开源项目资料整理
https://github.com/fengdu78/Coursera-ML-AndrewNg-Notes
https://morvanzhou.github.io/tutorials
B站:https://space.bilibili.com/243821484#!/
个人页:https://morvanzhou.github.io/
https://github.com/apachecn/AiLearning
https://kivy-cn.github.io/Stanford-CS-229-CN/#/Markdown/cs229-loss-functions
《机器学习技法》课程是《机器学习基石》的进阶课程。主要介绍了机器学习领域经典的一些算法,包括支持向量机、决策树、随机森林、神经网络等等。难度要略高于《机器学习基石》,具有很强的实用性。
中文视频:https://www.bilibili.com/video/av36731342
中文笔记:
https://github.com/ShusenTang/Dive-into-DL-PyTorch
https://github.com/greebear/deeplearning.ai-notes
深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述
链接:https://github.com/scutan90/DeepLearning-500-questions
https://github.com/nl8590687/ASRT_SpeechRecognition
https://github.com/vipstone/faceai
https://github.com/hankcs/HanLP
https://github.com/NLPchina/ansj_seg
https://github.com/codemayq/chinese_chatbot_corpus
https://github.com/Embedding/Chinese-Word-Vectors ##shibing624/pycorrector[中文文本纠错工具] 中文文本纠错工具。音似、形似错字(或变体字)纠正,可用于中文拼音、笔画输入法的错误纠正。python3开发。
pycorrector依据语言模型检测错别字位置,通过拼音音似特征、笔画五笔编辑距离特征及语言模型困惑度特征纠正错别字。
https://github.com/shibing624/pycorrector
https://github.com/YeYzheng/KGQA-Based-On-medicine
https://github.com/zhaoyingjun/chatbot
https://github.com/liuhuanyong/QAonMilitaryKG QAonMilitaryKG,QaSystem based on military knowledge graph that stores in mongodb which is different from the previous one, 基于mongodb存储的军事领域知识图谱问答项目,包括飞行器、太空装备等8大类,100余小类,共计5800项的军事武器知识库,该项目不使用图数据库进行存储,通过jieba进行问句解析,问句实体项识别,基于查询模板完成多类问题的查询,主要是提供一种工业界的问答思想demo。 ##ProductKnowledgeGraph https://github.com/liuhuanyong/ProductKnowledgeGraph 基于京东网站的商品上下级概念,商品品牌之间关系,商品描述维度等知识库,基于该知识库可以支持商品属性库构建,商品销售问答,品牌物品生产等知识查询服务,也可用于情感分析等下游应用
https://github.com/jobbole/awesome-programming-books
https://github.com/imhuay/Algorithm_Interview_Notes-Chinese
周志华老师的《机器学习》(西瓜书)是机器学习领域的经典入门教材之一,周老师为了使尽可能多的读者通过西瓜书对机器学习有所了解, 所以在书中对部分公式的推导细节没有详述
https://github.com/datawhalechina/pumpkin-book
This tutorial was designed for easily diving into TensorFlow, through examples. For readability, it includes both notebooks and source codes with explanation, for both TF v1 & v2.
https://github.com/aymericdamien/TensorFlow-Examples
https://github.com/yao62995/tensorflow
https://github.com/jikexueyuanwiki/tensorflow-zh
https://github.com/tensorflow/models
https://github.com/apachecn/fastai-ml-dl-notes-zh
https://github.com/exacity/deeplearningbook-chinese
https://github.com/apachecn/ai-roadmap
https://github.com/FudanNLP/nlp-beginner
https://github.com/greebear/deeplearning.ai-notes
https://github.com/apachecn/feature-engineering-for-ml-zh
https://github.com/apachecn/ml-mastery-zh
https://github.com/apachecn/hands-on-ml-zh
https://github.com/apachecn/kaggle
#项目
https://github.com/inspurer/WorkAttendanceSystem
https://github.com/vipstone/faceai https://github.com/ageitgey/face_recognition