1D convolution network.,13.0,21,True,2021-12-24 09:38:22.000,0.3.1,38.0,nnAudio,,,,,42.0,41.0,https://pypi.org/project/nnAudio,2021-12-24 09:38:22.000,1.0,1512.0,1512.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +679,vecstack,vecxoz/vecstack,others,,https://github.com/vecxoz/vecstack,https://github.com/vecxoz/vecstack,MIT,2016-11-08 13:23:21.000,2021-05-23 07:15:46.567000,2019-10-30 09:27:48,189.0,,75,21.0,12.0,,38.0,647,Python package for stacking (machine learning technique).,1.0,21,False,2019-08-12 16:09:01.000,0.4.0,6.0,vecstack,conda-forge/vecstack,,,,182.0,175.0,https://pypi.org/project/vecstack,2019-08-12 16:01:22.000,7.0,31881.0,31926.0,https://anaconda.org/conda-forge/vecstack,2021-05-23 07:15:46.567,407.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +680,TensorBoard Logger,TeamHG-Memex/tensorboard_logger,ml-experiments,,https://github.com/TeamHG-Memex/tensorboard_logger,https://github.com/TeamHG-Memex/tensorboard_logger,MIT,2016-10-27 14:02:25.000,2021-11-15 17:46:29.000000,2019-10-21 07:52:07,46.0,,51,29.0,11.0,11.0,15.0,620,Log TensorBoard events without touching TensorFlow.,5.0,21,False,2018-02-08 07:28:51.000,0.1.0,5.0,tensorboard_logger,,,,,51.0,,https://pypi.org/project/tensorboard_logger,2018-02-08 07:28:51.000,51.0,68879.0,68879.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +681,Torchbearer,pytorchbearer/torchbearer,ml-frameworks,,https://github.com/pytorchbearer/torchbearer,https://github.com/pytorchbearer/torchbearer,MIT,2018-03-12 16:30:42.000,2021-03-26 19:56:57.000000,2021-03-26 19:56:57,430.0,,68,29.0,422.0,8.0,237.0,616,torchbearer: A model fitting library for PyTorch.,13.0,21,True,2020-01-31 14:07:22.000,0.5.3,24.0,torchbearer,,,,['pytorch'],63.0,59.0,https://pypi.org/project/torchbearer,2020-01-31 14:05:56.000,4.0,673.0,673.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +682,TF Compression,tensorflow/compression,tensorflow-utils,,https://github.com/tensorflow/compression,https://github.com/tensorflow/compression,Apache-2.0,2018-05-15 23:32:19.000,2022-02-09 15:39:49.000000,2022-02-09 14:48:23,194.0,19.0,208,41.0,15.0,2.0,77.0,577,Data compression in TensorFlow.,10.0,21,True,2022-02-09 15:42:33.000,2.8.0,13.0,tensorflow-compression,,,,['tensorflow'],1.0,,https://pypi.org/project/tensorflow-compression,2022-02-09 15:39:49.000,1.0,989.0,989.0,,,,,,,,3.0,,,,,,,,,4.0,,,,,,,,,,,, +683,combo,yzhao062/combo,sklearn-utils,,https://github.com/yzhao062/combo,https://github.com/yzhao062/combo,BSD-2-Clause,2019-07-14 01:13:36.000,2021-10-02 13:57:54.000000,2021-10-02 13:57:52,207.0,,95,27.0,1.0,9.0,3.0,567,(AAAI 20) A Python Toolbox for Machine Learning Model Combination.,1.0,21,True,2020-12-23 02:21:49.000,0.1.2,12.0,combo,,,,"['sklearn', 'xgboost']",441.0,440.0,https://pypi.org/project/combo,2020-12-23 02:21:49.000,1.0,44446.0,44446.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +684,Submit it,facebookincubator/submitit,distributed-ml,,https://github.com/facebookincubator/submitit,https://github.com/facebookincubator/submitit,MIT,2020-04-24 07:41:09.000,2022-02-07 19:26:44.000000,2021-12-09 11:50:36,100.0,6.0,52,22.0,63.0,25.0,33.0,552,Python 3.6+ toolbox for submitting jobs to Slurm.,17.0,21,True,2021-11-30 13:57:53.000,1.4.1,15.0,submitit,conda-forge/submitit,,,,6.0,,https://pypi.org/project/submitit,2021-11-30 13:57:53.000,6.0,14206.0,14497.0,https://anaconda.org/conda-forge/submitit,2021-02-10 12:48:57.745,5249.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +685,pytorch_tabular,manujosephv/pytorch_tabular,tabular,,https://github.com/manujosephv/pytorch_tabular,https://github.com/manujosephv/pytorch_tabular,MIT,2020-12-15 07:17:03.000,2022-02-05 02:20:05.000000,2022-02-05 02:20:00,265.0,47.0,52,7.0,11.0,16.0,35.0,532,A standard framework for modelling Deep Learning Models for tabular data.,8.0,21,True,2021-09-01 11:51:30.000,0.7.0,8.0,pytorch_tabular,,,,['pytorch'],,,https://pypi.org/project/pytorch_tabular,2021-09-01 11:51:30.000,,1293.0,1293.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,,, +686,Poutyne,GRAAL-Research/poutyne,pytorch-utils,,https://github.com/GRAAL-Research/poutyne,https://github.com/GRAAL-Research/poutyne,LGPL-3.0,2017-12-07 18:30:17.000,2022-02-04 20:22:01.000000,2022-01-22 16:21:48,627.0,12.0,60,16.0,97.0,7.0,40.0,510,A simplified framework and utilities for PyTorch.,16.0,21,False,2021-12-17 18:16:02.000,1.8,25.0,poutyne,,,,['pytorch'],82.0,78.0,https://pypi.org/project/poutyne,2021-12-17 18:16:24.000,4.0,4206.0,4206.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +687,pyhsmm,mattjj/pyhsmm,probabilistics,,https://github.com/mattjj/pyhsmm,https://github.com/mattjj/pyhsmm,MIT,2012-03-18 17:40:13.000,2020-09-29 20:58:26.000000,2020-08-24 17:03:59,1426.0,,159,56.0,18.0,39.0,60.0,506,Bayesian inference in HSMMs and HMMs.,13.0,21,False,2017-05-10 17:14:37.000,0.1.7,8.0,pyhsmm,,,,,29.0,24.0,https://pypi.org/project/pyhsmm,2017-05-10 17:14:37.000,5.0,157.0,157.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +688,PyWaffle,gyli/PyWaffle,data-viz,,https://github.com/gyli/PyWaffle,https://github.com/gyli/PyWaffle,MIT,2017-11-14 20:03:47.000,2021-12-22 15:04:00.863000,2021-12-21 16:13:08,262.0,8.0,81,9.0,10.0,4.0,12.0,470,Make Waffle Charts in Python.,6.0,21,True,2021-12-21 16:10:13.000,0.6.4,25.0,pywaffle,conda-forge/pywaffle,,,,108.0,107.0,https://pypi.org/project/pywaffle,2021-12-21 16:10:13.000,1.0,2853.0,2962.0,https://anaconda.org/conda-forge/pywaffle,2021-12-22 15:04:00.863,4151.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +689,torch-cluster,rusty1s/pytorch_cluster,graph,,https://github.com/rusty1s/pytorch_cluster,https://github.com/rusty1s/pytorch_cluster,MIT,2018-01-12 20:56:06.000,2022-02-03 10:34:47.000000,2022-02-03 10:34:47,565.0,5.0,89,9.0,27.0,9.0,86.0,470,PyTorch Extension Library of Optimized Graph Cluster Algorithms.,20.0,21,True,2021-03-01 13:58:47.000,1.5.9,39.0,torch-cluster,conda-forge/pytorch_cluster,,,['pytorch'],26.0,,https://pypi.org/project/torch-cluster,2021-03-01 12:28:43.000,26.0,10323.0,11646.0,https://anaconda.org/conda-forge/pytorch_cluster,2022-01-13 17:00:46.492,27797.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +690,skope-rules,scikit-learn-contrib/skope-rules,sklearn-utils,,https://github.com/scikit-learn-contrib/skope-rules,https://github.com/scikit-learn-contrib/skope-rules,BSD-1-Clause,2018-02-18 13:42:47.000,2021-05-12 08:25:18.000000,2020-10-23 14:31:57,247.0,,68,24.0,29.0,23.0,5.0,435,machine learning with logical rules in Python.,18.0,21,False,2020-12-11 09:37:02.000,1.0.1,4.0,skope-rules,,,,['sklearn'],74.0,69.0,https://pypi.org/project/skope-rules,2020-01-25 12:01:37.000,5.0,92480.0,92480.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +691,MedPy,loli/medpy,medical-data,,https://github.com/loli/medpy,https://github.com/loli/medpy,GPL-3.0,2012-05-11 10:57:34.000,2021-11-11 11:54:44.393000,2020-05-01 15:25:38,324.0,,116,19.0,25.0,12.0,67.0,386,Medical image processing in Python.,13.0,21,False,2019-02-14 17:12:59.000,0.4.0,6.0,MedPy,conda-forge/medpy,,,,519.0,483.0,https://pypi.org/project/MedPy,2019-02-14 17:12:59.000,36.0,30039.0,30304.0,https://anaconda.org/conda-forge/medpy,2021-11-11 11:54:44.393,2125.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +692,Pandas Summary,polyaxon/datatile,data-containers,,https://github.com/polyaxon/datatile,https://github.com/polyaxon/datatile,Apache-2.0,2016-03-25 21:59:32.000,2022-02-08 15:31:50.000000,2022-02-08 15:31:45,33.0,9.0,37,9.0,8.0,8.0,7.0,385,"A library for managing, validating, summarizing, and visualizing data.",8.0,21,True,2021-11-25 22:52:42.000,0.2.0,10.0,pandas-summary,,,,['pandas'],57.0,,https://pypi.org/project/pandas-summary,2021-11-25 22:52:42.000,57.0,42846.0,42846.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +693,detoxify,unitaryai/detoxify,nlp,,https://github.com/unitaryai/detoxify,https://github.com/unitaryai/detoxify,Apache-2.0,2020-09-23 15:24:21.000,2022-01-31 18:29:18.000000,2022-01-14 11:14:08,190.0,11.0,41,11.0,17.0,10.0,13.0,376,Trained models & code to predict toxic comments on all 3 Jigsaw Toxic Comment Challenges. Built using Pytorch..,4.0,21,True,2021-10-27 17:12:11.000,0.4.0,10.0,detoxify,,,,,34.0,33.0,https://pypi.org/project/detoxify,2021-10-27 17:12:11.000,1.0,5773.0,7873.0,,,,,,,,3.0,31511.0,,,,,,,,,,,,,,,,,,,True, +694,tick,X-DataInitiative/tick,time-series-data,,https://github.com/X-DataInitiative/tick,https://github.com/X-DataInitiative/tick,BSD-3-Clause,2016-12-01 10:59:08.000,2022-01-30 17:29:29.000000,2020-06-15 12:01:36,413.0,,84,36.0,264.0,55.0,164.0,369,"Module for statistical learning, with a particular emphasis on time-dependent modelling.",16.0,21,False,2019-09-11 11:25:15.000,0.6,23.0,tick,,,,,50.0,49.0,https://pypi.org/project/tick,2020-05-24 22:01:17.000,1.0,966.0,969.0,,,,,,,,3.0,194.0,,,,,,,,,,,,,,,,,,,, +695,TimeSide,Parisson/TimeSide,audio,,https://github.com/Parisson/TimeSide,https://github.com/Parisson/TimeSide,AGPL-3.0,2011-11-21 21:48:08.000,2022-02-10 12:17:14.000000,2021-04-20 09:23:55,3418.0,,56,27.0,66.0,64.0,149.0,314,Scalable audio processing framework written in Python with a RESTful API.,19.0,21,False,2020-11-27 09:33:19.000,0.9.6,27.0,TimeSide,,,,,30.0,16.0,https://pypi.org/project/TimeSide,2021-12-15 14:33:37.113,14.0,209.0,209.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, +696,Brainiak,brainiak/brainiak,medical-data,,https://github.com/brainiak/brainiak,https://github.com/brainiak/brainiak,Apache-2.0,2016-02-08 23:19:27.000,2021-12-03 01:07:31.000000,2021-05-28 01:21:58,393.0,,123,33.0,316.0,72.0,123.0,261,Brain Imaging Analysis Kit.,33.0,21,False,2019-08-27 23:52:29.000,0.9.1,15.0,brainiak,,brainiak/brainiak,,,16.0,15.0,https://pypi.org/project/brainiak,2020-10-15 20:45:08.000,1.0,186.0,195.0,,,,https://hub.docker.com/r/brainiak/brainiak,2020-10-15 21:11:03.379549,1.0,692.0,3.0,,,,,,,,,,,,,,,,,,,,, +697,gokart,m3dev/gokart,ml-experiments,,https://github.com/m3dev/gokart,https://github.com/m3dev/gokart,MIT,2018-12-23 07:40:27.000,2022-02-10 14:32:33.000000,2022-01-31 07:15:18,453.0,5.0,41,22.0,206.0,15.0,51.0,234,"Gokart solves reproducibility, task dependencies, constraints of good code, and ease of use for Machine Learning..",30.0,21,False,2022-01-14 00:54:45.000,1.0.7,62.0,gokart,,,,,4.0,,https://pypi.org/project/gokart,2020-02-25 06:01:19.000,4.0,1060.0,1060.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +698,pymap3d,geospace-code/pymap3d,geospatial-data,,https://github.com/geospace-code/pymap3d,https://github.com/geospace-code/pymap3d,BSD-2-Clause,2014-08-03 04:28:03.000,2021-11-28 17:12:07.000000,2021-11-28 17:12:04,664.0,4.0,61,13.0,17.0,3.0,30.0,228,pure-Python (Numpy optional) 3D coordinate conversions for geospace ecef enu eci.,11.0,21,False,2021-11-22 06:36:42.000,2.7.3,51.0,pymap3d,conda-forge/pymap3d,,,,12.0,,https://pypi.org/project/pymap3d,2021-10-18 21:07:53.000,12.0,42528.0,43282.0,https://anaconda.org/conda-forge/pymap3d,2021-10-19 05:47:09.404,17363.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +699,Glow,projectglow/glow,medical-data,,https://github.com/projectglow/glow,https://github.com/projectglow/glow,Apache-2.0,2019-10-04 21:26:47.000,2022-02-09 20:29:28.000000,2022-02-09 20:29:28,373.0,18.0,60,18.0,352.0,51.0,79.0,189,An open-source toolkit for large-scale genomic analysis.,18.0,21,False,2021-12-02 00:37:53.000,1.1.2,14.0,glow.py,conda-forge/glow,,,,,,https://pypi.org/project/glow.py,2021-12-15 00:00:29.000,,21518.0,21636.0,https://anaconda.org/conda-forge/glow,2021-04-28 16:52:48.812,1424.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +700,lkpy,lenskit/lkpy,recommender-systems,,https://github.com/lenskit/lkpy,https://github.com/lenskit/lkpy,MIT,2018-06-08 21:05:10.000,2022-02-02 20:37:09.000000,2022-02-02 20:37:08,2334.0,44.0,50,8.0,202.0,26.0,65.0,188,Python recommendation toolkit.,13.0,21,False,2021-06-22 17:06:47.000,0.13.1,20.0,lenskit,conda-forge/lenskit,,,,1.0,,https://pypi.org/project/lenskit,2021-06-22 17:07:09.000,1.0,2880.0,3412.0,https://anaconda.org/conda-forge/lenskit,2021-11-12 01:30:50.433,7980.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +701,Larq Compute Engine,larq/compute-engine,model-serialisation,,https://github.com/larq/compute-engine,https://github.com/larq/compute-engine,Apache-2.0,2019-08-29 15:02:43.000,2022-02-07 07:42:58.000000,2022-02-07 07:42:57,515.0,16.0,29,21.0,565.0,21.0,118.0,185,Highly optimized inference engine for Binarized Neural Networks.,18.0,21,False,2021-09-08 21:44:17.000,0.6.2,15.0,larq-compute-engine,,,,,4.0,4.0,https://pypi.org/project/larq-compute-engine,2021-09-08 21:44:17.000,,493.0,509.0,,,,,,,,3.0,399.0,,,,,,,,,,,,,,,,,,,, +702,graph-nets,deepmind/graph_nets,graph,,https://github.com/deepmind/graph_nets,https://github.com/deepmind/graph_nets,Apache-2.0,2018-08-31 08:19:28.000,2020-12-04 17:43:48.000000,2020-12-04 17:43:47,47.0,,770,221.0,24.0,7.0,120.0,5077,Build Graph Nets in Tensorflow.,10.0,20,False,2020-01-29 16:00:25.000,1.1.0,7.0,graph-nets,,,,['tensorflow'],7.0,,https://pypi.org/project/graph-nets,2020-01-29 16:00:25.000,7.0,760.0,760.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +703,BytePS,bytedance/byteps,distributed-ml,,https://github.com/bytedance/byteps,https://github.com/bytedance/byteps,Apache-2.0,2019-06-25 07:00:13.000,2022-02-10 08:25:34.000000,2022-02-10 07:36:23,432.0,5.0,432,81.0,176.0,100.0,158.0,3068,A high performance and generic framework for distributed DNN training.,19.0,20,True,2020-08-27 15:42:13.000,0.2.4,8.0,byteps,,bytepsimage/tensorflow,,,,,https://pypi.org/project/byteps,2021-08-02 17:37:42.000,,84.0,122.0,,,,https://hub.docker.com/r/bytepsimage/tensorflow,2020-03-03 02:33:23.358610,,1234.0,3.0,,,,,,,,,,,,,,,,,,,,, +704,AdaBound,Luolc/AdaBound,pytorch-utils,,https://github.com/Luolc/AdaBound,https://github.com/Luolc/AdaBound,Apache-2.0,2019-02-15 18:05:20.000,2019-03-06 17:01:52.000000,2019-03-06 17:01:45,27.0,,327,78.0,1.0,17.0,7.0,2884,An optimizer that trains as fast as Adam and as good as SGD.,2.0,20,False,2019-03-06 16:44:42.000,0.0.5,4.0,adabound,,,,['pytorch'],133.0,126.0,https://pypi.org/project/adabound,2019-02-26 04:23:45.000,7.0,1279.0,1279.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +705,finmarketpy,cuemacro/finmarketpy,financial-data,,https://github.com/cuemacro/finmarketpy,https://github.com/cuemacro/finmarketpy,Apache-2.0,2015-02-19 23:32:03.000,2021-10-07 14:58:03.000000,2021-10-07 14:55:28,678.0,,448,216.0,16.0,23.0,3.0,2854,Python library for backtesting trading strategies & analyzing financial markets (formerly pythalesians).,14.0,20,True,2021-10-07 14:58:03.000,0.11.11,12.0,finmarketpy,,,,,4.0,4.0,https://pypi.org/project/finmarketpy,2021-10-07 14:58:03.000,,108.0,108.0,,,,,,,,3.0,40.0,,,,,,,,,,,,,,,,,,,, +706,image-match,ProvenanceLabs/image-match,image,,https://github.com/ProvenanceLabs/image-match,https://github.com/ProvenanceLabs/image-match,Apache-2.0,2016-03-08 18:16:45.000,2021-09-21 13:07:59.000000,2021-09-21 13:07:59,405.0,,380,100.0,53.0,56.0,48.0,2685,Quickly search over billions of images.,19.0,20,True,2017-02-13 14:54:48.000,1.1.2,10.0,image_match,,,,,4.0,,https://pypi.org/project/image_match,2017-02-13 14:54:48.000,4.0,584.0,584.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +707,opyrator,ml-tooling/opyrator,others,,https://github.com/ml-tooling/opyrator,https://github.com/ml-tooling/opyrator,MIT,2021-04-06 08:09:06.000,2022-01-21 19:58:38.000000,2021-05-06 12:10:38,127.0,,114,46.0,22.0,2.0,22.0,2577,"Turns your machine learning code into microservices with web API, interactive GUI, and more.",4.0,20,True,2021-05-04 18:48:03.000,0.0.12,11.0,opyrator,conda-forge/opyrator,,,,31.0,31.0,https://pypi.org/project/opyrator,2021-05-04 18:48:03.000,,142.0,177.0,https://anaconda.org/conda-forge/opyrator,2022-01-08 18:03:03.967,35.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +708,Apache Singa,apache/singa,distributed-ml,,https://github.com/apache/singa,https://github.com/apache/singa,Apache-2.0,2015-04-02 07:00:05.000,2022-01-18 11:03:40.000000,2021-08-10 09:12:48,2360.0,,755,122.0,851.0,40.0,49.0,2525,a distributed deep learning platform.,76.0,20,True,2020-04-21 08:01:08.000,3.0.0,16.0,,nusdbsystem/singa,apache/singa,,,1.0,1.0,,,,,8.0,https://anaconda.org/nusdbsystem/singa,2021-08-09 13:10:26.397,413.0,https://hub.docker.com/r/apache/singa,2019-06-04 04:32:52.195956,4.0,215.0,3.0,,,,,,,,,,,,,,,,,,,,, +709,Backtesting.py,kernc/backtesting.py,financial-data,,https://github.com/kernc/backtesting.py,https://github.com/kernc/backtesting.py,AGPL-3.0,2019-01-02 03:11:32.000,2022-01-27 10:39:10.000000,2021-12-18 23:12:51,250.0,5.0,439,85.0,56.0,47.0,235.0,2147,Backtest trading strategies in Python.,15.0,20,False,2017-07-22 02:00:06.000,0.0.1,1.0,backtesting,,,,,2.0,,https://pypi.org/project/backtesting,2017-07-22 02:00:06.000,2.0,7923.0,7923.