Python Data Science Handbook: full text in Jupyter Notebooks

⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.

Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。

此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。

Natural Language Processing Tutorial for Deep Learning Researchers

PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch：入门与实战》)

The "Python Machine Learning (1st edition)" book code repository and info resource

搜集、整理、发布 中文 自然语言处理 语料/数据集，与 有志之士 共同 促进 中文 自然语言处理 的 发展。

TensorFlow 2.x version's Tutorials and Examples, including CNN, RNN, GAN, Auto-Encoders, FasterRCNN, GPT, BERT examples, etc. TF 2.0版入门实例代码，实战教程。

数据挖掘、计算机视觉、自然语言处理、推荐系统竞赛知识、代码、思路

Tutorials on getting started with PyTorch and TorchText for sentiment analysis.

Go to https://github.com/pytorch/tutorials - this repo is deprecated and no longer maintained

Code for Stanford CS224u

Pytorch0.4.1 codes for InsightFace

A series of Jupyter notebooks with Chinese comment that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

wgan, wgan2(improved, gp), infogan, and dcgan implementation in lasagne, keras, pytorch

Jupyter Notebooks for Springer book "Python for Probability, Statistics, and Machine Learning"

推荐系统入门指南，全面介绍了工业级推荐系统的理论知识（王树森推荐系统公开课-基于小红书的场景讲解工业界真实的推荐系统），如何基于TensorFlow2训练模型，如何实现高性能、高并发、高可用的Golang推理微服务。Comprehensively introduced the theory of industrial recommender system, how to trainning …

NLP in Python with Deep Learning

Implementation of disco-diffusion wrapper that could run on your own GPU with batch text input.

The hands-on NLTK tutorial for NLP in Python

Clean, scalable and easy to use ResNet implementation in Pytorch

Making BERT stretchy. Semantic Elasticsearch with Sentence Transformers

深度学习与推荐系统学习，理论结合代码更香。

Build a semantic search engine with Transformers and Faiss

CCKS 2018 开放领域的中文问答任务 1st 解决方案

练手项目：Comment of Interest 电商文本评论数据挖掘 （爬虫 + 观点抽取 + 句子级和观点级情感分析）