vsmolyakov
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A Python implementation of global optimization with gaussian processes.
LLMOps framework using LangChain, Pinecone and Kubeflow
YAML files for use with The Kubernetes Book
Code repository for my book "Microservice APIs" (https://www.manning.com/books/microservice-apis)
CP4 Free Source Code Project (C++17, Java11, Python3 and OCaml)
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
Quantitative research and educational materials
Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
Collection of Monte Carlo (MC) and Markov Chain Monte Carlo (MCMC) algorithms applied on simple examples.
Collection of probabilistic models and inference algorithms
A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
Natural Language Processing Best Practices & Examples
A library that incorporates state-of-the-art explainers for text-based machine learning models and visualizes the result with a built-in dashboard.
Simple implementation of CART algorithm to train decision trees
C++ Implementation of Algorithms (aka. Spaghetti Source)
Keras implementations of Generative Adversarial Networks.
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep lear…
A header-only C++ library for L-BFGS and L-BFGS-B algorithms
Dirichlet Process Mixture Model sampling-based inference algorithms
Library for fast text representation and classification.
A modular library built on top of Keras and TensorFlow to generate a caption in natural language for any input image.
Python code for "Probabilistic Machine learning" book by Kevin Murphy
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
C++ code and Python wrappers for Inference on Bayesian Non-Parametric Models
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Some iPython Notebooks I have created for personal learning
Bayesian Modeling and Probabilistic Programming in Python