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +710,riko,nerevu/riko,data-pipelines,,https://github.com/nerevu/riko,https://github.com/nerevu/riko,MIT,2016-06-02 12:22:51.000,2021-12-28 23:04:04.000000,2021-12-28 23:01:31,1269.0,8.0,75,53.0,23.0,22.0,8.0,1579,A Python stream processing engine modeled after Yahoo! Pipes.,18.0,20,True,2021-12-28 23:04:04.000,0.67.0,59.0,riko,,,,,1.0,,https://pypi.org/project/riko,2021-12-28 23:04:04.000,1.0,291.0,291.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +711,Antialiased CNNs,adobe/antialiased-cnns,pytorch-utils,,https://github.com/adobe/antialiased-cnns,https://github.com/adobe/antialiased-cnns,CC BY-NC-SA 4.0,2019-05-14 20:51:25.000,2021-09-29 18:48:52.000000,2021-09-29 18:48:52,239.0,,186,37.0,6.0,11.0,31.0,1482,pip install antialiased-cnns to improve stability and accuracy.,6.0,20,False,2020-10-23 22:45:52.000,0.3,6.0,antialiased-cnns,,,,['pytorch'],17.0,15.0,https://pypi.org/project/antialiased-cnns,2020-10-23 22:42:49.000,2.0,1192.0,1192.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +712,Norfair,tryolabs/norfair,image,,https://github.com/tryolabs/norfair,https://github.com/tryolabs/norfair,BSD-3-Clause,2020-07-01 20:15:44.000,2022-02-09 19:13:43.000000,2022-02-09 19:13:42,287.0,4.0,108,33.0,37.0,10.0,31.0,1274,Lightweight Python library for adding real-time object tracking to any detector.,10.0,20,True,2021-07-29 15:49:06.000,0.3.1,12.0,norfair,,,,,1.0,,https://pypi.org/project/norfair,2021-07-29 15:49:06.000,1.0,3363.0,3363.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +713,qdrant,qdrant/qdrant,nlp,,https://github.com/qdrant/qdrant,https://github.com/qdrant/qdrant,Apache-2.0,2020-05-30 21:37:01.000,2022-02-10 14:44:33.000000,2022-02-09 14:46:01,363.0,125.0,71,16.0,185.0,24.0,65.0,1130,Qdrant - vector similarity search engine with extended filtering support.,22.0,20,True,2022-02-03 12:02:30.000,0.5.0,11.0,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, +714,sklearn-porter,nok/sklearn-porter,model-serialisation,,https://github.com/nok/sklearn-porter,https://github.com/nok/sklearn-porter,MIT,2016-06-22 22:21:34.000,2022-02-02 16:58:53.000000,2019-12-18 13:31:50,699.0,,149,35.0,20.0,42.0,29.0,1120,"Transpile trained scikit-learn estimators to C, Java, JavaScript and others.",11.0,20,False,2019-12-18 13:39:19.000,0.7.4,20.0,sklearn-porter,,,,['sklearn'],1.0,,https://pypi.org/project/sklearn-porter,2019-12-18 13:39:19.000,1.0,379.0,379.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +715,DIG,divelab/DIG,graph,,https://github.com/divelab/DIG,https://github.com/divelab/DIG,GPL-3.0,2020-10-30 03:51:15.000,2022-01-28 17:33:30.000000,2022-01-28 17:33:30,851.0,7.0,134,26.0,8.0,8.0,67.0,1016,A library for graph deep learning research.,30.0,20,False,2021-10-13 00:38:18.000,0.1.2,10.0,dig,,,,,8.0,,https://pypi.org/project/dig,2015-08-23 10:30:20.000,8.0,523.0,523.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +716,Skater,oracle/Skater,interpretability,,https://github.com/oracle/Skater,https://github.com/oracle/Skater,UPL-1.0,2017-01-26 05:45:42.000,2021-11-15 19:51:51.883000,2020-06-29 20:07:12,1101.0,,165,55.0,147.0,69.0,97.0,1013,Python Library for Model Interpretation/Explanations.,34.0,20,False,2018-09-21 07:03:32.000,1.1.2,23.0,skater,conda-forge/skater,,,,,,https://pypi.org/project/skater,2018-09-21 07:03:32.000,,416.0,1240.0,https://anaconda.org/conda-forge/skater,2021-11-15 19:51:51.883,46146.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +717,iNNvestigate,albermax/innvestigate,interpretability,,https://github.com/albermax/innvestigate,https://github.com/albermax/innvestigate,BSD-2-Clause,2017-12-13 18:11:20.000,2022-01-21 20:32:45.000000,2021-08-03 15:45:16,943.0,,204,42.0,47.0,71.0,163.0,947,A toolbox to iNNvestigate neural networks predictions!.,19.0,20,True,2020-11-14 11:35:59.000,1.0.9,2.0,innvestigate,,,,['tensorflow'],1.0,,https://pypi.org/project/innvestigate,2020-11-14 11:35:59.000,1.0,469.0,469.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +718,NGT,yahoojapan/NGT,nn-search,,https://github.com/yahoojapan/NGT,https://github.com/yahoojapan/NGT,Apache-2.0,2016-09-01 07:36:57.000,2022-02-10 04:43:35.000000,2022-02-09 01:45:43,134.0,2.0,84,34.0,19.0,11.0,77.0,852,Nearest Neighbor Search with Neighborhood Graph and Tree for High-dimensional Data.,12.0,20,True,2022-02-10 04:43:35.000,1.14.1,51.0,ngt,,,,,8.0,,https://pypi.org/project/ngt,2022-02-10 04:43:35.000,8.0,17046.0,17046.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +719,jraph,deepmind/jraph,graph,,https://github.com/deepmind/jraph,https://github.com/deepmind/jraph,Apache-2.0,2020-11-23 10:27:12.000,2022-02-07 18:58:24.000000,2022-02-07 18:57:54,72.0,12.0,45,31.0,8.0,9.0,9.0,824,A Graph Neural Network Library in Jax.,13.0,20,True,2021-11-19 18:56:04.000,0.0.2.de0,2.0,jraph,conda-forge/jraph,,,['jax'],13.0,11.0,https://pypi.org/project/jraph,2021-11-19 19:05:01.000,2.0,1212.0,1281.0,https://anaconda.org/conda-forge/jraph,2021-10-31 19:30:27.109,278.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, +720,PFRL,pfnet/pfrl,reinforcement-learning,,https://github.com/pfnet/pfrl,https://github.com/pfnet/pfrl,MIT,2020-06-24 09:31:50.000,2022-01-16 16:46:43.000000,2021-12-06 07:44:27,388.0,1.0,106,97.0,107.0,27.0,33.0,785,PFRL: a PyTorch-based deep reinforcement learning library.,15.0,20,True,2021-07-07 02:43:23.000,0.3.0,5.0,pfrl,,,,,31.0,30.0,https://pypi.org/project/pfrl,2021-07-07 02:48:20.000,1.0,5286.0,5286.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +721,Saliency,PAIR-code/saliency,tensorflow-utils,,https://github.com/PAIR-code/saliency,https://github.com/PAIR-code/saliency,Apache-2.0,2017-06-09 22:07:35.000,2022-01-19 15:07:44.000000,2021-07-28 22:22:27,79.0,,159,28.0,52.0,14.0,26.0,762,"Framework-agnostic implementation for state-of-the-art saliency methods (XRAI, BlurIG, SmoothGrad, and more).",14.0,20,True,2021-05-03 16:33:29.000,0.1.3,10.0,saliency,,,,['tensorflow'],24.0,21.0,https://pypi.org/project/saliency,2021-05-03 16:33:29.000,3.0,736.0,736.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +722,Vulkan Kompute,KomputeProject/kompute,gpu-utilities,,https://github.com/KomputeProject/kompute,https://github.com/KomputeProject/kompute,Apache-2.0,2020-07-29 05:23:33.000,2022-01-30 13:34:23.000000,2022-01-30 13:34:23,999.0,38.0,54,22.0,101.0,56.0,111.0,746,"General purpose GPU compute framework built on Vulkan to support 1000s of cross vendor graphics cards (AMD, Qualcomm,..",16.0,20,True,2021-09-16 04:09:57.000,0.8.0,12.0,kp,,,,,2.0,2.0,https://pypi.org/project/kp,2021-09-15 06:20:19.000,,148.0,155.0,,,,,,,,3.0,127.0,,,,,,,,,,,,,,,,,,,, +723,kompute,KomputeProject/kompute,gpu-utilities,,https://github.com/KomputeProject/kompute,https://github.com/KomputeProject/kompute,Apache-2.0,2020-07-29 05:23:33.000,2022-01-30 13:34:23.000000,2022-01-30 13:34:23,999.0,38.0,54,22.0,101.0,56.0,111.0,746,"General purpose GPU compute framework built on Vulkan to support 1000s of cross vendor graphics cards (AMD, Qualcomm,..",16.0,20,True,2021-09-16 04:09:57.000,0.8.0,12.0,kp,,,,,2.0,2.0,https://pypi.org/project/kp,2021-09-15 06:20:19.000,,148.0,155.0,,,,,,,,3.0,127.0,,,,,,,,,,,,,,,,,,,True, +724,Test Tube,williamFalcon/test-tube,hyperopt,,https://github.com/williamFalcon/test-tube,https://github.com/williamFalcon/test-tube,MIT,2017-09-06 02:14:57.000,2021-10-14 18:44:27.000000,2020-03-17 22:44:47,642.0,,64,21.0,36.0,25.0,21.0,708,Python library to easily log experiments and parallelize hyperparameter search for neural networks.,16.0,20,False,2019-12-01 01:19:36.000,0.7.5,53.0,test_tube,,,,,5.0,,https://pypi.org/project/test_tube,2018-12-12 22:45:59.000,5.0,14451.0,14451.0,,,,,,,,3.0,10.0,,,,,,,,,,,,,,,,,,,, +725,finetune,IndicoDataSolutions/finetune,nlp,,https://github.com/IndicoDataSolutions/finetune,https://github.com/IndicoDataSolutions/finetune,MPL-2.0,2018-06-12 17:02:16.000,2022-02-10 03:35:11.000000,2021-12-20 17:41:00,1483.0,5.0,71,34.0,554.0,22.0,117.0,656,Scikit-learn style model finetuning for NLP.,19.0,20,True,2020-01-10 22:42:24.000,0.8.6,38.0,finetune,,,,"['tensorflow', 'sklearn']",11.0,9.0,https://pypi.org/project/finetune,2021-12-20 14:14:00.000,2.0,86.0,86.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +726,deeplift,kundajelab/deeplift,interpretability,,https://github.com/kundajelab/deeplift,https://github.com/kundajelab/deeplift,MIT,2016-06-01 02:18:06.000,2021-11-11 17:50:26.000000,2021-11-11 17:50:26,553.0,,139,37.0,45.0,34.0,48.0,607,Public facing deeplift repo.,11.0,20,True,2018-07-13 21:11:52.000,0.6.6,21.0,deeplift,,,,,58.0,54.0,https://pypi.org/project/deeplift,2020-11-11 09:32:57.000,4.0,527.0,527.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +727,Baal,ElementAI/baal,probabilistics,,https://github.com/ElementAI/baal,https://github.com/ElementAI/baal,Apache-2.0,2019-09-30 20:16:26.000,2022-02-05 14:48:49.000000,2022-01-10 03:19:15,154.0,14.0,50,21.0,110.0,18.0,45.0,537,Library to enable Bayesian active learning in your research or labeling work.,11.0,20,True,2021-12-17 20:29:34.000,1.5.1,13.0,baal,conda-forge/baal,,,,1.0,,https://pypi.org/project/baal,2021-12-17 20:28:12.000,1.0,735.0,812.0,https://anaconda.org/conda-forge/baal,2021-08-06 17:07:19.714,1003.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +728,seglearn,dmbee/seglearn,time-series-data,,https://github.com/dmbee/seglearn,https://github.com/dmbee/seglearn,BSD-3-Clause,2018-03-05 20:53:59.000,2021-03-13 16:18:30.000000,2021-03-12 17:12:50,268.0,,52,29.0,29.0,5.0,23.0,486,Python module for machine learning time series:.,13.0,20,True,2021-03-13 16:18:30.000,1.2.3,22.0,seglearn,,,,,12.0,11.0,https://pypi.org/project/seglearn,2021-03-13 16:18:30.000,1.0,1113.0,1113.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +729,aequitas,dssg/aequitas,interpretability,,https://github.com/dssg/aequitas,https://github.com/dssg/aequitas,MIT,2018-02-13 19:40:30.000,2021-07-13 10:19:56.000000,2021-05-27 09:45:10,857.0,,85,42.0,56.0,37.0,21.0,458,Bias and Fairness Audit Toolkit.,16.0,20,True,2020-12-16 11:48:14.000,0.42.0,16.0,aequitas,,,,,95.0,89.0,https://pypi.org/project/aequitas,2020-12-16 11:48:14.000,6.0,758.0,758.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +730,pydlm,wwrechard/pydlm,time-series-data,,https://github.com/wwrechard/pydlm,https://github.com/wwrechard/pydlm,BSD-3-Clause,2016-06-29 07:58:53.000,2021-02-24 14:21:28.000000,2019-10-22 07:18:40,362.0,,87,28.0,11.0,35.0,8.0,407,A python library for Bayesian time series modeling.,6.0,20,False,2016-11-06 01:43:35.000,0.1.1,13.0,pydlm,,,,,27.0,25.0,https://pypi.org/project/pydlm,2018-12-19 10:27:54.000,2.0,23561.0,23561.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +731,Auto TS,AutoViML/Auto_TS,time-series-data,,https://github.com/AutoViML/Auto_TS,https://github.com/AutoViML/Auto_TS,Apache-2.0,2020-02-15 15:23:32.000,2022-01-31 11:56:13.000000,2022-01-31 11:46:43,249.0,13.0,69,14.0,12.0,6.0,56.0,393,"Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of..",6.0,20,True,2022-01-31 11:56:13.000,0.0.64,30.0,auto-ts,,,,,,,https://pypi.org/project/auto-ts,2022-01-31 11:56:13.000,,2516.0,2516.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +732,deepsnap,snap-stanford/deepsnap,graph,,https://github.com/snap-stanford/deepsnap,https://github.com/snap-stanford/deepsnap,MIT,2020-06-06 21:17:38.000,2021-09-28 07:21:22.000000,2021-09-19 23:51:06,406.0,,43,59.0,6.0,13.0,23.0,387,Python library assists deep learning on graphs.,15.0,20,True,2021-09-05 23:08:21.000,0.2.1,5.0,deepsnap,,,,,16.0,15.0,https://pypi.org/project/deepsnap,2021-09-05 22:57:16.000,1.0,373.0,373.0,,,,,,,,3.0,8.0,,,,,,,,,,,,,,,,,,,True, +733,TSFEL,fraunhoferportugal/tsfel,time-series-data,,https://github.com/fraunhoferportugal/tsfel,https://github.com/fraunhoferportugal/tsfel,BSD-3-Clause,2019-01-09 16:41:30.000,2022-02-02 18:25:16.000000,2021-12-23 11:44:19,277.0,4.0,56,18.0,61.0,5.0,43.0,375,An intuitive library to extract features from time series.,13.0,20,True,2021-02-14 17:48:46.000,0.1.4,8.0,tsfel,,,,,25.0,25.0,https://pypi.org/project/tsfel,2021-02-14 17:40:32.000,,5749.0,5749.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +734,DESlib,scikit-learn-contrib/DESlib,sklearn-utils,,https://github.com/scikit-learn-contrib/DESlib,https://github.com/scikit-learn-contrib/DESlib,BSD-3-Clause,2017-12-08 22:49:49.000,2021-10-10 00:13:26.000000,2021-10-10 00:13:26,273.0,,73,15.0,121.0,14.0,129.0,371,A Python library for dynamic classifier and ensemble selection.,13.0,20,True,2021-02-08 06:29:25.000,0.3.5,4.0,deslib,,,,['sklearn'],24.0,22.0,https://pypi.org/project/deslib,2021-02-08 06:29:25.000,2.0,14465.0,14465.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +735,scikit-rebate,EpistasisLab/scikit-rebate,others,,https://github.com/EpistasisLab/scikit-rebate,https://github.com/EpistasisLab/scikit-rebate,MIT,2016-09-19 13:36:17.000,2021-12-29 00:49:30.000000,2021-02-15 17:10:59,283.0,,62,22.0,47.0,13.0,19.0,342,"A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for..",13.0,20,True,2017-04-12 16:12:01.000,0.3.4,13.0,skrebate,conda-forge/skrebate,,,['sklearn'],40.0,,https://pypi.org/project/skrebate,2021-03-20 17:11:52.000,40.0,2512.0,2998.0,https://anaconda.org/conda-forge/skrebate,2021-02-16 02:08:21.926,23847.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +736,MXBoard,awslabs/mxboard,ml-experiments,,https://github.com/awslabs/mxboard,https://github.com/awslabs/mxboard,Apache-2.0,2018-02-06 23:03:51.000,2021-11-30 10:46:24.000000,2020-01-24 23:21:55,42.0,,46,25.0,19.0,16.0,15.0,332,Logging MXNet data for visualization in TensorBoard.,9.0,20,False,2018-05-22 20:25:51.000,0.1.0,12.0,mxboard,,,,['mxnet'],138.0,131.0,https://pypi.org/project/mxboard,2018-05-22 20:25:51.000,7.0,9367.0,9367.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +737,Auto ViML,AutoViML/Auto_ViML,hyperopt,,https://github.com/AutoViML/Auto_ViML,https://github.com/AutoViML/Auto_ViML,Apache-2.0,2019-06-10 13:09:15.000,2021-12-06 01:40:00.000000,2021-12-06 01:38:51,293.0,1.0,70,22.0,5.0,4.0,14.0,329,Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome...,6.0,20,True,2021-12-06 01:40:00.000,0.1.684,133.0,autoviml,,,,,17.0,15.0,https://pypi.org/project/autoviml,2021-12-06 01:40:00.000,2.0,1106.0,1106.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +738,impyute,eltonlaw/impyute,others,,https://github.com/eltonlaw/impyute,https://github.com/eltonlaw/impyute,MIT,2017-01-21 09:16:27.000,2021-11-06 21:15:04.000000,2021-11-06 21:15:04,292.0,,43,8.0,37.0,27.0,37.0,307,Data imputations library to preprocess datasets with missing data.,11.0,20,True,2019-04-29 02:31:32.000,0.0.8,8.0,impyute,,,,,129.0,126.0,https://pypi.org/project/impyute,2019-04-29 02:31:32.000,3.0,2073.0,2073.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +739,SUOD,yzhao062/SUOD,others,,https://github.com/yzhao062/SUOD,https://github.com/yzhao062/SUOD,BSD-2-Clause,2019-11-20 00:23:54.000,2022-01-06 18:50:48.000000,2021-10-02 14:00:01,144.0,,40,15.0,1.0,6.0,2.0,306,(MLSys 21) An Acceleration System for Large-scare Unsupervised Heterogeneous Outlier Detection (Anomaly Detection).,1.0,20,True,2021-10-01 18:05:35.000,0.0.8,9.0,suod,,,,,408.0,408.0,https://pypi.org/project/suod,2021-10-01 18:05:35.000,,35081.0,35081.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +740,chefboost,serengil/chefboost,ml-frameworks,,https://github.com/serengil/chefboost,https://github.com/serengil/chefboost,MIT,2019-03-06 12:26:27.000,2022-02-02 12:03:51.000000,2022-02-02 12:03:51,345.0,18.0,79,14.0,2.0,2.0,15.0,297,"A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4,5, CART, CHAID and Regression Trees; some..",5.0,20,False,2022-01-12 10:40:48.000,0.0.16,16.0,chefboost,,,,,17.0,17.0,https://pypi.org/project/chefboost,2022-01-12 10:40:48.000,,787.0,787.