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TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
Learn how to design, develop, deploy and iterate on production-grade ML applications.
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
100-Days-Of-ML-Code中文版
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
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。
📡 Simple and ready-to-use tutorials for TensorFlow
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
FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.
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》)
YSDA course in Natural Language Processing
Interview = 简历指南 + 算法题 + 八股文 + 源码分析
Build your neural network easy and fast, 莫烦Python中文教学
tensorflow2中文教程，持续更新(当前版本:tensorflow2.0)，tag: tensorflow 2.0 tutorials
An annotated implementation of the Transformer paper.
This project reproduces the book Dive Into Deep Learning (https://d2l.ai/), adapting the code from MXNet into PyTorch.
Acceptance rates for the major AI conferences
骆驼(Luotuo): Open Sourced Chinese Language Models. Developed by 陈启源 @ 华中师范大学 & 李鲁鲁 @ 商汤科技 & 冷子昂 @ 商汤科技
Language-Agnostic SEntence Representations
Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier
This is code of book "Learn Deep Learning with PyTorch"