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +741,launchpad,deepmind/launchpad,distributed-ml,,https://github.com/deepmind/launchpad,https://github.com/deepmind/launchpad,Apache-2.0,2021-02-18 15:16:49.000,2022-02-10 05:46:59.000000,2022-02-10 05:45:30,237.0,57.0,18,18.0,2.0,,18.0,254,Launchpad is a library that simplifies writing distributed programs and seamlessly launching them on a range of..,13.0,20,False,2022-01-06 12:29:48.000,0.4.1,7.0,dm-launchpad,,,,['tensorflow'],7.0,7.0,https://pypi.org/project/dm-launchpad,2022-01-06 12:29:48.000,,3019.0,3019.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +742,somoclu,peterwittek/somoclu,distributed-ml,,https://github.com/peterwittek/somoclu,https://github.com/peterwittek/somoclu,MIT,2013-01-16 06:33:16.000,2021-11-15 19:51:57.895000,2021-10-31 08:28:12,619.0,,61,26.0,29.0,26.0,107.0,232,"Massively parallel self-organizing maps: accelerate training on multicore CPUs, GPUs, and clusters.",19.0,20,False,2021-10-31 08:33:47.000,1.7.6,17.0,somoclu,conda-forge/somoclu,,,,7.0,,https://pypi.org/project/somoclu,2020-04-25 05:33:32.000,7.0,1108.0,2194.0,https://anaconda.org/conda-forge/somoclu,2021-11-15 19:51:57.895,57716.0,,,,,3.0,1576.0,,,,,,,,,,,,,,,,,,,, +743,pyfasttext,vrasneur/pyfasttext,nlp,,https://github.com/vrasneur/pyfasttext,https://github.com/vrasneur/pyfasttext,GPL-3.0,2017-06-30 18:44:42.000,2018-12-08 15:32:09.000000,2018-12-08 15:02:12,153.0,,30,9.0,4.0,21.0,28.0,230,Yet another Python binding for fastText.,4.0,20,False,2018-12-08 15:32:09.000,0.4.6,13.0,pyfasttext,,,,,216.0,203.0,https://pypi.org/project/pyfasttext,2018-12-08 15:32:09.000,13.0,5184.0,5190.0,,,,,,,,3.0,346.0,,,,,,,,,,,,,,,,,,,, +744,scikit-posthocs,maximtrp/scikit-posthocs,probabilistics,,https://github.com/maximtrp/scikit-posthocs,https://github.com/maximtrp/scikit-posthocs,MIT,2017-06-22 19:41:37.000,2021-11-26 21:39:34.000000,2021-11-26 21:39:28,466.0,3.0,23,5.0,7.0,4.0,39.0,230,Multiple Pairwise Comparisons (Post Hoc) Tests in Python.,8.0,20,False,2021-03-17 06:05:28.000,0.6.7,21.0,scikit-posthocs,conda-forge/scikit-posthocs,,,['sklearn'],19.0,,https://pypi.org/project/scikit-posthocs,2021-03-15 16:05:51.000,19.0,30176.0,30692.0,https://anaconda.org/conda-forge/scikit-posthocs,2021-03-15 21:17:30.605,8259.0,,,,,3.0,25.0,,,,,,,,,,,,,,,,,,,, +745,BatchFlow,analysiscenter/batchflow,data-pipelines,,https://github.com/analysiscenter/batchflow,https://github.com/analysiscenter/batchflow,Apache-2.0,2017-03-13 14:22:53.000,2022-02-10 13:45:52.000000,2022-02-10 13:38:27,4992.0,126.0,38,12.0,539.0,40.0,67.0,170,BatchFlow helps you conveniently work with random or sequential batches of your data and define data processing and..,30.0,20,False,2021-06-10 10:54:52.000,0.5.0,7.0,batchflow,,,,,,,https://pypi.org/project/batchflow,2021-06-10 10:54:52.000,,21.0,21.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +746,nvidia-ml-py3,nicolargo/nvidia-ml-py3,gpu-utilities,,https://github.com/nicolargo/nvidia-ml-py3,https://github.com/nicolargo/nvidia-ml-py3,BSD-3-Clause,2017-06-03 07:47:03.000,2021-07-24 06:21:40.748000,2019-03-06 20:41:09,5.0,,49,3.0,1.0,2.0,,72,Python 3 Bindings for the NVIDIA Management Library.,2.0,20,False,2017-06-03 07:43:46.000,7.352.0,1.0,nvidia-ml-py3,anaconda/nvidia-ml,,,,5060.0,4927.0,https://pypi.org/project/nvidia-ml-py3,2017-06-03 07:43:46.000,133.0,751502.0,751502.0,https://anaconda.org/anaconda/nvidia-ml,2021-07-24 06:21:40.748,3.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +747,DeepMind Lab,deepmind/lab,reinforcement-learning,,https://github.com/deepmind/lab,https://github.com/deepmind/lab,GPL-2.0,2016-11-30 13:41:26.000,2022-01-05 14:39:38.000000,2022-01-05 13:45:51,493.0,4.0,1323,476.0,18.0,51.0,160.0,6626,A customisable 3D platform for agent-based AI research.,7.0,19,False,2020-12-07 11:26:33.000,release-2020-12-07,8.0,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +748,SerpentAI,SerpentAI/SerpentAI,reinforcement-learning,,https://github.com/SerpentAI/SerpentAI,https://github.com/SerpentAI/SerpentAI,MIT,2017-04-16 21:48:39.000,2021-12-05 00:55:52.000000,2020-05-22 22:34:09,250.0,,716,329.0,58.0,2.0,,6156,Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!.,7.0,19,False,2018-02-17 00:12:46.000,2018.1.2,18.0,SerpentAI,,,,,,,https://pypi.org/project/SerpentAI,2018-02-17 00:12:46.000,,130.0,137.0,,,,,,,,3.0,159.0,,,,,,,,,,,,,,,,,,,True, +749,tinygrad,geohot/tinygrad,pytorch-utils,,https://github.com/geohot/tinygrad,https://github.com/geohot/tinygrad,MIT,2020-10-18 16:23:12.000,2022-02-10 08:40:24.000000,2022-02-10 08:40:24,672.0,82.0,571,120.0,205.0,21.0,87.0,5163,You like pytorch? You like micrograd? You love tinygrad!.,54.0,19,True,,,,,,,,['pytorch'],2.0,2.0,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +750,PySlowFast,facebookresearch/SlowFast,image,,https://github.com/facebookresearch/SlowFast,https://github.com/facebookresearch/SlowFast,Apache-2.0,2019-08-20 22:47:26.000,2022-02-04 12:58:13.000000,2021-10-28 14:20:52,163.0,,862,96.0,32.0,246.0,240.0,4552,PySlowFast: video understanding codebase from FAIR for reproducing state-of-the-art video models.,25.0,19,True,,,1.0,pyslowfast,,,,['pytorch'],6.0,6.0,https://pypi.org/project/pyslowfast,2020-01-15 23:51:07.000,,15.0,15.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +751,pdftabextract,WZBSocialScienceCenter/pdftabextract,ocr,,https://github.com/WZBSocialScienceCenter/pdftabextract,https://github.com/WZBSocialScienceCenter/pdftabextract,Apache-2.0,2016-07-08 11:44:46.000,2020-12-28 00:52:23.000000,2018-10-26 13:57:02,168.0,,342,89.0,3.0,3.0,18.0,1972,A set of tools for extracting tables from PDF files helping to do data mining on (OCR-processed) scanned documents.,2.0,19,False,2018-01-09 08:00:24.000,0.3.0,5.0,pdftabextract,,,,,40.0,39.0,https://pypi.org/project/pdftabextract,2018-01-09 08:00:24.000,1.0,685.0,685.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +752,spark-deep-learning,databricks/spark-deep-learning,data-pipelines,,https://github.com/databricks/spark-deep-learning,https://github.com/databricks/spark-deep-learning,Apache-2.0,2017-05-31 17:30:28.000,2021-09-26 02:36:04.000000,2021-08-19 02:08:33,136.0,,455,151.0,140.0,76.0,27.0,1904,Deep Learning Pipelines for Apache Spark.,16.0,19,True,2020-01-08 19:50:31.000,1.6.0,9.0,,,,,['spark'],19.0,19.0,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +753,pycls,facebookresearch/pycls,image,,https://github.com/facebookresearch/pycls,https://github.com/facebookresearch/pycls,MIT,2019-06-10 22:47:17.000,2022-02-09 18:45:09.000000,2021-08-19 02:33:54,91.0,,210,59.0,96.0,21.0,56.0,1841,"Codebase for Image Classification Research, written in PyTorch.",13.0,19,True,2021-05-21 00:29:47.000,0.2,3.0,pycls,,,,['pytorch'],5.0,5.0,https://pypi.org/project/pycls,2020-09-05 00:21:00.000,,465.0,465.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +754,doc2text,jlsutherland/doc2text,ocr,,https://github.com/jlsutherland/doc2text,https://github.com/jlsutherland/doc2text,MIT,2016-08-28 19:30:02.000,2020-12-01 22:56:27.000000,2020-12-01 22:56:26,62.0,,101,40.0,13.0,14.0,9.0,1250,Detect text blocks and OCR poorly scanned PDFs in bulk. Python module available via pip.,5.0,19,False,2016-09-06 21:59:21.000,0.2.4,5.0,doc2text,,,,,50.0,50.0,https://pypi.org/project/doc2text,2016-09-06 21:59:21.000,,574.0,574.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +755,AdvBox,advboxes/AdvBox,adversarial,,https://github.com/advboxes/AdvBox,https://github.com/advboxes/AdvBox,Apache-2.0,2018-08-08 08:55:41.000,2022-02-09 23:58:53.000000,2021-05-03 22:51:52,375.0,,240,57.0,50.0,8.0,29.0,1200,Advbox is a toolbox to generate adversarial examples that fool neural networks in..,19.0,19,True,2018-12-05 02:48:50.000,0.4.1,2.0,advbox,,,,,,,https://pypi.org/project/advbox,2018-12-05 02:48:50.000,,26.0,26.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +756,Databolt Flow,d6t/d6tflow,data-pipelines,,https://github.com/d6t/d6tflow,https://github.com/d6t/d6tflow,MIT,2019-02-03 01:51:22.000,2021-10-06 00:53:48.000000,2021-09-28 02:59:00,266.0,,69,22.0,18.0,10.0,13.0,935,Python library for building highly effective data science workflows.,12.0,19,True,2021-10-06 00:53:48.000,0.2.5,21.0,d6tflow,,,,,19.0,19.0,https://pypi.org/project/d6tflow,2021-10-06 00:53:48.000,,208.0,208.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +757,Performer Pytorch,lucidrains/performer-pytorch,pytorch-utils,,https://github.com/lucidrains/performer-pytorch,https://github.com/lucidrains/performer-pytorch,MIT,2020-10-03 03:41:36.000,2022-02-02 20:34:04.000000,2022-02-02 20:33:18,124.0,1.0,105,15.0,11.0,31.0,41.0,781,"An implementation of Performer, a linear attention-based transformer, in Pytorch.",6.0,19,True,2022-02-02 20:34:04.000,1.1.4,80.0,performer-pytorch,,,,['pytorch'],42.0,38.0,https://pypi.org/project/performer-pytorch,2022-02-02 20:34:04.000,4.0,1463.0,1463.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +758,ADTK,arundo/adtk,time-series-data,,https://github.com/arundo/adtk,https://github.com/arundo/adtk,MPL-2.0,2019-09-27 00:34:22.000,2021-07-18 06:52:12.000000,2020-04-17 02:27:44,79.0,,94,25.0,73.0,26.0,35.0,773,A Python toolkit for rule-based/unsupervised anomaly detection in time series.,11.0,19,False,2020-04-17 02:18:00.000,0.6.2,13.0,adtk,conda-forge/adtk,,,,,,https://pypi.org/project/adtk,2020-04-17 02:18:00.000,,101199.0,101356.0,https://anaconda.org/conda-forge/adtk,2020-04-20 19:46:14.062,3627.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +759,AlphaPy,ScottfreeLLC/AlphaPy,hyperopt,,https://github.com/ScottfreeLLC/AlphaPy,https://github.com/ScottfreeLLC/AlphaPy,Apache-2.0,2016-02-14 00:47:32.000,2021-12-22 00:07:44.000000,2021-10-23 07:17:16,413.0,,152,57.0,3.0,12.0,29.0,712,"Automated Machine Learning [AutoML] with Python, scikit-learn, Keras, XGBoost, LightGBM, and CatBoost.",3.0,19,True,2020-08-29 18:48:20.000,2.5.0,25.0,alphapy,,,,,3.0,3.0,https://pypi.org/project/alphapy,2020-08-29 18:44:15.000,,87.0,87.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +760,sklearn-deap,rsteca/sklearn-deap,hyperopt,,https://github.com/rsteca/sklearn-deap,https://github.com/rsteca/sklearn-deap,MIT,2015-10-28 22:52:34.000,2021-07-30 15:13:54.000000,2021-07-30 15:06:27,104.0,,114,29.0,25.0,21.0,34.0,676,Use evolutionary algorithms instead of gridsearch in scikit-learn.,22.0,19,True,2021-07-30 15:13:54.000,0.3.0,14.0,sklearn-deap,,,,['sklearn'],33.0,31.0,https://pypi.org/project/sklearn-deap,2021-07-30 15:13:54.000,2.0,732.0,732.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +761,matrixprofile-ts,target/matrixprofile-ts,time-series-data,,https://github.com/target/matrixprofile-ts,https://github.com/target/matrixprofile-ts,Apache-2.0,2018-09-10 19:03:34.000,2020-04-25 18:38:20.000000,2020-04-25 18:37:42,198.0,,92,24.0,46.0,19.0,34.0,671,A Python library for detecting patterns and anomalies in massive datasets using the Matrix Profile.,15.0,19,False,2019-08-08 01:24:38.000,0.0.9,9.0,matrixprofile-ts,,,,,18.0,18.0,https://pypi.org/project/matrixprofile-ts,2019-08-08 01:24:38.000,,1090.0,1090.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +762,NeoML,neoml-lib/neoml,ml-frameworks,,https://github.com/neoml-lib/neoml,https://github.com/neoml-lib/neoml,Apache-2.0,2020-06-14 17:37:36.000,2022-02-10 11:31:35.000000,2022-02-10 11:31:35,562.0,89.0,102,30.0,507.0,28.0,42.0,665,Machine learning framework for both deep learning and traditional algorithms.,29.0,19,True,2021-06-22 05:25:53.000,NeoML-master_2.0.5.0,5.0,neoml,,,,,,,https://pypi.org/project/neoml,2021-06-21 21:43:53.000,,87.0,87.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +763,Tensor Sensor,parrt/tensor-sensor,pytorch-utils,,https://github.com/parrt/tensor-sensor,https://github.com/parrt/tensor-sensor,MIT,2020-08-28 22:54:04.000,2021-12-13 18:54:27.000000,2021-12-13 18:54:25,234.0,29.0,33,12.0,13.0,8.0,15.0,624,"The goal of this library is to generate more helpful exception messages for matrix algebra expressions for numpy,..",3.0,19,True,2021-12-11 21:24:11.000,1.0,37.0,tensor-sensor,conda-forge/tensor-sensor,,,['pytorch'],7.0,7.0,https://pypi.org/project/tensor-sensor,2021-12-11 21:24:35.000,,2066.0,2106.0,https://anaconda.org/conda-forge/tensor-sensor,2021-12-11 23:37:02.831,160.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +764,Dragonfly,dragonfly/dragonfly,hyperopt,,https://github.com/dragonfly/dragonfly,https://github.com/dragonfly/dragonfly,MIT,2018-04-20 22:19:50.000,2021-07-31 04:54:26.000000,2020-07-03 18:01:17,397.0,,202,29.0,35.0,34.0,19.0,621,An open source python library for scalable Bayesian optimisation.,12.0,19,False,2020-07-03 18:05:12.000,0.1.6,9.0,dragonfly-opt,,,,,2.0,,https://pypi.org/project/dragonfly-opt,2020-07-03 18:05:12.000,2.0,29867.0,29867.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +765,cuSignal,rapidsai/cusignal,gpu-utilities,,https://github.com/rapidsai/cusignal,https://github.com/rapidsai/cusignal,Apache-2.0,2019-08-22 14:27:27.000,2022-02-08 16:07:15.000000,2022-01-28 16:44:39,1182.0,17.0,81,40.0,333.0,15.0,111.0,569,GPU accelerated signal processing.,36.0,19,True,2022-02-02 15:59:38.000,22.02.00,11.0,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +766,tcav,tensorflow/tcav,interpretability,,https://github.com/tensorflow/tcav,https://github.com/tensorflow/tcav,Apache-2.0,2018-07-03 17:45:35.000,2022-02-10 00:14:14.000000,2021-09-16 17:56:31,171.0,,122,31.0,68.0,7.0,53.0,506,Code for the TCAV ML interpretability project.,19.0,19,True,2021-02-23 16:17:42.000,0.2.2,4.0,tcav,,,,['tensorflow'],14.0,11.0,https://pypi.org/project/tcav,2021-02-23 16:17:42.000,3.0,119.0,119.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +767,carefree-learn,carefree0910/carefree-learn,tabular,,https://github.com/carefree0910/carefree-learn,https://github.com/carefree0910/carefree-learn,MIT,2020-06-17 17:44:17.000,2022-02-03 04:45:29.000000,2022-02-03 04:45:25,3200.0,24.0,30,10.0,1.0,,80.0,357,Deep Learning PyTorch.,1.0,19,True,2022-01-29 03:42:09.000,0.2.2,20.0,carefree-learn,,,,['pytorch'],2.0,2.0,https://pypi.org/project/carefree-learn,2021-10-29 05:36:03.000,,155.0,155.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,, +768,rrcf,kLabUM/rrcf,others,,https://github.com/kLabUM/rrcf,https://github.com/kLabUM/rrcf,MIT,2018-10-20 05:39:05.000,2021-01-13 23:05:23.000000,2020-06-10 01:07:39,253.0,,81,20.0,52.0,22.0,17.0,354,Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams.,4.0,19,False,2020-06-10 01:53:55.000,0.4.3,7.0,rrcf,,,,,34.0,32.0,https://pypi.org/project/rrcf,2020-06-10 01:53:55.000,2.0,9240.0,9240.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +769,pykale,pykale/pykale,others,,https://github.com/pykale/pykale,https://github.com/pykale/pykale,MIT,2020-06-30 08:06:10.000,2022-02-10 15:01:54.000000,2022-01-20 17:03:09,1770.0,95.0,39,9.0,178.0,10.0,70.0,321,Knowledge-Aware machine LEarning (KALE): accessible machine learning from multiple sources for interdisciplinary..,16.0,19,True,2021-10-13 22:01:16.000,0.1.0rc4,8.0,pykale,,,,['pytorch'],,,https://pypi.org/project/pykale,2021-10-13 22:02:19.000,,46.0,46.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +770,sklearn-evaluation,edublancas/sklearn-evaluation,interpretability,,https://github.com/edublancas/sklearn-evaluation,https://github.com/edublancas/sklearn-evaluation,MIT,2015-09-04 16:33:42.000,2021-10-17 18:15:40.000000,2021-10-17 18:09:37,533.0,,28,13.0,3.0,8.0,29.0,320,"Machine learning model evaluation made easy: plots, tables, HTML reports, experiment tracking and Jupyter notebook..",6.0,19,True,2021-10-17 18:15:40.000,0.5.7,19.0,sklearn-evaluation,,,,['sklearn'],40.0,38.0,https://pypi.org/project/sklearn-evaluation,2021-10-17 18:15:40.000,2.0,1030.0,1030.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +771,quinn,MrPowers/quinn,ml-experiments,,https://github.com/MrPowers/quinn,https://github.com/MrPowers/quinn,Apache-2.0,2017-09-15 13:02:42.000,2021-03-27 14:31:44.000000,2021-02-09 04:48:07,110.0,,40,20.0,18.0,17.0,9.0,311,pyspark methods to enhance developer productivity.,6.0,19,True,2021-02-06 15:21:04.000,0.9.0,12.0,quinn,,,,['spark'],4.0,,https://pypi.org/project/quinn,2021-02-06 15:21:04.000,4.0,464530.0,464530.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +772,textpipe,textpipe/textpipe,nlp,,https://github.com/textpipe/textpipe,https://github.com/textpipe/textpipe,MIT,2018-06-21 16:23:32.000,2021-06-09 11:55:53.000000,2021-06-09 11:55:53,371.0,,23,23.0,239.0,24.0,25.0,293,Textpipe: clean and extract metadata from text.,28.0,19,False,2021-01-25 14:05:21.000,0.12.2,39.0,textpipe,,,,,9.0,8.0,https://pypi.org/project/textpipe,2021-01-25 14:05:21.000,1.0,1051.0,1051.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +773,sk-dist,Ibotta/sk-dist,distributed-ml,,https://github.com/Ibotta/sk-dist,https://github.com/Ibotta/sk-dist,Apache-2.0,2019-08-14 21:07:17.000,2021-07-07 00:44:10.000000,2021-07-07 00:44:07,58.0,,47,25.0,38.0,7.0,10.0,275,Distributed scikit-learn meta-estimators in PySpark.,7.0,19,False,2020-05-14 22:20:14.000,0.1.9,12.0,sk-dist,,,,"['sklearn', 'spark']",11.0,9.0,https://pypi.org/project/sk-dist,2020-05-14 22:20:14.000,2.0,40771.0,40771.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +774,fastT5,Ki6an/fastT5,nlp,,https://github.com/Ki6an/fastT5,https://github.com/Ki6an/fastT5,Apache-2.0,2021-03-11 08:46:42.000,2022-01-14 11:55:53.000000,2022-01-06 19:38:13,32.0,16.0,28,5.0,8.0,11.0,21.0,254,boost inference speed of T5 models by 5x & reduce the model size by 3x.,5.0,19,False,2022-01-06 19:43:48.000,0.1.2,12.0,fastt5,,,,,7.0,7.0,https://pypi.org/project/fastt5,2022-01-06 19:43:48.000,,785.0,785.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +775,fletcher,xhochy/fletcher,data-containers,,https://github.com/xhochy/fletcher,https://github.com/xhochy/fletcher,MIT,2018-03-04 16:44:22.000,2021-11-04 09:30:27.570000,2021-02-18 14:46:18,520.0,,34,19.0,146.0,34.0,40.0,220,Pandas ExtensionDType/Array backed by Apache Arrow.,24.0,19,False,2021-01-17 20:11:01.000,0.7.2,16.0,fletcher,conda-forge/fletcher,,,['pandas'],4.0,3.0,https://pypi.org/project/fletcher,2021-01-17 20:11:01.000,1.0,201.0,1111.0,https://anaconda.org/conda-forge/fletcher,2021-11-04 09:30:27.570,39169.0,,,,,3.0,13.0,,,,,,,,,,,,,,,,,,,, +776,Muda,bmcfee/muda,audio,,https://github.com/bmcfee/muda,https://github.com/bmcfee/muda,ISC,2014-11-07 21:21:22.000,2021-12-15 16:53:25.527000,2021-05-03 14:04:36,293.0,,34,12.0,36.0,7.0,44.0,198,A library for augmenting annotated audio data.,7.0,19,False,2019-11-15 15:46:21.000,0.4.1,12.0,muda,,,,,15.0,14.0,https://pypi.org/project/muda,2021-12-15 16:53:25.527,1.0,204.0,204.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +777,Funsor,pyro-ppl/funsor,probabilistics,,https://github.com/pyro-ppl/funsor,https://github.com/pyro-ppl/funsor,Apache-2.0,2019-01-30 23:13:39.000,2021-12-13 22:27:14.000000,2021-12-13 22:24:28,561.0,1.0,15,16.0,444.0,83.0,73.0,187,Functional tensors for probabilistic programming.,9.0,19,False,2021-12-13 22:52:43.000,0.4.2,8.0,funsor,,,,['pytorch'],24.0,22.0,https://pypi.org/project/funsor,2021-12-13 22:27:14.000,2.0,1792.0,1792.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +778,chitra,gradsflow/chitra,ml-experiments,,https://github.com/gradsflow/chitra,https://github.com/gradsflow/chitra,Apache-2.0,2020-01-23 14:17:54.000,2022-01-24 02:31:36.059000,2022-01-13 09:09:43,363.0,21.0,34,5.0,125.0,5.0,33.0,177,"A multi-functional library for full-stack Deep Learning. Simplifies Model Building, API development, and Model..",14.0,19,False,2021-11-26 17:10:22.000,0.2.0,38.0,chitra,conda-forge/chitra,,,,,,https://pypi.org/project/chitra,2022-01-09 08:49:42.000,,252.0,327.0,https://anaconda.org/conda-forge/chitra,2022-01-24 02:31:36.059,75.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, +779,DEβ«ΆTR,facebookresearch/detr,image,,https://github.com/facebookresearch/detr,https://github.com/facebookresearch/detr,Apache-2.0,2020-05-26 23:54:52.000,2021-11-28 09:13:56.000000,2021-10-18 10:06:31,45.0,,1424,148.0,71.0,136.0,268.0,8344,End-to-End Object Detection with Transformers.,24.0,18,True,2020-06-29 16:41:01.000,0.2,1.0,,,,,['pytorch'],,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +780,prettymaps,marceloprates/prettymaps,geospatial-data,,https://github.com/marceloprates/prettymaps,https://github.com/marceloprates/prettymaps,AGPL-3.0,2021-03-05 12:22:05.000,2022-01-08 18:08:26.920000,2022-01-07 13:32:00,148.0,1.0,329,70.0,29.0,30.0,20.0,7722,"A small set of Python functions to draw pretty maps from OpenStreetMap data. Based on osmnx, matplotlib and shapely..",14.0,18,False,2021-10-19 13:33:43.000,0.1.3,4.0,prettymaps,conda-forge/prettymaps,,,,5.0,5.0,https://pypi.org/project/prettymaps,2021-10-19 13:33:43.000,,611.0,642.0,https://anaconda.org/conda-forge/prettymaps,2022-01-08 18:08:26.920,31.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, +781,Spotlight,maciejkula/spotlight,recommender-systems,,https://github.com/maciejkula/spotlight,https://github.com/maciejkula/spotlight,MIT,2017-06-25 18:52:19.000,2020-11-15 08:21:28.000000,2020-02-09 21:03:48,299.0,,391,111.0,79.0,67.0,48.0,2658,Deep recommender models using PyTorch.,11.0,18,False,2019-09-08 10:19:53.000,0.1.6,7.0,,maciejkula/spotlight,,,['pytorch'],,,,,,,118.0,https://anaconda.org/maciejkula/spotlight,2018-05-27 18:32:12.235,6639.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +782,pytorchviz,szagoruyko/pytorchviz,pytorch-utils,,https://github.com/szagoruyko/pytorchviz,https://github.com/szagoruyko/pytorchviz,MIT,2018-01-30 15:37:55.000,2021-07-15 01:54:59.000000,2021-06-15 18:41:51,22.0,,218,30.0,18.0,19.0,33.0,2112,A small package to create visualizations of PyTorch execution graphs.,6.0,18,True,,,,,,,,,572.0,572.0,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, +783,NeuroNER,Franck-Dernoncourt/NeuroNER,nlp,,https://github.com/Franck-Dernoncourt/NeuroNER,https://github.com/Franck-Dernoncourt/NeuroNER,MIT,2017-03-07 01:24:15.000,2022-02-10 00:08:21.000000,2019-10-02 23:26:11,132.0,,452,84.0,31.0,82.0,67.0,1590,Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results.,7.0,18,False,2019-10-02 23:30:15.000,1.0.8,7.0,pyneuroner,,,,,,,https://pypi.org/project/pyneuroner,2019-10-02 23:30:15.000,,72.0,72.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +784,keepsake,replicate/keepsake,ml-experiments,,https://github.com/replicate/keepsake,https://github.com/replicate/keepsake,Apache-2.0,2020-07-01 04:37:44.000,2022-02-09 23:26:26.000000,2021-05-07 00:33:52,788.0,,60,10.0,661.0,123.0,64.0,1549,Version control for machine learning.,16.0,18,True,2021-03-11 21:15:01.000,0.4.2,7.0,keepsake,,,,,,,https://pypi.org/project/keepsake,2021-03-11 21:15:01.000,,844.0,844.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +785,Lambda Networks,lucidrains/lambda-networks,pytorch-utils,,https://github.com/lucidrains/lambda-networks,https://github.com/lucidrains/lambda-networks,MIT,2020-10-08 19:01:15.000,2020-11-18 19:54:34.000000,2020-11-18 19:54:30,31.0,,153,46.0,3.0,12.0,15.0,1497,"Implementation of LambdaNetworks, a new approach to image recognition that reaches SOTA with less compute.",3.0,18,False,2020-11-18 08:19:23.000,0.4.0,11.0,lambda-networks,,,,['pytorch'],4.0,4.0,https://pypi.org/project/lambda-networks,2020-11-18 08:19:23.000,,187.0,187.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +786,Torch-Struct,harvardnlp/pytorch-struct,pytorch-utils,,https://github.com/harvardnlp/pytorch-struct,https://github.com/harvardnlp/pytorch-struct,MIT,2019-08-26 19:34:30.000,2022-01-30 19:50:59.000000,2022-01-30 19:49:08,271.0,3.0,80,32.0,72.0,24.0,30.0,1017,"Fast, general, and tested differentiable structured prediction in PyTorch.",16.0,18,True,2021-02-15 20:20:59.000,0.5,2.0,torch-struct,,,,['pytorch'],,,https://pypi.org/project/torch-struct,2021-02-14 02:43:46.000,,7208.0,7208.0,,,,,,,,3.0,,,,,,,,,4.0,,,,,,,,,,,, +787,Fiber,uber/fiber,distributed-ml,,https://github.com/uber/fiber,https://github.com/uber/fiber,Apache-2.0,2020-01-07 18:16:24.000,2021-06-30 02:02:42.000000,2021-03-15 07:00:08,66.0,,105,24.0,34.0,20.0,8.0,957,Distributed Computing for AI Made Simple.,5.0,18,True,2020-07-09 03:28:28.000,0.2.1,6.0,fiber,,,,,32.0,31.0,https://pypi.org/project/fiber,2020-07-09 03:28:28.000,1.0,2039.0,2039.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +788,XAI,EthicalML/xai,interpretability,,https://github.com/EthicalML/xai,https://github.com/EthicalML/xai,MIT,2019-01-11 20:00:09.000,2021-10-30 06:35:19.000000,2021-10-30 06:30:12,91.0,,119,42.0,5.0,2.0,7.0,773,XAI - An eXplainability toolbox for machine learning.,3.0,18,True,2021-10-30 06:35:19.000,0.1.0,6.0,xai,,,,,18.0,12.0,https://pypi.org/project/xai,2021-10-30 06:33:26.000,6.0,236.0,236.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +789,pytorch2keras,gmalivenko/pytorch2keras,model-serialisation,,https://github.com/gmalivenko/pytorch2keras,https://github.com/gmalivenko/pytorch2keras,MIT,2017-11-16 20:21:43.000,2021-09-28 21:39:06.000000,2021-08-06 08:18:46,282.0,,128,14.0,21.0,53.0,67.0,773,PyTorch to Keras model convertor.,13.0,18,True,2020-05-14 10:03:56.000,0.2.4,23.0,pytorch2keras,,,,,29.0,28.0,https://pypi.org/project/pytorch2keras,2020-05-14 10:03:56.000,1.0,734.0,734.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +790,AutoGL,THUMNLab/AutoGL,graph,,https://github.com/THUMNLab/AutoGL,https://github.com/THUMNLab/AutoGL,Apache-2.0,2020-11-30 14:26:22.000,2022-02-01 15:23:32.000000,2021-12-31 09:00:41,567.0,207.0,80,28.0,75.0,5.0,13.0,765,An autoML framework & toolkit for machine learning on graphs.,13.0,18,True,2020-12-23 08:15:15.000,0.1.1,2.0,auto-graph-learning,,,,['pytorch'],,,https://pypi.org/project/auto-graph-learning,2020-12-23 08:05:25.000,,15.0,15.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +791,FinQuant,fmilthaler/FinQuant,financial-data,,https://github.com/fmilthaler/FinQuant,https://github.com/fmilthaler/FinQuant,MIT,2019-01-20 15:07:19.000,2021-04-05 00:03:18.000000,2020-05-03 16:12:29,469.0,,96,33.0,42.0,16.0,11.0,725,"A program for financial portfolio management, analysis and optimisation.",9.0,18,False,2020-05-03 16:19:19.000,0.2.2,6.0,FinQuant,,,,,26.0,26.0,https://pypi.org/project/FinQuant,2020-05-03 16:19:19.000,,340.0,340.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, +792,baikal,alegonz/baikal,others,,https://github.com/alegonz/baikal,https://github.com/alegonz/baikal,BSD-3-Clause,2019-01-21 12:59:02.000,2021-12-13 20:33:34.000000,2021-04-11 07:50:00,405.0,,29,20.0,38.0,6.0,14.0,592,A graph-based functional API for building complex scikit-learn pipelines.,2.0,18,True,2020-11-15 13:40:18.000,0.4.2,8.0,baikal,conda-forge/cython-blis,,,,4.0,3.0,https://pypi.org/project/baikal,2020-11-15 13:40:18.000,1.0,659.0,34462.0,https://anaconda.org/conda-forge/cython-blis,2021-11-04 20:09:22.632,1183126.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +793,Caer,jasmcaus/caer,image,,https://github.com/jasmcaus/caer,https://github.com/jasmcaus/caer,MIT,2020-08-06 18:36:14.000,2021-10-13 21:04:50.000000,2021-10-13 21:05:33,5078.0,,101,18.0,57.0,2.0,13.0,591,"A lightweight Computer Vision library. Scale your models, not boilerplate.",8.0,18,True,2021-10-13 21:04:12.000,2.0.8,119.0,caer,,,https://caer.rtfd.io,,1.0,,https://pypi.org/project/caer,2021-10-13 21:04:12.000,1.0,3991.0,3992.0,,,,,,,,3.0,19.0,,,,,,,,,,,,,,,,,,,, +794,Auto Tune Models,HDI-Project/ATM,hyperopt,,https://github.com/HDI-Project/ATM,https://github.com/HDI-Project/ATM,MIT,2016-10-14 18:03:00.000,2020-02-21 17:44:07.000000,2020-02-21 17:40:58,775.0,,128,60.0,72.0,17.0,71.0,514,"Auto Tune Models - A multi-tenant, multi-data system for automated machine learning (model selection and tuning).",16.0,18,False,2019-07-30 09:28:26.000,0.2.2,14.0,atm,,,,,10.0,10.0,https://pypi.org/project/atm,2019-07-30 09:25:11.000,,79.0,79.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +795,N2,kakao/n2,nn-search,,https://github.com/kakao/n2,https://github.com/kakao/n2,Apache-2.0,2017-11-23 02:27:59.000,2021-05-20 05:41:36.000000,2021-05-20 05:39:44,264.0,,61,38.0,16.0,17.0,20.0,506,TOROS N2 - lightweight approximate Nearest Neighbor library which runs fast even with large datasets.,18.0,18,True,2020-10-16 03:43:47.000,0.1.7,9.0,n2,,,,,25.0,22.0,https://pypi.org/project/n2,2020-10-16 03:10:01.000,3.0,708.0,708.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +796,kale,kubeflow-kale/kale,data-pipelines,,https://github.com/kubeflow-kale/kale,https://github.com/kubeflow-kale/kale,Apache-2.0,2019-01-24 17:58:44.000,2022-02-10 02:26:14.000000,2021-10-20 12:44:09,644.0,,94,16.0,255.0,83.0,72.0,483,Kubeflows superfood for Data Scientists.,10.0,18,True,2021-05-19 12:56:53.000,0.7.0,15.0,kubeflow-kale,,,,['jupyter'],,,https://pypi.org/project/kubeflow-kale,2021-05-19 12:56:53.000,,1118.0,1118.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +797,parallelformers,tunib-ai/parallelformers,distributed-ml,,https://github.com/tunib-ai/parallelformers,https://github.com/tunib-ai/parallelformers,Apache-2.0,2021-07-17 12:50:43.000,2021-12-29 21:48:48.000000,2021-12-29 21:46:44,80.0,18.0,23,10.0,6.0,3.0,9.0,436,Parallelformers: An Efficient Model Parallelization Toolkit for Deployment.,3.0,18,True,2021-12-29 21:48:48.000,1.2.4,16.0,parallelformers,,,,,3.0,3.0,https://pypi.org/project/parallelformers,2021-12-29 21:47:16.000,,221.0,221.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, +798,BioPandas,rasbt/biopandas,others,,https://github.com/rasbt/biopandas,https://github.com/rasbt/biopandas,BSD-3-Clause,2015-11-21 00:00:14.000,2022-01-04 15:52:57.000000,2022-01-04 15:52:45,167.0,1.0,90,14.0,50.0,15.0,24.0,407,Working with molecular structures in pandas DataFrames.,8.0,18,True,2021-08-30 11:52:40.000,0.2.9,14.0,biopandas,conda-forge/biopandas,,,['pandas'],9.0,,https://pypi.org/project/biopandas,2021-09-24 00:14:13.000,9.0,2503.0,4045.0,https://anaconda.org/conda-forge/biopandas,2021-08-31 18:19:35.536,95659.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +799,datmo,datmo/datmo,ml-experiments,,https://github.com/datmo/datmo,https://github.com/datmo/datmo,MIT,2017-11-03 05:46:43.000,2022-01-06 22:27:34.000000,2019-11-29 00:48:44,1051.0,,27,10.0,120.0,42.0,149.0,339,Open source production model management tool for data scientists.,6.0,18,False,2018-12-07 06:16:42.000,0.0.40,41.0,datmo,,,,,5.0,5.0,https://pypi.org/project/datmo,2018-12-07 06:16:42.000,,109.0,109.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +800,recmetrics,statisticianinstilettos/recmetrics,recommender-systems,,https://github.com/statisticianinstilettos/recmetrics,https://github.com/statisticianinstilettos/recmetrics,MIT,2018-10-15 15:29:49.000,2021-10-27 14:22:31.000000,2021-10-27 14:16:34,237.0,,79,10.0,20.0,7.0,10.0,339,A library of metrics for evaluating recommender systems.,13.0,18,True,2021-09-24 21:30:26.000,0.1.0,15.0,recmetrics,,,,,22.0,22.0,https://pypi.org/project/recmetrics,2021-09-24 21:30:26.000,,1037.0,1037.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +801,TextBox,RUCAIBox/TextBox,nlp,,https://github.com/RUCAIBox/TextBox,https://github.com/RUCAIBox/TextBox,MIT,2020-11-08 07:35:46.000,2022-02-08 13:15:36.000000,2022-02-08 13:15:36,730.0,71.0,58,10.0,159.0,3.0,15.0,336,TextBox is an open-source library for building text generation system.,13.0,18,True,2021-04-15 13:39:28.000,0.2.1,10.0,textbox,,,,,5.0,5.0,https://pypi.org/project/textbox,2021-04-15 09:35:06.000,,46.0,46.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +802,elegy,poets-ai/elegy,ml-frameworks,,https://github.com/poets-ai/elegy,https://github.com/poets-ai/elegy,MIT,2020-06-30 14:00:37.000,2021-12-14 13:57:24.000000,2021-12-14 13:55:52,324.0,6.0,21,11.0,134.0,22.0,63.0,316,A High Level API for Deep Learning in JAX.,14.0,18,True,2021-12-14 13:57:24.000,0.8.4,28.0,elegy,,,,"['tensorflow', 'jax']",,,https://pypi.org/project/elegy,2021-12-14 13:56:14.000,,167.0,167.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +803,Sherpa,sherpa-ai/sherpa,hyperopt,,https://github.com/sherpa-ai/sherpa,https://github.com/sherpa-ai/sherpa,GPL-3.0,2018-05-16 21:41:54.000,2020-10-18 07:57:50.000000,2020-10-18 07:57:48,823.0,,48,11.0,60.0,15.0,41.0,308,"Hyperparameter optimization that enables researchers to experiment, visualize, and scale quickly.",43.0,18,False,2020-07-31 05:29:09.000,1.0.7,8.0,parameter-sherpa,,,,,19.0,17.0,https://pypi.org/project/parameter-sherpa,2019-11-23 21:32:27.000,2.0,346.0,346.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +804,pandas-ml,pandas-ml/pandas-ml,others,,https://github.com/pandas-ml/pandas-ml,https://github.com/pandas-ml/pandas-ml,BSD-3-Clause,2015-02-21 03:14:04.000,2020-08-14 12:29:33.000000,2019-03-05 01:36:55,153.0,,62,20.0,93.0,23.0,18.0,282,"pandas, scikit-learn, xgboost and seaborn integration.",4.0,18,False,2019-03-05 01:36:12.000,0.6.1,9.0,pandas-ml,,,,"['sklearn', 'pandas']",11.0,,https://pypi.org/project/pandas-ml,2019-03-05 01:35:23.000,11.0,4348.0,4348.0,,,,,,,,3.0,5.0,,,,,,,,,,,,,,,,,,,, +805,equinox,patrick-kidger/equinox,jax-utils,,https://github.com/patrick-kidger/equinox,https://github.com/patrick-kidger/equinox,Apache-2.0,2021-07-29 02:21:39.000,2022-02-09 23:14:00.000000,2022-02-09 23:13:58,147.0,62.0,15,11.0,20.0,5.0,5.0,264,Callable PyTrees and filtered JIT/grad transformations = neural networks in JAX.,4.0,18,False,2022-02-09 22:07:23.000,0.1.6,10.0,equinox,,,,['jax'],6.0,5.0,https://pypi.org/project/equinox,2022-02-09 22:07:23.000,1.0,384.0,384.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,,True, +806,ivis,beringresearch/ivis,data-viz,,https://github.com/beringresearch/ivis,https://github.com/beringresearch/ivis,Apache-2.0,2018-08-13 08:31:01.000,2021-11-08 17:08:45.000000,2021-11-08 17:08:42,611.0,,27,12.0,57.0,3.0,50.0,256,Dimensionality reduction in very large datasets using Siamese Networks.,10.0,18,False,2021-10-17 09:48:21.000,2.06,32.0,ivis,,,,['tensorflow'],21.0,20.0,https://pypi.org/project/ivis,2021-10-17 09:46:36.000,1.0,654.0,654.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +807,model-card-toolkit,tensorflow/model-card-toolkit,interpretability,,https://github.com/tensorflow/model-card-toolkit,https://github.com/tensorflow/model-card-toolkit,Apache-2.0,2020-07-24 16:48:58.000,2022-02-09 19:31:56.000000,2022-02-09 19:31:48,195.0,40.0,42,11.0,181.0,13.0,2.0,253,a tool that leverages rich metadata and lineage information in MLMD to build a model card.,12.0,18,False,2022-01-06 17:29:20.000,1.2.0,7.0,model-card-toolkit,,,,,6.0,6.0,https://pypi.org/project/model-card-toolkit,2022-01-04 18:19:01.000,,309.0,309.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +808,Julius,adefossez/julius,audio,,https://github.com/adefossez/julius,https://github.com/adefossez/julius,MIT,2020-10-26 10:54:21.000,2022-01-28 09:28:20.000000,2022-01-28 09:27:02,66.0,1.0,13,8.0,8.0,2.0,9.0,250,Fast PyTorch based DSP for audio and 1D signals.,2.0,18,False,2021-10-20 08:30:11.000,0.2.6,10.0,julius,,,,['pytorch'],64.0,60.0,https://pypi.org/project/julius,2021-10-20 08:30:11.000,4.0,10827.0,10827.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +809,fairness-indicators,tensorflow/fairness-indicators,interpretability,,https://github.com/tensorflow/fairness-indicators,https://github.com/tensorflow/fairness-indicators,Apache-2.0,2019-09-30 22:56:45.000,2022-02-02 23:21:42.000000,2022-02-02 19:52:59,281.0,4.0,66,19.0,272.0,12.0,8.0,240,Tensorflows Fairness Evaluation and Visualization Toolkit.,25.0,18,False,2022-02-02 23:21:42.000,0.37.0,23.0,fairness-indicators,,,,"['tensorflow', 'jupyter']",,,https://pypi.org/project/fairness-indicators,2022-02-02 23:21:42.000,,794.0,794.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +810,skift,shaypal5/skift,nlp,,https://github.com/shaypal5/skift,https://github.com/shaypal5/skift,MIT,2018-02-03 11:37:21.000,2022-01-20 08:55:59.000000,2022-01-20 08:44:25,137.0,8.0,23,10.0,7.0,2.0,9.0,226,scikit-learn wrappers for Python fastText.,9.0,18,False,2022-01-20 08:56:38.000,0.0.22,17.0,skift,,,,['sklearn'],11.0,11.0,https://pypi.org/project/skift,2022-01-20 08:55:59.000,,648.0,648.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +811,featurewiz,AutoViML/featurewiz,hyperopt,,https://github.com/AutoViML/featurewiz,https://github.com/AutoViML/featurewiz,Apache-2.0,2020-11-29 16:46:16.000,2022-01-30 03:45:07.000000,2022-01-30 03:44:10,155.0,37.0,35,1.0,1.0,3.0,13.0,146,Use advanced feature engineering strategies and select best features from your data set with a single line of code.,3.0,18,False,2022-01-28 03:44:08.000,0.0.90,68.0,featurewiz,,,,,5.0,4.0,https://pypi.org/project/featurewiz,2022-01-30 03:45:07.000,1.0,3533.0,3533.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +812,celer,mathurinm/celer,sklearn-utils,,https://github.com/mathurinm/celer,https://github.com/mathurinm/celer,BSD-3-Clause,2018-02-20 19:37:31.000,2021-12-10 09:56:59.000000,2021-12-10 09:44:45,228.0,2.0,23,8.0,146.0,14.0,55.0,129,"Fast solver for L1-type problems: Lasso, sparse Logisitic regression, Group Lasso, weighted Lasso, Multitask Lasso, etc.",9.0,18,False,2021-10-28 09:58:28.000,0.6.1,11.0,celer,,,,['sklearn'],10.0,10.0,https://pypi.org/project/celer,2021-10-28 09:58:28.000,,285.0,285.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +813,Feature Engine,solegalli/feature_engine,others,,https://github.com/solegalli/feature_engine,https://github.com/solegalli/feature_engine,BSD-3-Clause,2020-08-06 19:43:35.639,2022-01-04 17:54:20.182000,2021-08-06 12:03:40,126.0,,5,1.0,1.0,,,12,Feature engineering package with sklearn like functionality.,24.0,18,False,2022-01-04 14:15:17.000,1.2.0,29.0,feature_engine,conda-forge/feature_engine,,,,34.0,,https://pypi.org/project/feature_engine,2022-01-04 14:15:17.000,34.0,89189.0,89595.0,https://anaconda.org/conda-forge/feature_engine,2022-01-04 17:54:20.182,7317.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +814,OpenNRE,thunlp/OpenNRE,nlp,,https://github.com/thunlp/OpenNRE,https://github.com/thunlp/OpenNRE,MIT,2017-02-26 07:37:12.000,2021-12-09 19:53:22.000000,2021-12-09 19:53:22,161.0,3.0,916,122.0,20.0,21.0,321.0,3488,An Open-Source Package for Neural Relation Extraction (NRE).,10.0,17,True,,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +815,Mara Pipelines,mara/mara-pipelines,data-pipelines,,https://github.com/mara/mara-pipelines,https://github.com/mara/mara-pipelines,MIT,2018-03-31 20:37:22.000,2021-10-27 08:01:17.000000,2021-09-18 06:45:18,141.0,,86,58.0,46.0,11.0,13.0,1859,"A lightweight opinionated ETL framework, halfway between plain scripts and Apache Airflow.",16.0,17,True,2021-01-23 22:34:03.000,3.1.2,7.0,mara-pipelines,,,,,8.0,8.0,https://pypi.org/project/mara-pipelines,2021-01-23 22:34:03.000,,254.0,254.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +816,Advisor,tobegit3hub/advisor,hyperopt,,https://github.com/tobegit3hub/advisor,https://github.com/tobegit3hub/advisor,Apache-2.0,2017-09-14 03:50:33.000,2019-11-11 07:09:57.869705,2019-11-11 06:59:31,165.0,,256,51.0,13.0,20.0,13.0,1432,Open-source implementation of Google Vizier for hyper parameters tuning.,11.0,17,False,2018-10-18 02:54:09.000,0.1.6,4.0,advisor,,tobegit3hub/advisor,,,,,https://pypi.org/project/advisor,2018-10-18 02:54:09.000,,50.0,81.0,,,,https://hub.docker.com/r/tobegit3hub/advisor,2019-11-11 07:09:57.869705,,1650.0,3.0,,,,,,,,,,,,,,,,,,,,, +817,Bounter,RaRe-Technologies/bounter,data-containers,,https://github.com/RaRe-Technologies/bounter,https://github.com/RaRe-Technologies/bounter,MIT,2017-07-18 07:24:15.000,2021-09-19 00:43:46.000000,2021-05-24 07:29:54,156.0,,48,21.0,27.0,15.0,9.0,930,Efficient Counter that uses a limited (bounded) amount of memory regardless of data size.,8.0,17,True,2020-08-17 06:37:51.000,1.1.1,7.0,bounter,,,,,33.0,25.0,https://pypi.org/project/bounter,2020-08-17 06:37:51.000,8.0,110.0,110.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +818,Tez,abhishekkrthakur/tez,pytorch-utils,,https://github.com/abhishekkrthakur/tez,https://github.com/abhishekkrthakur/tez,Apache-2.0,2020-11-13 10:19:22.000,2022-01-12 16:54:01.000000,2021-12-28 11:56:11,85.0,1.0,110,11.0,5.0,18.0,10.0,774,Tez is a super-simple and lightweight Trainer for PyTorch. It also comes with many utils that you can use to tackle..,1.0,17,True,2021-12-28 11:56:53.000,0.2.0,14.0,tez,,,,['pytorch'],21.0,19.0,https://pypi.org/project/tez,2021-12-28 11:56:53.000,2.0,2447.0,2447.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +819,scenic,google-research/scenic,image,,https://github.com/google-research/scenic,https://github.com/google-research/scenic,Apache-2.0,2021-07-12 14:27:08.000,2022-02-09 10:00:37.000000,2022-02-09 10:00:32,178.0,85.0,74,24.0,186.0,4.0,15.0,716,Scenic: A Jax Library for Computer Vision Research and Beyond.,24.0,17,True,,,,,,,,['jax'],9.0,9.0,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, +820,robustness,MadryLab/robustness,adversarial,,https://github.com/MadryLab/robustness,https://github.com/MadryLab/robustness,MIT,2019-08-21 09:26:33.000,2022-01-09 12:27:01.000000,2021-11-30 00:11:07,141.0,2.0,124,16.0,39.0,15.0,55.0,662,"A library for experimenting with, training and evaluating neural networks, with a focus on adversarial robustness.",13.0,17,True,2020-12-01 06:11:12.000,1.2.1.post2,10.0,robustness,conda-forge/robustness,,,,71.0,69.0,https://pypi.org/project/robustness,2020-12-01 06:21:33.000,2.0,437.0,616.0,https://anaconda.org/conda-forge/robustness,2021-04-30 19:03:43.367,3234.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +821,nboost,koursaros-ai/nboost,nlp,,https://github.com/koursaros-ai/nboost,https://github.com/koursaros-ai/nboost,Apache-2.0,2019-10-29 20:56:24.000,2020-09-30 14:51:16.000000,2020-07-16 19:48:25,1336.0,,64,19.0,21.0,29.0,50.0,609,"NBoost is a scalable, search-api-boosting platform for deploying transformer models to improve the relevance of search..",10.0,17,False,2020-06-12 20:05:15.000,0.3.9,26.0,nboost,,,,,3.0,3.0,https://pypi.org/project/nboost,2020-06-12 20:05:15.000,,119.0,119.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +822,animatplot,t-makaro/animatplot,data-viz,,https://github.com/t-makaro/animatplot,https://github.com/t-makaro/animatplot,MIT,2017-04-03 00:54:04.000,2021-04-07 10:46:25.000000,2020-10-05 06:14:18,178.0,,35,10.0,29.0,17.0,17.0,386,A python package for animating plots build on matplotlib.,7.0,17,False,2020-10-05 06:20:52.000,0.4.2,10.0,animatplot,conda-forge/animatplot,,,,32.0,30.0,https://pypi.org/project/animatplot,2020-10-05 06:20:52.000,2.0,268.0,474.0,https://anaconda.org/conda-forge/animatplot,2020-10-06 02:02:00.460,7436.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +823,Case Recommender,caserec/CaseRecommender,recommender-systems,,https://github.com/caserec/CaseRecommender,https://github.com/caserec/CaseRecommender,MIT,2015-11-12 18:25:39.000,2021-11-25 23:19:05.000000,2021-11-25 23:08:43,204.0,1.0,77,23.0,18.0,7.0,20.0,382,Case Recommender: A Flexible and Extensible Python Framework for Recommender Systems.,11.0,17,True,2021-11-25 23:19:05.000,1.1.1,42.0,caserecommender,,,,['sklearn'],9.0,9.0,https://pypi.org/project/caserecommender,2021-11-25 23:19:05.000,,352.0,352.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +824,Sematch,gsi-upm/sematch,graph,,https://github.com/gsi-upm/sematch,https://github.com/gsi-upm/sematch,Apache-2.0,2012-11-30 11:11:53.000,2020-11-05 21:20:52.000000,2019-03-27 03:17:24,122.0,,101,71.0,5.0,14.0,19.0,375,semantic similarity framework for knowledge graph.,5.0,17,False,2017-04-17 10:56:52.000,1.0.4,5.0,sematch,,,,,35.0,32.0,https://pypi.org/project/sematch,2017-04-17 10:56:52.000,3.0,240.0,240.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +825,Pywick,achaiah/pywick,pytorch-utils,,https://github.com/achaiah/pywick,https://github.com/achaiah/pywick,MIT,2019-03-25 15:42:47.000,2022-02-04 15:57:11.000000,2021-10-22 03:09:17,149.0,,38,15.0,39.0,2.0,12.0,366,High-level batteries-included neural network training library for Pytorch.,4.0,17,True,2021-10-22 03:19:11.000,0.6.5,8.0,pywick,,,,['pytorch'],5.0,5.0,https://pypi.org/project/pywick,2021-10-22 03:19:11.000,,60.0,60.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +826,scikit-tda,scikit-tda/scikit-tda,sklearn-utils,,https://github.com/scikit-tda/scikit-tda,https://github.com/scikit-tda/scikit-tda,MIT,2018-04-13 21:00:31.000,2021-10-01 15:05:45.000000,2021-08-03 00:21:54,60.0,,40,14.0,5.0,13.0,4.0,332,Topological Data Analysis for Python.,3.0,17,True,2021-08-03 00:23:20.000,1.0.0,4.0,scikit-tda,,,,['sklearn'],25.0,25.0,https://pypi.org/project/scikit-tda,2021-08-03 00:23:20.000,,4970.0,4970.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +827,bodywork-core,bodywork-ml/bodywork-core,data-pipelines,,https://github.com/bodywork-ml/bodywork-core,https://github.com/bodywork-ml/bodywork-core,AGPL-3.0,2020-11-17 11:38:17.000,2022-01-18 03:27:32.000000,2022-01-18 02:57:09,789.0,36.0,16,9.0,102.0,7.0,48.0,319,"ML pipeline orchestration and model deployments on Kubernetes, made really easy.",4.0,17,False,2021-07-05 08:15:59.000,2.1.7,46.0,bodywork,,,,,9.0,9.0,https://pypi.org/project/bodywork,2021-12-24 12:53:14.000,,280.0,280.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +828,solt,MIPT-Oulu/solt,image,,https://github.com/Oulu-IMEDS/solt,https://github.com/Oulu-IMEDS/solt,MIT,2018-08-02 15:09:05.000,2021-10-12 22:58:52.000000,2020-04-09 06:44:39,336.0,,19,7.0,30.0,17.0,30.0,253,Streaming over lightweight data transformations.,4.0,17,False,2020-03-10 14:09:31.000,0.1.9,18.0,solt,,,,,28.0,25.0,https://pypi.org/project/solt,2020-03-10 14:09:31.000,3.0,179.0,179.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,Oulu-IMEDS/solt +829,textaugment,dsfsi/textaugment,nlp,,https://github.com/dsfsi/textaugment,https://github.com/dsfsi/textaugment,MIT,2019-05-06 12:28:19.000,2021-09-15 07:35:53.000000,2021-09-15 07:35:53,60.0,,37,5.0,4.0,10.0,13.0,210,TextAugment: Text Augmentation Library.,5.0,17,False,2020-11-05 15:04:26.000,1.3.4,8.0,textaugment,,,,,12.0,12.0,https://pypi.org/project/textaugment,2020-11-05 15:02:11.000,,2791.0,2792.0,,,,,,,,3.0,53.0,,,,,,,,,,,,,,,,,,,, +830,skggm,skggm/skggm,sklearn-utils,,https://github.com/skggm/skggm,https://github.com/skggm/skggm,MIT,2016-06-11 18:35:56.000,2021-10-01 04:11:05.000000,2020-12-24 05:43:15,701.0,,34,9.0,58.0,28.0,47.0,192,Scikit-learn compatible estimation of general graphical models.,5.0,17,False,2018-09-12 01:12:49.000,0.2.8,6.0,skggm,,,,['sklearn'],10.0,8.0,https://pypi.org/project/skggm,2018-09-12 01:12:49.000,2.0,59.0,59.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +831,nx-altair,Zsailer/nx_altair,data-viz,,https://github.com/Zsailer/nx_altair,https://github.com/Zsailer/nx_altair,MIT,2018-05-13 00:10:12.000,2022-01-08 12:10:11.000000,2020-06-02 21:10:26,51.0,,23,11.0,14.0,6.0,4.0,187,Draw interactive NetworkX graphs with Altair.,3.0,17,False,2020-06-02 21:11:12.000,0.1.6,8.0,nx-altair,,,,['jupyter'],3.0,,https://pypi.org/project/nx-altair,2020-06-02 21:11:12.000,3.0,2806.0,2806.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +832,flupy,olirice/flupy,data-pipelines,,https://github.com/olirice/flupy,https://github.com/olirice/flupy,MIT,2018-01-06 16:46:04.000,2021-11-05 17:01:59.000000,2021-11-05 17:01:56,195.0,,12,8.0,13.0,3.0,9.0,170,Fluent data pipelines for python and your shell.,6.0,17,False,2021-10-15 12:35:59.000,1.1.9,37.0,flupy,,,,,1.0,,https://pypi.org/project/flupy,2021-10-15 12:35:59.000,1.0,51693.0,51693.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +833,mesh-transformer-jax,kingoflolz/mesh-transformer-jax,distributed-ml,,https://github.com/kingoflolz/mesh-transformer-jax,https://github.com/kingoflolz/mesh-transformer-jax,Apache-2.0,2021-03-13 23:31:13.000,2022-01-28 07:38:06.000000,2022-01-28 07:38:03,142.0,8.0,465,67.0,48.0,11.0,132.0,3817,Model parallel transformers in JAX and Haiku.,23.0,16,True,,,,,,,,['jax'],,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, +834,Euler,alibaba/euler,graph,,https://github.com/alibaba/euler,https://github.com/alibaba/euler,Apache-2.0,2019-01-10 06:32:32.000,2021-12-30 02:31:11.000000,2020-07-29 05:53:01,8.0,,546,138.0,25.0,214.0,102.0,2724,A distributed graph deep learning framework.,5.0,16,False,2020-07-07 02:24:18.000,2.0.0,2.0,euler-gl,,,,['tensorflow'],,,https://pypi.org/project/euler-gl,2019-04-10 01:53:45.000,,11.0,11.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +835,GraphEmbedding,shenweichen/GraphEmbedding,graph,,https://github.com/shenweichen/GraphEmbedding,https://github.com/shenweichen/GraphEmbedding,MIT,2019-02-11 16:27:20.000,2022-01-06 09:34:21.000000,2020-10-18 09:32:47,28.0,,764,51.0,10.0,39.0,14.0,2559,Implementation and experiments of graph embedding algorithms.,8.0,16,False,,,,,,,,['sklearn'],15.0,15.0,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +836,Xcessiv,reiinakano/xcessiv,hyperopt,,https://github.com/reiinakano/xcessiv,https://github.com/reiinakano/xcessiv,Apache-2.0,2017-03-07 18:18:25.000,2018-06-06 22:23:37.000000,2017-08-21 00:51:15,316.0,,109,54.0,34.0,22.0,13.0,1263,"A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python.",6.0,16,False,2017-08-21 00:53:25.000,0.5.1,34.0,xcessiv,,,,,2.0,1.0,https://pypi.org/project/xcessiv,2017-08-21 00:49:41.000,1.0,90.0,90.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +837,MedicalTorch,perone/medicaltorch,medical-data,,https://github.com/perone/medicaltorch,https://github.com/perone/medicaltorch,Apache-2.0,2018-02-27 02:50:07.000,2021-12-04 23:52:48.000000,2021-04-16 18:50:54,57.0,,113,49.0,19.0,14.0,9.0,760,A medical imaging framework for Pytorch.,8.0,16,True,2018-11-24 00:33:11.000,0.2,2.0,medicaltorch,,,,['pytorch'],11.0,11.0,https://pypi.org/project/medicaltorch,2018-11-24 00:29:36.000,,119.0,119.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +838,HyperparameterHunter,HunterMcGushion/hyperparameter_hunter,hyperopt,,https://github.com/HunterMcGushion/hyperparameter_hunter,https://github.com/HunterMcGushion/hyperparameter_hunter,MIT,2018-06-01 23:17:00.000,2021-01-20 03:52:41.000000,2021-01-20 03:52:40,1096.0,,87,25.0,101.0,37.0,84.0,682,Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries.,4.0,16,False,2019-08-06 09:09:45.000,3.0.0,16.0,hyperparameter-hunter,,,,,2.0,,https://pypi.org/project/hyperparameter-hunter,2019-08-06 08:52:20.000,2.0,47.0,55.0,,,,,,,,3.0,329.0,,,,,,,,,,,,,,,,,,,, +839,ThunderGBM,Xtra-Computing/thundergbm,ml-frameworks,,https://github.com/Xtra-Computing/thundergbm,https://github.com/Xtra-Computing/thundergbm,Apache-2.0,2016-11-11 09:58:08.000,2021-11-23 01:55:15.000000,2021-01-05 04:22:15,606.0,,81,25.0,4.0,36.0,36.0,618,ThunderGBM: Fast GBDTs and Random Forests on GPUs.,10.0,16,False,2020-05-01 23:16:25.000,0.3.16,24.0,thundergbm,,,,,,,https://pypi.org/project/thundergbm,2020-05-01 23:16:25.000,,141.0,141.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +840,kglib,vaticle/kglib,graph,,https://github.com/vaticle/kglib,https://github.com/vaticle/kglib,Apache-2.0,2018-09-16 16:46:48.000,2021-10-22 14:09:11.000000,2021-10-22 14:09:00,488.0,,86,34.0,98.0,12.0,49.0,494,Grakn Knowledge Graph Library (ML R&D).,7.0,16,True,2020-08-19 15:39:10.000,0.2.2,7.0,grakn-kglib,,,,,,,https://pypi.org/project/grakn-kglib,2020-08-19 15:39:10.000,,90.0,95.0,,,,,,,,3.0,211.0,,,,,,,,,,,,,,,,,,,, +841,LOFO,aerdem4/lofo-importance,interpretability,,https://github.com/aerdem4/lofo-importance,https://github.com/aerdem4/lofo-importance,MIT,2019-01-14 10:46:46.000,2021-10-04 13:21:59.000000,2021-10-04 13:20:39,26.0,,52,14.0,26.0,5.0,13.0,436,Leave One Feature Out Importance.,3.0,16,True,2021-10-04 13:21:59.000,0.3.1,11.0,lofo-importance,,,,,7.0,7.0,https://pypi.org/project/lofo-importance,2021-10-04 13:21:59.000,,242.0,242.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +842,apricot,jmschrei/apricot,others,,https://github.com/jmschrei/apricot,https://github.com/jmschrei/apricot,MIT,2018-08-12 02:42:12.000,2021-11-18 21:06:56.000000,2021-11-18 21:06:54,172.0,1.0,40,8.0,8.0,6.0,18.0,404,apricot implements submodular optimization for the purpose of selecting subsets of massive data sets to train machine..,4.0,16,True,2020-09-28 07:19:15.000,0.6.0,13.0,apricot-select,,,,,25.0,22.0,https://pypi.org/project/apricot-select,2020-09-28 07:19:15.000,3.0,303.0,303.0,,,,,,,,3.0,10.0,,,,,,,,,,,,,,,,,,,, +843,OpenRec,ylongqi/openrec,recommender-systems,,https://github.com/ylongqi/openrec,https://github.com/ylongqi/openrec,Apache-2.0,2017-11-29 16:04:40.000,2022-02-09 23:36:33.000000,2020-02-19 07:57:17,213.0,,84,36.0,43.0,5.0,12.0,391,OpenRec is an open-source and modular library for neural network-inspired recommendation algorithms.,11.0,16,False,2020-02-18 06:52:11.000,0.3.0,12.0,openrec,,,,,2.0,1.0,https://pypi.org/project/openrec,2020-02-18 06:52:11.000,1.0,39.0,39.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +844,Adversary,airbnb/artificial-adversary,adversarial,,https://github.com/airbnb/artificial-adversary,https://github.com/airbnb/artificial-adversary,MIT,2018-08-08 04:42:11.000,2022-01-07 11:24:14.000000,2018-08-29 15:31:30,15.0,,51,21.0,6.0,6.0,,361,Tool to generate adversarial text examples and test machine learning models against them.,5.0,16,False,2018-08-29 15:14:41.000,1.1.1,3.0,Adversary,conda-forge/artificial-adversary,,,,7.0,6.0,https://pypi.org/project/Adversary,2018-08-29 15:14:41.000,1.0,30.0,156.0,https://anaconda.org/conda-forge/artificial-adversary,2021-04-30 19:05:10.636,2398.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +845,tfdeploy,riga/tfdeploy,model-serialisation,,https://github.com/riga/tfdeploy,https://github.com/riga/tfdeploy,BSD-3-Clause,2016-03-07 13:08:21.000,2021-01-08 09:52:54.000000,2021-01-08 09:52:49,170.0,,38,23.0,5.0,11.0,23.0,346,Deploy tensorflow graphs for fast evaluation and export to tensorflow-less environments running numpy.,4.0,16,False,2017-03-30 10:51:26.000,0.4.2,22.0,tfdeploy,,,,['tensorflow'],2.0,,https://pypi.org/project/tfdeploy,2017-03-30 10:51:26.000,2.0,78.0,78.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +846,Camphr,PKSHATechnology-Research/camphr,nlp,,https://github.com/PKSHATechnology-Research/camphr,https://github.com/PKSHATechnology-Research/camphr,Apache-2.0,2020-02-10 03:39:58.000,2021-08-18 06:06:52.000000,2021-08-18 06:06:51,1404.0,,17,5.0,215.0,2.0,26.0,345,Camphr - NLP libary for creating pipeline components.,7.0,16,True,2021-07-28 07:48:46.000,0.10.0,48.0,camphr,,,,['spacy'],2.0,,https://pypi.org/project/camphr,2021-07-28 07:48:46.000,2.0,233.0,233.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +847,pdvega,altair-viz/pdvega,data-viz,,https://github.com/altair-viz/pdvega,https://github.com/altair-viz/pdvega,MIT,2018-01-11 21:30:27.000,2019-03-29 16:09:14.000000,2019-03-29 16:09:13,177.0,,31,22.0,21.0,16.0,10.0,340,Interactive plotting for Pandas using Vega-Lite.,9.0,16,False,,,1.0,pdvega,,,,,71.0,64.0,https://pypi.org/project/pdvega,2018-02-01 04:56:43.000,7.0,121.0,121.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +848,ptgnn,microsoft/ptgnn,graph,,https://github.com/microsoft/ptgnn,https://github.com/microsoft/ptgnn,MIT,2020-05-12 08:42:30.000,2022-02-01 17:31:29.000000,2022-02-01 17:31:29,99.0,5.0,36,10.0,17.0,2.0,5.0,305,A PyTorch Graph Neural Network Library.,7.0,16,True,2021-10-21 21:43:04.000,0.10.4,18.0,ptgnn,,,,['pytorch'],1.0,1.0,https://pypi.org/project/ptgnn,2021-10-21 21:43:04.000,,149.0,149.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, +849,data-describe,data-describe/data-describe,data-viz,,https://github.com/data-describe/data-describe,https://github.com/data-describe/data-describe,Apache-2.0,2020-05-04 17:58:14.000,2022-02-07 05:05:16.000000,2021-11-19 06:05:15,700.0,5.0,15,14.0,237.0,69.0,175.0,289,datadescribe: Pythonic EDA Accelerator for Data Science.,14.0,16,False,,,5.0,data-describe,,,,,,,https://pypi.org/project/data-describe,2020-12-03 23:07:43.000,,283.0,283.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +850,DeepGraph,deepgraph/deepgraph,graph,,https://github.com/deepgraph/deepgraph,https://github.com/deepgraph/deepgraph,BSD-3-Clause,2015-10-27 12:28:45.000,2021-11-08 16:53:47.290000,2021-06-14 10:58:10,162.0,,36,17.0,1.0,9.0,5.0,248,Analyze Data with Pandas-based Networks. Documentation:.,2.0,16,False,2020-10-01 13:20:38.000,0.2.3,13.0,deepgraph,conda-forge/deepgraph,,,['pandas'],3.0,3.0,https://pypi.org/project/deepgraph,2020-10-01 13:18:38.000,,138.0,2309.0,https://anaconda.org/conda-forge/deepgraph,2021-11-08 16:53:47.290,117242.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +851,NeuralCompression,facebookresearch/NeuralCompression,others,,https://github.com/facebookresearch/NeuralCompression,https://github.com/facebookresearch/NeuralCompression,MIT,2021-07-09 15:14:13.000,2022-02-09 16:41:19.000000,2022-02-09 16:41:15,92.0,28.0,16,12.0,120.0,18.0,44.0,235,A collection of tools for neural compression enthusiasts.,3.0,16,False,2022-01-12 14:55:21.000,0.2.1,3.0,neuralcompression,,,,,,,https://pypi.org/project/neuralcompression,2022-01-12 14:55:21.000,,101.0,101.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, +852,Maze,enlite-ai/maze,reinforcement-learning,,https://github.com/enlite-ai/maze,https://github.com/enlite-ai/maze,Custom,2021-02-11 08:26:37.000,2022-01-27 01:28:07.000000,2021-12-13 15:30:15,947.0,515.0,5,7.0,24.0,1.0,2.0,202,Maze Applied Reinforcement Learning Framework.,3.0,16,False,2021-12-13 16:04:42.000,0.1.8,20.0,maze-rl,,enliteai/maze,,['pytorch'],1.0,1.0,https://pypi.org/project/maze-rl,2021-12-13 16:04:42.000,,82.0,101.0,,,,https://hub.docker.com/r/enliteai/maze,2021-06-24 21:00:27.801118,,236.0,3.0,,,,,,,,,,,,,,,,,,,,, +853,ipyexperiments,stas00/ipyexperiments,gpu-utilities,,https://github.com/stas00/ipyexperiments,https://github.com/stas00/ipyexperiments,Apache-2.0,2018-11-15 01:19:40.000,2021-12-07 18:50:39.000000,2021-12-07 18:50:38,203.0,6.0,10,6.0,2.0,1.0,5.0,144,jupyter/ipython experiment containers for GPU and general RAM re-use.,3.0,16,False,2021-12-07 18:44:34.000,0.1.28,24.0,ipyexperiments,,,,['jupyter'],7.0,5.0,https://pypi.org/project/ipyexperiments,2021-12-07 18:44:34.000,2.0,159.0,159.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +854,pyRDF2Vec,IBCNServices/pyRDF2Vec,graph,,https://github.com/IBCNServices/pyRDF2Vec,https://github.com/IBCNServices/pyRDF2Vec,MIT,2019-06-13 11:36:12.000,2022-02-04 19:54:24.000000,2022-02-04 19:53:46,1152.0,9.0,27,14.0,13.0,3.0,45.0,139,Python Implementation and Extension of RDF2Vec.,5.0,16,False,2021-06-09 10:56:14.000,0.2.3,11.0,pyrdf2vec,,,,,,,https://pypi.org/project/pyrdf2vec,2021-06-09 10:56:14.000,,139.0,139.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +855,steppy,minerva-ml/steppy,ml-experiments,,https://github.com/minerva-ml/steppy,https://github.com/minerva-ml/steppy,MIT,2018-01-15 09:40:49.000,2018-11-23 09:49:59.000000,2018-11-23 09:47:34,69.0,,33,14.0,54.0,16.0,50.0,132,"Lightweight, Python library for fast and reproducible experimentation.",5.0,16,False,2018-11-23 09:49:59.000,0.1.16,16.0,steppy,,,,,47.0,42.0,https://pypi.org/project/steppy,2018-11-23 09:49:59.000,5.0,71.0,71.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +856,StarSpace,facebookresearch/StarSpace,ml-frameworks,,https://github.com/facebookresearch/StarSpace,https://github.com/facebookresearch/StarSpace,MIT,2017-06-28 17:50:18.000,2021-11-03 16:23:46.000000,2019-12-13 19:03:25,138.0,,503,182.0,109.0,50.0,148.0,3719,"Learning embeddings for classification, retrieval and ranking.",17.0,15,False,,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +857,OpenKE,thunlp/OpenKE,graph,,https://github.com/thunlp/OpenKE,https://github.com/thunlp/OpenKE,MIT,2017-10-08 11:20:23.000,2021-09-29 09:46:39.000000,2021-04-06 08:24:50,113.0,,848,98.0,25.0,68.0,312.0,2900,An Open-Source Package for Knowledge Embedding (KE).,10.0,15,True,,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +858,GraphSAGE,williamleif/GraphSAGE,graph,,https://github.com/williamleif/GraphSAGE,https://github.com/williamleif/GraphSAGE,MIT,2017-05-29 15:36:22.000,2022-02-09 23:43:10.000000,2018-09-19 19:27:00,59.0,,727,74.0,26.0,96.0,59.0,2627,Representation learning on large graphs using stochastic graph convolutions.,9.0,15,False,,,,,,,,['tensorflow'],,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +859,ZhuSuan,thu-ml/zhusuan,probabilistics,,https://github.com/thu-ml/zhusuan,https://github.com/thu-ml/zhusuan,MIT,2016-07-18 13:31:38.000,2020-01-09 14:51:27.000000,2019-08-05 10:00:04,439.0,,404,144.0,70.0,8.0,53.0,2106,"A probabilistic programming library for Bayesian deep learning, generative models, based on Tensorflow.",20.0,15,False,,,,,,,,['tensorflow'],,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +860,micrograd,karpathy/micrograd,pytorch-utils,,https://github.com/karpathy/micrograd,https://github.com/karpathy/micrograd,MIT,2020-04-13 04:31:18.000,2021-06-24 12:28:13.000000,2020-04-18 19:15:25,24.0,,149,49.0,8.0,2.0,3.0,1884,A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API.,2.0,15,False,2020-04-18 19:06:59.000,0.1.0,1.0,micrograd,,,,['pytorch'],5.0,4.0,https://pypi.org/project/micrograd,2020-04-18 19:06:59.000,1.0,30.0,30.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +861,automl-gs,minimaxir/automl-gs,hyperopt,,https://github.com/minimaxir/automl-gs,https://github.com/minimaxir/automl-gs,MIT,2019-01-13 18:57:44.000,2019-10-22 11:20:40.000000,2019-04-05 06:48:14,102.0,,164,58.0,10.0,26.0,6.0,1769,"Provide an input CSV and a target field to predict, generate a model + code to run it.",7.0,15,False,2019-04-05 06:51:04.000,0.2.1,2.0,automl_gs,,,,,,,https://pypi.org/project/automl_gs,2019-04-05 06:47:54.000,,19.0,19.0,,,,,,,,3.0,27.0,,,,,,,,,,,,,,,,,,,, +862,OpenNE,thunlp/OpenNE,graph,,https://github.com/thunlp/OpenNE,https://github.com/thunlp/OpenNE,MIT,2017-10-08 04:58:20.000,2022-01-28 17:40:30.000000,2019-08-12 10:56:27,98.0,,468,66.0,23.0,50.0,94.0,1545,An Open-Source Package for Network Embedding (NE).,10.0,15,False,,,,,,,,['tensorflow'],,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +863,Botflow,kkyon/botflow,data-pipelines,,https://github.com/kkyon/botflow,https://github.com/kkyon/botflow,BSD-3-Clause,2018-08-20 03:13:31.000,2020-12-31 09:03:22.000000,2019-05-23 14:40:50,192.0,,101,55.0,28.0,2.0,2.0,1181,"Python Fast Dataflow programming framework for Data pipeline work( Web Crawler,Machine Learning,Quantitative..",11.0,15,False,2018-09-14 14:38:32.000,0.2.0,5.0,botflow,,,,,1.0,1.0,https://pypi.org/project/botflow,2018-09-14 14:38:32.000,,23.0,23.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +864,Translate,pytorch/translate,nlp,,https://github.com/pytorch/translate,https://github.com/pytorch/translate,BSD-3-Clause,2018-04-24 16:44:04.000,2021-10-06 18:21:48.000000,2021-10-06 18:21:42,810.0,,170,44.0,667.0,66.0,27.0,724,Translate - a PyTorch Language Library.,87.0,15,True,,,1.0,pytorch-translate,,,,['pytorch'],,,https://pypi.org/project/pytorch-translate,2018-05-01 19:59:40.000,,3.0,3.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +865,Anchor,marcotcr/anchor,interpretability,,https://github.com/marcotcr/anchor,https://github.com/marcotcr/anchor,BSD-2-Clause,2018-02-02 23:38:50.000,2021-11-17 21:38:50.000000,2021-11-17 21:38:50,45.0,1.0,95,24.0,10.0,18.0,51.0,682,Code for High-Precision Model-Agnostic Explanations paper.,10.0,15,True,,,8.0,anchor_exp,,,,,,,https://pypi.org/project/anchor_exp,2020-06-26 20:56:50.000,,1836.0,1836.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +866,SpeedTorch,Santosh-Gupta/SpeedTorch,gpu-utilities,,https://github.com/Santosh-Gupta/SpeedTorch,https://github.com/Santosh-Gupta/SpeedTorch,MIT,2019-09-07 18:57:52.000,2020-02-21 23:13:29.000000,2020-02-21 23:13:28,170.0,,39,26.0,4.0,4.0,2.0,647,Library for faster pinned CPU - GPU transfer in Pytorch.,3.0,15,False,2020-01-06 05:27:17.000,0.1.6,14.0,SpeedTorch,,,,['pytorch'],5.0,3.0,https://pypi.org/project/SpeedTorch,2020-01-06 05:27:17.000,2.0,94.0,94.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +867,FlashTorch,MisaOgura/flashtorch,interpretability,,https://github.com/MisaOgura/flashtorch,https://github.com/MisaOgura/flashtorch,MIT,2019-03-22 13:00:57.000,2021-06-30 12:46:02.000000,2021-04-27 11:10:20,127.0,,80,18.0,14.0,10.0,22.0,644,Visualization toolkit for neural networks in PyTorch! Demo --.,2.0,15,True,2020-05-29 14:39:38.000,0.1.3,12.0,flashtorch,,,,['pytorch'],9.0,9.0,https://pypi.org/project/flashtorch,2020-05-29 14:38:32.000,,477.0,477.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +868,interpret-text,interpretml/interpret-text,interpretability,,https://github.com/interpretml/interpret-text,https://github.com/interpretml/interpret-text,MIT,2019-09-04 16:39:48.000,2022-01-22 11:41:20.000000,2021-12-06 17:38:41,146.0,3.0,54,18.0,139.0,58.0,16.0,300,A library that incorporates state-of-the-art explainers for text-based machine learning models and visualizes the..,17.0,15,True,2021-12-07 15:12:02.000,0.1.3,5.0,interpret-text,,,,['jupyter'],,,https://pypi.org/project/interpret-text,2021-12-07 01:57:31.000,,91.0,91.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +869,ExplainX.ai,explainX/explainx,interpretability,,https://github.com/explainX/explainx,https://github.com/explainX/explainx,MIT,2020-06-16 14:27:15.000,2022-01-07 00:02:17.000000,2021-02-02 09:03:57,184.0,,39,8.0,12.0,10.0,17.0,287,Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line..,4.0,15,False,2021-02-07 11:06:21.000,2.407,56.0,explainx,,,,,,,https://pypi.org/project/explainx,2021-02-04 16:44:24.000,,853.0,853.0,,,,,,,,3.0,2.0,,,,,,,,,,,,,,,,,,,, +870,NeuralQA,victordibia/neuralqa,nlp,,https://github.com/victordibia/neuralqa,https://github.com/victordibia/neuralqa,MIT,2020-05-19 03:55:56.000,2022-02-10 02:02:04.000000,2020-12-16 17:41:37,312.0,,31,5.0,55.0,31.0,8.0,219,NeuralQA: A Usable Library for Question Answering on Large Datasets with BERT.,3.0,15,False,,,27.0,neuralqa,,,,,4.0,4.0,https://pypi.org/project/neuralqa,2020-09-18 17:54:50.000,,100.0,100.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +871,Parfit,jmcarpenter2/parfit,hyperopt,,https://github.com/jmcarpenter2/parfit,https://github.com/jmcarpenter2/parfit,MIT,2017-11-22 20:17:51.000,2020-04-04 19:26:44.000000,2020-04-04 19:26:37,127.0,,25,4.0,4.0,6.0,5.0,200,"A package for parallelizing the fit and flexibly scoring of sklearn machine learning models, with visualization..",2.0,15,False,,,23.0,parfit,,,,['sklearn'],9.0,9.0,https://pypi.org/project/parfit,2018-10-11 22:03:16.000,,20013.0,20013.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +872,dabl,amueller/dabl,sklearn-utils,,https://github.com/amueller/dabl,https://github.com/amueller/dabl,BSD-3-Clause,2020-01-30 18:26:49.000,2021-07-09 20:34:09.000000,2021-07-09 18:47:52,275.0,,9,3.0,3.0,1.0,,113,Data Analysis Baseline Library.,21.0,15,False,2021-07-09 19:20:43.000,0.2.2,12.0,dabl,,,,['sklearn'],,,https://pypi.org/project/dabl,2021-07-09 19:20:43.000,,2293.0,2293.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +873,nptsne,biovault/nptsne,data-viz,,https://github.com/biovault/nptsne,https://github.com/biovault/nptsne,Apache-2.0,2019-06-28 08:40:25.000,2021-12-23 19:59:24.000000,2021-02-03 08:52:27,857.0,,2,3.0,1.0,7.0,5.0,27,nptsne is a numpy compatible python binary package that offers a number of APIs for fast tSNE calculation.,3.0,15,False,2021-12-23 15:53:08.000,1.2.0,3.0,nptsne,,,,,3.0,3.0,https://pypi.org/project/nptsne,2021-12-23 15:53:08.000,,227.0,227.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +874,upgini,upgini/upgini,tabular,,https://github.com/upgini/upgini,https://github.com/upgini/upgini,BSD-3-Clause,2021-12-08 21:53:58.000,2022-02-09 22:48:05.000000,2022-02-09 22:43:30,77.0,77.0,3,1.0,23.0,1.0,,21,Automated feature discovery & enrichment library automatically find and enrich ML models with relevant external..,7.0,15,False,2021-12-03 01:26:10.000,0.9.0,50.0,upgini,,,,,,,https://pypi.org/project/upgini,2022-02-09 22:48:05.000,,1409.0,1409.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, +875,Torch Points 3D,nicolas-chaulet/torch-points3d,image,,https://github.com/nicolas-chaulet/torch-points3d,https://github.com/nicolas-chaulet/torch-points3d,BSD-3-Clause,2022-01-09 14:41:37.000,2021-12-10 20:17:18.000000,2021-12-10 20:17:18,1788.0,14.0,3,,,,,12,Pytorch framework for doing deep learning on point clouds.,29.0,15,False,2021-04-30 09:00:22.000,1.3.0,14.0,torch-points3d,,,,['pytorch'],,,https://pypi.org/project/torch-points3d,2021-04-30 09:00:22.000,,704.0,704.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +876,Medical Detection Toolkit,MIC-DKFZ/medicaldetectiontoolkit,medical-data,,https://github.com/MIC-DKFZ/medicaldetectiontoolkit,https://github.com/MIC-DKFZ/medicaldetectiontoolkit,Apache-2.0,2018-10-12 12:34:57.000,2022-01-13 05:17:27.000000,2021-09-09 14:14:04,40.0,,275,52.0,11.0,40.0,85.0,1087,"The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN,..",3.0,14,True,,,,,,,,['pytorch'],,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +877,GraphGym,snap-stanford/GraphGym,graph,,https://github.com/snap-stanford/GraphGym,https://github.com/snap-stanford/GraphGym,MIT,2020-10-14 05:01:35.000,2021-12-11 19:28:20.000000,2021-12-11 19:28:20,63.0,2.0,100,20.0,11.0,3.0,22.0,885,Platform for designing and evaluating Graph Neural Networks (GNN).,5.0,14,True,2021-06-29 06:03:18.000,0.3.1,2.0,graphgym,,,,,2.0,2.0,https://pypi.org/project/graphgym,2021-06-29 02:17:44.000,,60.0,61.0,,,,,,,,3.0,8.0,,,,,,,,,,,,,,,,,,,True, +878,madgrad,facebookresearch/madgrad,pytorch-utils,,https://github.com/facebookresearch/madgrad,https://github.com/facebookresearch/madgrad,MIT,2021-01-12 19:41:06.000,2021-08-20 18:31:57.000000,2021-08-20 18:31:57,13.0,,52,19.0,1.0,2.0,7.0,750,MADGRAD Optimization Method.,1.0,14,True,,,2.0,madgrad,,,,['pytorch'],21.0,21.0,https://pypi.org/project/madgrad,2021-04-01 13:54:29.000,,5500.0,5500.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +879,textflint,textflint/textflint,adversarial,,https://github.com/textflint/textflint,https://github.com/textflint/textflint,GPL-3.0,2021-03-06 11:15:52.000,2022-01-23 02:59:57.000000,2022-01-23 02:59:36,170.0,1.0,86,18.0,17.0,2.0,25.0,537,Unified Multilingual Robustness Evaluation Toolkit for Natural Language Processing.,12.0,14,False,2021-08-30 06:41:29.000,0.0.5,5.0,textflint,,,,,2.0,2.0,https://pypi.org/project/textflint,2021-08-30 06:41:29.000,,116.0,116.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +880,caliban,google/caliban,ml-experiments,,https://github.com/google/caliban,https://github.com/google/caliban,Apache-2.0,2020-06-02 18:12:50.000,2021-07-28 10:12:57.000000,2020-09-25 16:15:35,254.0,,42,19.0,79.0,15.0,12.0,411,"Research workflows made easy, locally and in the Cloud.",9.0,14,False,2020-09-12 19:41:23.000,0.4.1,10.0,caliban,,,,,,,https://pypi.org/project/caliban,2020-09-12 19:41:23.000,,44.0,44.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, +881,atspy,firmai/atspy,time-series-data,,https://github.com/firmai/atspy,https://github.com/firmai/atspy,MIT,2020-01-28 05:00:10.000,2022-02-10 01:20:22.000000,2021-12-18 09:26:18,99.0,1.0,80,21.0,14.0,18.0,2.0,408,AtsPy: Automated Time Series Models in Python (by @firmai).,5.0,14,True,2020-11-12 16:10:48.000,zen,39.0,atspy,,,,,5.0,5.0,https://pypi.org/project/atspy,2020-04-24 18:16:15.000,,694.0,694.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +882,VizSeq,facebookresearch/vizseq,nlp,,https://github.com/facebookresearch/vizseq,https://github.com/facebookresearch/vizseq,MIT,2019-08-26 13:19:38.000,2022-01-15 05:39:52.000000,2022-01-15 05:39:50,57.0,2.0,45,16.0,43.0,7.0,9.0,380,"An Analysis Toolkit for Natural Language Generation (Translation, Captioning, Summarization, etc.).",3.0,14,True,2020-08-07 01:13:52.000,0.1.15,16.0,vizseq,,,,,3.0,3.0,https://pypi.org/project/vizseq,2020-08-07 01:13:52.000,,91.0,91.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +883,TransferNLP,feedly/transfer-nlp,nlp,,https://github.com/feedly/transfer-nlp,https://github.com/feedly/transfer-nlp,MIT,2019-03-12 20:00:31.000,2020-05-28 19:00:02.000000,2020-05-28 17:31:53,465.0,,18,13.0,57.0,4.0,20.0,289,NLP library designed for reproducible experimentation management.,7.0,14,False,2020-05-28 19:00:02.000,0.1.6,8.0,transfer-nlp,,,,['pytorch'],,,https://pypi.org/project/transfer-nlp,2020-05-28 19:00:02.000,,165.0,165.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +884,Headliner,as-ideas/headliner,nlp,,https://github.com/as-ideas/headliner,https://github.com/as-ideas/headliner,MIT,2019-09-30 11:33:28.000,2021-03-26 07:19:57.000000,2020-02-14 09:03:27,276.0,,41,16.0,7.0,1.0,13.0,229,Easy training and deployment of seq2seq models.,2.0,14,False,2020-01-24 09:06:29.000,1.0.2,30.0,headliner,,,,,4.0,3.0,https://pypi.org/project/headliner,2020-01-24 09:06:29.000,1.0,105.0,105.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +885,tsaug,arundo/tsaug,time-series-data,,https://github.com/arundo/tsaug,https://github.com/arundo/tsaug,Apache-2.0,2019-09-27 00:38:05.000,2020-04-17 02:55:58.000000,2020-04-17 02:46:38,10.0,,25,10.0,7.0,7.0,3.0,223,A Python package for time series augmentation.,4.0,14,False,2020-04-17 02:50:25.000,0.2.1,4.0,tsaug,,,,,,,https://pypi.org/project/tsaug,2020-04-17 02:50:25.000,,2610.0,2610.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +886,TorchDrift,torchdrift/torchdrift,pytorch-utils,,https://github.com/TorchDrift/TorchDrift,https://github.com/TorchDrift/TorchDrift,Apache-2.0,2021-02-10 09:27:48.000,2021-06-29 11:52:29.000000,2021-06-29 11:52:29,33.0,,7,10.0,4.0,2.0,5.0,195,Drift Detection for your PyTorch Models.,2.0,14,False,2021-03-08 12:21:48.000,0.1.0,3.0,torchdrift,,,,['pytorch'],18.0,18.0,https://pypi.org/project/torchdrift,2021-03-08 12:51:05.000,,246.0,246.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +887,HugsVision,qanastek/HugsVision,image,,https://github.com/qanastek/HugsVision,https://github.com/qanastek/HugsVision,MIT,2021-08-12 21:46:08.000,2021-12-25 03:44:41.000000,2021-12-25 03:44:33,70.0,24.0,10,3.0,1.0,12.0,20.0,143,HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision.,2.0,14,False,2021-12-19 22:13:56.000,0.75.2,76.0,hugsvision,,,,['huggingface'],2.0,2.0,https://pypi.org/project/hugsvision,2021-12-19 22:27:31.000,,441.0,441.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, +888,numerizer,jaidevd/numerizer,nlp,,https://github.com/jaidevd/numerizer,https://github.com/jaidevd/numerizer,MIT,2019-12-02 07:00:34.000,2022-01-07 06:54:29.000000,2022-01-07 06:54:29,18.0,1.0,14,4.0,7.0,2.0,4.0,139,A Python module to convert natural language numerics into ints and floats.,3.0,14,False,2021-04-03 04:33:45.000,0.2.0,8.0,numerizer,,,,,18.0,18.0,https://pypi.org/project/numerizer,2021-04-03 04:33:45.000,,4390.0,4390.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +889,datajob,vincentclaes/datajob,data-pipelines,,https://github.com/vincentclaes/datajob,https://github.com/vincentclaes/datajob,Apache-2.0,2020-10-22 19:07:31.000,2022-01-08 18:26:40.000000,2022-01-08 18:26:39,394.0,7.0,13,4.0,71.0,17.0,40.0,83,Build and deploy a serverless data pipeline on AWS with no effort.,6.0,14,False,2021-08-13 11:25:15.000,0.10.1,11.0,datajob,,,,,,,https://pypi.org/project/datajob,2021-08-13 11:25:15.000,,33.0,33.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, +890,ENAS,carpedm20/ENAS-pytorch,hyperopt,,https://github.com/carpedm20/ENAS-pytorch,https://github.com/carpedm20/ENAS-pytorch,Apache-2.0,2018-02-15 04:54:37.000,2020-12-09 18:13:03.000000,2020-06-16 07:23:32,53.0,,463,113.0,11.0,37.0,7.0,2527,PyTorch implementation of Efficient Neural Architecture Search via Parameters Sharing.,6.0,13,False,,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +891,traingenerator,jrieke/traingenerator,others,,https://github.com/jrieke/traingenerator,https://github.com/jrieke/traingenerator,MIT,2020-12-03 16:47:16.000,2021-06-28 17:42:41.000000,2021-04-29 13:46:13,117.0,,160,37.0,9.0,13.0,3.0,1142,A web app to generate template code for machine learning.,3.0,13,True,,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +892,BLINK,facebookresearch/BLINK,nlp,,https://github.com/facebookresearch/BLINK,https://github.com/facebookresearch/BLINK,MIT,2019-09-25 21:27:44.000,2021-10-28 02:39:25.000000,2021-04-02 03:03:34,211.0,,143,38.0,30.0,48.0,31.0,810,Entity Linker solution.,16.0,13,True,,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +893,backprop,backprop-ai/backprop,model-serialisation,,https://github.com/backprop-ai/backprop,https://github.com/backprop-ai/backprop,Apache-2.0,2020-10-30 15:25:14.000,2021-05-03 09:15:25.000000,2021-05-03 09:15:21,219.0,,12,16.0,14.0,4.0,4.0,222,"Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models.",8.0,13,False,2021-04-20 13:53:12.000,0.1.2,14.0,backprop,,,,,,,https://pypi.org/project/backprop,2021-04-20 13:53:12.000,,79.0,79.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +894,ONNX-T5,abelriboulot/onnxt5,nlp,,https://github.com/abelriboulot/onnxt5,https://github.com/abelriboulot/onnxt5,Apache-2.0,2020-08-01 09:38:35.000,2021-01-28 09:26:15.000000,2021-01-28 09:24:52,74.0,,23,7.0,4.0,6.0,8.0,191,"Summarization, translation, sentiment-analysis, text-generation and more at blazing speed using a T5 version..",3.0,13,False,2021-01-28 09:26:15.000,0.1.8,11.0,onnxt5,,,,,,,https://pypi.org/project/onnxt5,2021-01-28 09:26:15.000,,79.0,79.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +895,Auptimizer,LGE-ARC-AdvancedAI/auptimizer,hyperopt,,https://github.com/LGE-ARC-AdvancedAI/auptimizer,https://github.com/LGE-ARC-AdvancedAI/auptimizer,GPL-3.0,2019-09-12 01:08:37.000,2022-02-10 03:24:31.000000,2021-03-03 01:30:06,79.0,,22,21.0,19.0,1.0,5.0,181,An automatic ML model optimization tool.,11.0,13,False,2021-03-03 02:00:23.000,2.0,7.0,auptimizer,,,,,,,https://pypi.org/project/auptimizer,2021-03-02 02:40:32.000,,46.0,46.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +896,textvec,textvec/textvec,nlp,,https://github.com/textvec/textvec,https://github.com/textvec/textvec,MIT,2018-04-12 14:03:53.000,2020-12-03 14:23:11.000000,2020-12-03 14:23:04,70.0,,21,8.0,14.0,3.0,6.0,181,Text vectorization tool to outperform TFIDF for classification tasks.,9.0,13,False,2019-09-12 07:41:04.000,2.0,4.0,textvec,,,,['sklearn'],4.0,4.0,https://pypi.org/project/textvec,2020-12-03 14:17:09.000,,41.0,41.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +897,ModelChimp,ModelChimp/modelchimp,ml-experiments,,https://github.com/ModelChimp/modelchimp,https://github.com/ModelChimp/modelchimp,BSD-2-Clause,2018-11-05 08:39:03.000,2022-02-10 06:55:23.000000,2021-08-01 07:11:57,363.0,,12,3.0,893.0,4.0,10.0,124,Experiment tracking for machine and deep learning projects.,3.0,13,False,2019-04-09 10:43:15.000,0.4.0,37.0,modelchimp,,modelchimp/modelchimp-server,,,,,https://pypi.org/project/modelchimp,2019-04-09 10:41:20.000,,89.0,105.0,,,,https://hub.docker.com/r/modelchimp/modelchimp-server,2019-04-09 10:15:09.532793,,654.0,3.0,,,,,,,,,,,,,,,,,,,,, +898,DeepNeuro,QTIM-Lab/DeepNeuro,medical-data,,https://github.com/QTIM-Lab/DeepNeuro,https://github.com/QTIM-Lab/DeepNeuro,MIT,2017-06-01 19:36:34.000,2020-06-24 13:00:15.000000,2020-06-24 13:00:14,285.0,,34,15.0,18.0,27.0,16.0,109,A deep learning python package for neuroimaging data. Made by:.,6.0,13,False,2019-06-10 21:04:04.000,0.2.3,6.0,deepneuro,,,,,1.0,1.0,https://pypi.org/project/deepneuro,2019-06-10 21:04:04.000,,40.0,40.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +899,surpriver,tradytics/surpriver,financial-data,,https://github.com/tradytics/surpriver,https://github.com/tradytics/surpriver,GPL-3.0,2020-08-30 07:56:22.000,2021-08-13 08:02:31.000000,2020-09-21 04:32:05,64.0,,261,85.0,11.0,10.0,6.0,1412,Find big moving stocks before they move using machine learning and anomaly detection.,6.0,12,False,,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +900,MedicalNet,Tencent/MedicalNet,medical-data,,https://github.com/Tencent/MedicalNet,https://github.com/Tencent/MedicalNet,MIT,2019-07-17 09:53:10.000,2021-09-16 22:05:49.000000,2020-08-27 13:37:26,26.0,,342,66.0,4.0,50.0,14.0,1325,Many studies have shown that the performance on deep learning is significantly affected by volume of training data...,1.0,12,False,,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +901,GraphVite,DeepGraphLearning/graphvite,graph,,https://github.com/DeepGraphLearning/graphvite,https://github.com/DeepGraphLearning/graphvite,Apache-2.0,2019-07-16 15:48:20.000,2021-01-14 02:19:03.000000,2021-01-14 02:18:46,15.0,,132,29.0,,37.0,56.0,997,GraphVite: A General and High-performance Graph Embedding System.,1.0,12,False,,,4.0,,milagraph/graphvite,,,,,,,,,,139.0,https://anaconda.org/milagraph/graphvite,2020-03-19 18:21:30.972,4182.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +902,dstack,dstackai/dstack,others,,https://github.com/dstackai/dstack,https://github.com/dstackai/dstack,Apache-2.0,2020-06-22 09:03:03.000,2022-02-07 08:42:06.000000,,,,11,,,21.0,,183,An open-source tool to rapidly develop data applications with Python.,2.0,12,False,2021-03-23 15:46:40.000,0.6.5,42.0,dstack,,,,,,,https://pypi.org/project/dstack,2022-02-07 08:42:06.000,,275.0,275.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +903,Hypermax,electricbrainio/hypermax,hyperopt,,https://github.com/electricbrainio/hypermax,https://github.com/electricbrainio/hypermax,BSD-3-Clause,2018-07-27 18:43:01.000,2020-08-02 18:08:50.000000,2020-08-02 18:08:46,207.0,,14,12.0,5.0,3.0,2.0,100,"Better, faster hyper-parameter optimization.",9.0,12,False,2019-10-23 15:40:12.000,0.5.1,11.0,hypermax,,,,,4.0,4.0,https://pypi.org/project/hypermax,2019-10-23 15:40:12.000,,36.0,36.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +904,Attribution Priors,suinleelab/attributionpriors,interpretability,,https://github.com/suinleelab/attributionpriors,https://github.com/suinleelab/attributionpriors,MIT,2019-06-24 23:54:24.000,2021-03-19 19:43:58.000000,2021-03-19 19:43:51,72.0,,10,5.0,,1.0,3.0,93,Tools for training explainable models using attribution priors.,6.0,12,False,2021-03-16 17:47:18.000,1.0.0,4.0,attributionpriors,,,,"['tensorflow', 'pytorch']",3.0,3.0,https://pypi.org/project/attributionpriors,2019-10-31 18:03:05.000,,28.0,28.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +905,contextual-ai,SAP/contextual-ai,interpretability,,https://github.com/SAP/contextual-ai,https://github.com/SAP/contextual-ai,Apache-2.0,2020-05-12 07:15:56.000,2021-11-11 10:54:41.000000,2021-11-11 10:53:33,630.0,,9,11.0,19.0,4.0,11.0,78,"Contextual AI adds explainability to different stages of machine learning pipelines - data, training, and inference -..",12.0,12,False,2021-01-25 04:56:57.000,0.0.2,2.0,contextual-ai,,,,,,,https://pypi.org/project/contextual-ai,2021-01-25 04:56:57.000,,90.0,90.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +906,nylon,Palashio/nylon,others,,https://github.com/Palashio/nylon,https://github.com/Palashio/nylon,MIT,2021-06-04 17:33:49.000,2021-07-29 20:34:04.000000,2021-07-23 19:37:10,185.0,,9,5.0,4.0,14.0,18.0,78,"An intelligent, flexible grammar of machine learning.",3.0,12,False,2021-06-25 14:27:32.000,0.0.7,8.0,nylon-ai,,,,,,,https://pypi.org/project/nylon-ai,2021-06-25 14:27:32.000,,43.0,43.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +907,LazyCluster,ml-tooling/lazycluster,distributed-ml,,https://github.com/ml-tooling/lazycluster,https://github.com/ml-tooling/lazycluster,Apache-2.0,2019-08-07 08:05:13.000,2021-09-16 02:14:06.000000,2021-08-19 13:59:11,444.0,,8,5.0,13.0,,,43,Distributed machine learning made simple.,2.0,12,False,2020-12-14 15:25:59.000,0.2.4,5.0,lazycluster,,,,,9.0,9.0,https://pypi.org/project/lazycluster,2020-12-14 14:49:33.000,,88.0,88.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +908,bias-detector,intuit/bias-detector,interpretability,,https://github.com/intuit/bias-detector,https://github.com/intuit/bias-detector,MIT,2021-02-02 16:58:52.000,2021-12-20 16:28:25.000000,2021-12-20 16:28:25,121.0,3.0,9,11.0,15.0,,,37,Bias Detector is a python package for detecting bias in machine learning models.,4.0,12,False,2021-04-22 15:20:54.000,0.0.12,11.0,bias-detector,,,,,,,https://pypi.org/project/bias-detector,2021-04-22 15:20:54.000,,60.0,60.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +909,model_search,google/model_search,hyperopt,,https://github.com/google/model_search,https://github.com/google/model_search,Apache-2.0,2021-01-19 18:26:34.000,2022-02-09 22:20:12.000000,2022-02-09 22:20:11,9.0,1.0,307,97.0,13.0,35.0,15.0,3185,AutoML algorithms for model architecture search at scale.,1.0,11,True,,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +910,Devol,joeddav/devol,hyperopt,,https://github.com/joeddav/devol,https://github.com/joeddav/devol,MIT,2017-02-10 03:07:54.000,2020-07-05 21:56:59.000000,2020-07-05 21:56:58,116.0,,109,44.0,12.0,7.0,20.0,937,Genetic neural architecture search with Keras.,18.0,11,False,,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +911,PySparNN,facebookresearch/pysparnn,nn-search,,https://github.com/facebookresearch/pysparnn,https://github.com/facebookresearch/pysparnn,BSD-3-Clause,2016-03-28 20:43:42.000,2020-10-02 06:01:01.000000,2018-01-31 16:50:23,147.0,,143,41.0,7.0,15.0,14.0,897,Approximate Nearest Neighbor Search for Sparse Data in Python!.,5.0,11,False,,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +912,PandaPy,firmai/pandapy,data-containers,,https://github.com/firmai/pandapy,https://github.com/firmai/pandapy,MIT,2020-01-15 18:21:23.000,2021-10-20 11:36:04.000000,2021-10-20 11:36:04,85.0,,56,19.0,2.0,2.0,1.0,494,PandaPy has the speed of NumPy and the usability of Pandas 10x to 50x faster (by @firmai).,3.0,11,True,2020-11-12 16:12:54.000,zen,22.0,pandapy,,,,['pandas'],1.0,1.0,https://pypi.org/project/pandapy,2020-01-25 23:10:32.000,,96.0,96.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +913,deltapy,firmai/deltapy,tabular,,https://github.com/firmai/deltapy,https://github.com/firmai/deltapy,MIT,2020-04-08 05:27:53.000,2021-12-18 09:25:30.000000,2021-12-18 09:25:30,41.0,1.0,40,14.0,2.0,2.0,1.0,402,DeltaPy - Tabular Data Augmentation (by @firmai).,4.0,11,True,2020-11-12 16:13:21.000,zen,11.0,deltapy,,,,,2.0,2.0,https://pypi.org/project/deltapy,2020-04-09 01:48:32.000,,47.0,47.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +914,rliable,google-research/rliable,reinforcement-learning,,https://github.com/google-research/rliable,https://github.com/google-research/rliable,Apache-2.0,2021-08-20 00:41:06.000,2022-02-06 20:10:40.000000,2022-02-06 20:10:40,41.0,14.0,17,7.0,2.0,,6.0,313,"Library for reliable evaluation on RL and ML benchmarks, as recommended by our NeurIPS 2021 Outstanding Paper.",2.0,11,True,,,,rliable`,,,,,6.0,6.0,https://pypi.org/project/rliable`,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, +915,autodist,petuum/autodist,distributed-ml,,https://github.com/petuum/autodist,https://github.com/petuum/autodist,Apache-2.0,2020-06-29 19:45:38.000,2021-04-12 21:55:36.000000,2021-01-28 00:04:40,208.0,,22,16.0,49.0,11.0,1.0,119,Simple Distributed Deep Learning on TensorFlow.,11.0,11,False,,,2.0,autodist,,,,['tensorflow'],,,https://pypi.org/project/autodist,2020-07-16 05:36:19.000,,36.0,36.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +916,Mozart,aashrafh/Mozart,ocr,,https://github.com/aashrafh/Mozart,https://github.com/aashrafh/Mozart,Apache-2.0,2020-12-14 11:49:14.000,2021-05-05 17:21:44.000000,2021-05-05 17:21:44,60.0,,52,16.0,5.0,3.0,7.0,352,An optical music recognition (OMR) system. Converts sheet music to a machine-readable version.,5.0,10,True,,,,,,,,['sklearn'],,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +917,Hypertunity,gdikov/hypertunity,hyperopt,,https://github.com/gdikov/hypertunity,https://github.com/gdikov/hypertunity,Apache-2.0,2019-06-02 12:04:55.000,2020-01-26 23:14:49.000000,2020-01-26 22:53:29,64.0,,9,9.0,44.0,,2.0,120,A toolset for black-box hyperparameter optimisation.,2.0,9,False,2020-01-26 23:08:16.000,1.0.1,7.0,hypertunity,,,,,2.0,2.0,https://pypi.org/project/hypertunity,2020-01-26 23:08:16.000,,15.0,15.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +918,spacy-dbpedia-spotlight,MartinoMensio/spacy-dbpedia-spotlight,nlp,,https://github.com/MartinoMensio/spacy-dbpedia-spotlight,https://github.com/MartinoMensio/spacy-dbpedia-spotlight,MIT,2020-04-29 19:35:04.000,2022-01-10 16:28:50.000000,2022-01-10 16:28:50,15.0,2.0,6,6.0,1.0,4.0,2.0,50,A spaCy wrapper for DBpedia Spotlight.,2.0,9,False,2021-04-12 13:25:07.000,0.2.1,6.0,spacy-dbpedia-spotlight,,,,['spacy'],,,https://pypi.org/project/spacy-dbpedia-spotlight,2021-04-09 13:21:45.000,,172.0,172.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +919,traintool,jrieke/traintool,ml-experiments,,https://github.com/jrieke/traintool,https://github.com/jrieke/traintool,Apache-2.0,2020-09-30 22:23:05.000,2021-03-12 01:44:04.000000,2021-03-12 01:43:14,122.0,,1,3.0,,,,9,Train off-the-shelf machine learning models in one line of code.,,9,False,2020-11-02 02:25:32.000,0.0.3,3.0,traintool,,,,"['pytorch', 'tensorflow', 'sklearn']",,,https://pypi.org/project/traintool,2020-11-02 02:25:32.000,,22.0,22.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,, +920,jaxdf,ucl-bug/jaxdf,jax-utils,,https://github.com/ucl-bug/jaxdf,https://github.com/ucl-bug/jaxdf,LGPL-3.0,2021-09-08 16:38:46.000,2022-02-09 16:24:15.000000,2022-01-09 11:46:42,81.0,33.0,1,7.0,51.0,1.0,,43,A JAX-based research framework for writing differentiable numerical simulators with arbitrary discretizations.,2.0,8,False,2021-11-29 17:38:20.000,0.1.0-alpha,1.0,,,,,['jax'],,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, +921,pyrtfolio,alvarobartt/pyrtfolio,financial-data,,https://github.com/alvarobartt/pyrtfolio,https://github.com/alvarobartt/pyrtfolio,GPL-3.0,2019-10-06 20:22:12.000,2020-11-20 09:58:42.000000,2020-11-20 09:58:41,19.0,,18,6.0,1.0,1.0,5.0,104,Python package to generate stock portfolios.,1.0,7,False,2020-03-13 20:04:08.000,0.2,3.0,pyrtfolio,,,,,,,https://pypi.org/project/pyrtfolio,2020-03-13 20:31:47.000,,24.0,24.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,True, diff --git a/latest-changes.md b/latest-changes.md index 5d5cae5f..6dcb5e45 100644 --- a/latest-changes.md +++ b/latest-changes.md @@ -2,29 +2,71 @@ _Projects that have a higher project-quality score compared to the last update. There might be a variety of reasons, such as increased downloads or code activity._ -- joblib (πŸ₯‡37 Β· ⭐ 2.6K Β· πŸ“ˆ) - Computing with Python functions. BSD-3 -- imageio (πŸ₯‡37 Β· ⭐ 980 Β· πŸ“ˆ) - Python library for reading and writing image data. BSD-2 -- PyCaret (πŸ₯‡36 Β· ⭐ 4.8K Β· πŸ“ˆ) - An open-source, low-code machine learning library in Python. MIT -- Great Expectations (πŸ₯ˆ35 Β· ⭐ 5.9K Β· πŸ“ˆ) - Always know what to expect from your data. Apache-2 -- Faiss (πŸ₯‡34 Β· ⭐ 16K Β· πŸ“ˆ) - A library for efficient similarity search and clustering of dense vectors. MIT -- EasyOCR (πŸ₯‡33 Β· ⭐ 14K Β· πŸ“ˆ) - Ready-to-use OCR with 80+ supported languages and all popular.. Apache-2 -- auto-sklearn (πŸ₯‡33 Β· ⭐ 6K Β· πŸ“ˆ) - Automated Machine Learning with scikit-learn. BSD-3 -- sentencepiece (πŸ₯ˆ33 Β· ⭐ 5.6K Β· πŸ“ˆ) - Unsupervised text tokenizer for Neural Network-based.. Apache-2 -- OpenNMT (πŸ₯ˆ33 Β· ⭐ 5.4K Β· πŸ“ˆ) - Open Source Neural Machine Translation in PyTorch. MIT -- Objax (πŸ₯‰22 Β· ⭐ 670 Β· πŸ“ˆ) - Objax is a machine learning framework that provides an Object.. Apache-2 jax +- MMDetection (πŸ₯‡37 Β· ⭐ 18K Β· πŸ“ˆ) - OpenMMLab Detection Toolbox and Benchmark. Apache-2 +- DeepSpeech (πŸ₯‡33 Β· ⭐ 19K Β· πŸ“ˆ) - DeepSpeech is an open source embedded (offline, on-.. MPL-2.0 +- Recommenders (πŸ₯‡32 Β· ⭐ 12K Β· πŸ“ˆ) - Best Practices on Recommendation Systems. MIT +- Ludwig (πŸ₯‰32 Β· ⭐ 8.1K Β· πŸ“ˆ) - Data-centric declarative deep learning framework. Apache-2 +- River (πŸ₯ˆ30 Β· ⭐ 3.2K Β· πŸ“ˆ) - Online machine learning in Python. BSD-3 +- Haiku (πŸ₯‰29 Β· ⭐ 1.7K Β· πŸ“ˆ) - JAX-based neural network library. Apache-2 +- Talos (πŸ₯ˆ26 Β· ⭐ 1.5K Β· πŸ“ˆ) - Hyperparameter Optimization for TensorFlow, Keras and PyTorch. MIT +- torchsde (πŸ₯‰21 Β· ⭐ 910 Β· πŸ’€) - Differentiable SDE solvers with GPU support and efficient.. Apache-2 +- TF Compression (πŸ₯‰21 Β· ⭐ 580 Β· πŸ“ˆ) - Data compression in TensorFlow. Apache-2 +- Torch-Struct (πŸ₯‰18 Β· ⭐ 1K Β· πŸ“ˆ) - Fast, general, and tested differentiable structured.. MIT ## πŸ“‰ Trending Down _Projects that have a lower project-quality score compared to the last update. There might be a variety of reasons such as decreased downloads or code activity._ -- Airflow (πŸ₯‡44 Β· ⭐ 25K Β· πŸ“‰) - Platform to programmatically author, schedule, and monitor.. Apache-2 -- Rasa (πŸ₯‡39 Β· ⭐ 13K Β· πŸ“‰) - Open source machine learning framework to automate text- and.. Apache-2 -- dbt (πŸ₯ˆ36 Β· ⭐ 4K Β· πŸ“‰) - dbt enables data analysts and engineers to transform their data using.. Apache-2 -- tensorflow-hub (πŸ₯ˆ34 Β· ⭐ 3K Β· πŸ“‰) - A library for transfer learning by reusing parts of.. Apache-2 -- category_encoders (πŸ₯ˆ33 Β· ⭐ 1.8K Β· πŸ“‰) - A library of sklearn compatible categorical variable.. BSD-3 -- torchaudio (πŸ₯‡32 Β· ⭐ 1.5K Β· πŸ“‰) - Data manipulation and transformation for audio signal.. BSD-2 -- snowballstemmer (πŸ₯ˆ32 Β· ⭐ 540 Β· πŸ“‰) - Snowball compiler and stemming algorithms. BSD-3 -- Bottleneck (πŸ₯ˆ31 Β· ⭐ 690 Β· πŸ’€) - Fast NumPy array functions written in C. BSD-2 -- flupy (πŸ₯‰17 Β· ⭐ 170 Β· πŸ“‰) - Fluent data pipelines for python and your shell. MIT -- Torch Points 3D (πŸ₯‰13 Β· ⭐ 1 Β· πŸ“‰) - Pytorch framework for doing deep learning on point.. BSD-3 +- tensor2tensor (πŸ₯ˆ33 Β· ⭐ 12K Β· πŸ“‰) - Library of deep learning models and datasets designed.. Apache-2 +- carla (πŸ₯ˆ31 Β· ⭐ 7.2K Β· πŸ“‰) - Open-source simulator for autonomous driving research. MIT +- category_encoders (πŸ₯ˆ31 Β· ⭐ 1.8K Β· πŸ“‰) - A library of sklearn compatible categorical variable.. BSD-3 +- snowballstemmer (πŸ₯ˆ30 Β· ⭐ 540 Β· πŸ“‰) - Snowball compiler and stemming algorithms. BSD-3 +- BentoML (πŸ₯ˆ27 Β· ⭐ 3.2K Β· πŸ“‰) - The Unified Model Serving Framework. Apache-2 +- TensorForce (πŸ₯‰27 Β· ⭐ 3.1K Β· πŸ“‰) - Tensorforce: a TensorFlow library for applied.. Apache-2 +- FATE (πŸ₯‰25 Β· ⭐ 3.9K Β· πŸ“‰) - An Industrial Grade Federated Learning Framework. Apache-2 +- fastNLP (πŸ₯‰25 Β· ⭐ 2.5K Β· πŸ“‰) - fastNLP: A Modularized and Extensible NLP Framework. Currently.. Apache-2 +- Elephas (πŸ₯‰25 Β· ⭐ 1.5K Β· πŸ“‰) - Distributed Deep learning with Keras & Spark. MIT keras +- openTSNE (πŸ₯‰24 Β· ⭐ 940 Β· πŸ“‰) - Extensible, parallel implementations of t-SNE. BSD-3 + +## βž• Added Projects + +_Projects that were recently added to this best-of list._ + +- triton (πŸ₯ˆ28 Β· ⭐ 3.5K Β· βž•) - Development repository for the Triton language and compiler. MIT +- adapter-transformers (πŸ₯ˆ28 Β· ⭐ 660 Β· βž•) - Huggingface Transformers + Adapters =. Apache-2 huggingface +- pandera (πŸ₯‰27 Β· ⭐ 1K Β· βž•) - A light-weight, flexible, and expressive data validation library.. MIT +- SynapseML (πŸ₯‰26 Β· ⭐ 3.1K Β· βž•) - Simple and Distributed Machine Learning. MIT +- icevision (πŸ₯‰25 Β· ⭐ 580 Β· βž•) - An Agnostic Computer Vision Framework - Pluggable to any.. Apache-2 +- sahi (πŸ₯‰24 Β· ⭐ 540 Β· βž•) - A lightweight vision library for performing large scale object detection/.. MIT +- rubrix (πŸ₯‰23 Β· ⭐ 840 Β· βž•) - Python framework for data-centric NLP. Apache-2 +- docarray (πŸ₯‰23 Β· ⭐ 520 Β· 🐣) - The data structure for unstructured data. Apache-2 +- MONAILabel (πŸ₯‰23 Β· ⭐ 200 Β· βž•) - MONAI Label is an intelligent open source image labeling and.. Apache-2 +- whoosh (πŸ₯‰23 Β· ⭐ 190 Β· βž•) - Pure-Python full-text search library. ❗️BSD-1-Clause +- happy-transformer (πŸ₯‰22 Β· ⭐ 260 Β· βž•) - A package built on top of Hugging Faces transformers.. Apache-2 huggingface +- OpenPrompt (πŸ₯‰21 Β· ⭐ 1.1K Β· 🐣) - An Open-Source Framework for Prompt-Learning. Apache-2 +- detoxify (πŸ₯‰21 Β· ⭐ 380 Β· βž•) - Trained models & code to predict toxic comments on all 3 Jigsaw.. Apache-2 +- TimeSide (πŸ₯‰21 Β· ⭐ 310 Β· πŸ’€) - Scalable audio processing framework written in Python with a.. ❗️AGPL-3.0 +- qdrant (πŸ₯‰20 Β· ⭐ 1.1K Β· βž•) - Qdrant - vector similarity search engine with extended filtering.. Apache-2 +- jraph (πŸ₯‰20 Β· ⭐ 820 Β· βž•) - A Graph Neural Network Library in Jax. Apache-2 +- kompute (πŸ₯‰20 Β· ⭐ 750 Β· βž•) - General purpose GPU compute framework built on Vulkan to support.. Apache-2 +- deepsnap (πŸ₯‰20 Β· ⭐ 390 Β· βž•) - Python library assists deep learning on graphs. MIT +- SerpentAI (πŸ₯‰19 Β· ⭐ 6.2K Β· πŸ’€) - Game Agent Framework. Helping you create AIs / Bots that learn to.. MIT +- chitra (πŸ₯‰19 Β· ⭐ 180 Β· βž•) - A multi-functional library for full-stack Deep Learning... Apache-2 +- prettymaps (πŸ₯‰18 Β· ⭐ 7.7K Β· βž•) - A small set of Python functions to draw pretty maps from.. ❗️AGPL-3.0 +- pytorchviz (πŸ₯‰18 Β· ⭐ 2.1K Β· πŸ’€) - A small package to create visualizations of PyTorch execution.. MIT +- FinQuant (πŸ₯‰18 Β· ⭐ 720 Β· πŸ’€) - A program for financial portfolio management, analysis and.. MIT +- parallelformers (πŸ₯‰18 Β· ⭐ 440 Β· βž•) - Parallelformers: An Efficient Model Parallelization.. Apache-2 +- equinox (πŸ₯‡18 Β· ⭐ 260 Β· βž•) - Callable PyTrees and filtered JIT/grad transformations =.. Apache-2 +- scenic (πŸ₯‰17 Β· ⭐ 720 Β· βž•) - Scenic: A Jax Library for Computer Vision Research and Beyond. Apache-2 +- mesh-transformer-jax (πŸ₯‰16 Β· ⭐ 3.8K Β· βž•) - Model parallel transformers in JAX and Haiku. Apache-2 +- ptgnn (πŸ₯‰16 Β· ⭐ 300 Β· βž•) - A PyTorch Graph Neural Network Library. MIT +- NeuralCompression (πŸ₯‰16 Β· ⭐ 240 Β· βž•) - A collection of tools for neural compression enthusiasts. MIT +- upgini (πŸ₯‰15 Β· ⭐ 21 Β· 🐣) - Automated feature discovery & enrichment library automatically find.. BSD-3 +- GraphGym (πŸ₯‰14 Β· ⭐ 880 Β· βž•) - Platform for designing and evaluating Graph Neural Networks (GNN). MIT +- caliban (πŸ₯‰14 Β· ⭐ 410 Β· πŸ’€) - Research workflows made easy, locally and in the Cloud. Apache-2 +- HugsVision (πŸ₯‰14 Β· ⭐ 140 Β· 🐣) - HugsVision is a easy to use huggingface wrapper for state-of-.. MIT huggingface +- datajob (πŸ₯‰14 Β· ⭐ 83 Β· βž•) - Build and deploy a serverless data pipeline on AWS with no effort. Apache-2 +- rliable (πŸ₯‰11 Β· ⭐ 310 Β· 🐣) - Library for reliable evaluation on RL and ML benchmarks, as.. Apache-2 +- jaxdf (πŸ₯‰8 Β· ⭐ 43 Β· 🐣) - A JAX-based research framework for writing differentiable.. ❗️LGPL-3.0 +- pyrtfolio (πŸ₯‰7 Β· ⭐ 100 Β· πŸ’€) - Python package to generate stock portfolios. ❗️GPL-3.0