PyTorch deep learning tutorial
A Chinese-language PyTorch tutorial series (Jupyter notebooks) covering neural network basics, CNN, RNN, DQN, GAN, and other deep learning architectures.
Same problem, same approach. Swapping one for another is a config change, not a rewrite.
Choose it for a recent, theory-first Chinese PyTorch course covering deep learning fundamentals.
《李宏毅深度学习教程》（李宏毅老师推荐👍，苹果书🍎），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases
Choose it for a comprehensive, modern PyTorch tutorial with up-to-date practices and rich exercises.
Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2023
Choose it for a Chinese practicalAI course with PyTorch examples and a project-based curriculum.
AI实战-practicalAI 中文版
Solves the same problem with a different architecture or at a different layer. Expect to rewrite the integration.
Choose it over the seed if you want a fastai-based, top-down deep learning book rather than low-level PyTorch code.
The fastai book, published as Jupyter Notebooks
Choose it if you want TensorFlow-based lab assignments from MIT's deep learning course.
Lab Materials for MIT 6.S191: Introduction to Deep Learning
Choose it if you want simple TensorFlow code examples instead of PyTorch.
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
Choose it for a ready-to-use TensorFlow course if you are not committed to PyTorch.
:satellite: Simple and ready-to-use tutorials for TensorFlow
Choose it for Keras-based deep learning course materials with practical applications.
T81-558: Keras - Applications of Deep Neural Networks @Washington University in St. Louis
Choose it if you prefer the same author's teaching style but want TensorFlow instead of PyTorch.
Tensorflow tutorial from basic to hard, 莫烦Python 中文AI教学
Choose it if you want multimedia experiments and videos to intuit deep learning rather than a structured tutorial.
Videos, notes and experiments to understand deep learning
Choose it for a book-driven classic ML course with scikit-learn and some neural networks.
The "Python Machine Learning (1st edition)" book code repository and info resource
Choose it for an open ML course with sklearn and data science focus, not deep learning.
Open Machine Learning Course
Choose it for a wide assortment of independent tutorials where you can pick specific topics.
A resource for learning about Machine learning & Deep Learning
Choose it for a recipe-style TensorFlow cookbook covering many practical tasks.
Code for Tensorflow Machine Learning Cookbook
An earlier or more limited way to do the job. Still the right call when you need something small, proven, or CPU-only.
Choose it as an older but still valid Chinese PyTorch handbook if you prefer a book-style reference.
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
Choose it as a classic, well-organized PyTorch tutorial if you prefer plain Python files over notebooks.
PyTorch Tutorial for Deep Learning Researchers
Choose it if you only need Keras GAN examples and not a full deep learning tutorial.
Keras implementations of Generative Adversarial Networks.
These projects were analysed and named PyTorch-Tutorial among their alternatives. The relationship is not symmetric — how PyTorch-Tutorial rates them is a separate judgement, made when PyTorch-Tutorial is analysed in its own right.
calls PyTorch-Tutorial “choose it for a friendly Chinese-language beginner PyTorch tutorial instead of paper implementations.”
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
calls PyTorch-Tutorial “Choose for a straightforward PyTorch tutorial in Chinese, though it is older and less maintained.”
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
calls PyTorch-Tutorial “Choose for PyTorch-specific tutorials in Chinese/English, not NumPy from scratch.”
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 learning.
calls PyTorch-Tutorial “Use for a beginner-friendly PyTorch tutorial series if you prefer PyTorch over TensorFlow.”
:satellite: Simple and ready-to-use tutorials for TensorFlow
calls PyTorch-Tutorial “Chinese-language PyTorch tutorials with exercises; for PyTorch learners preferring Chinese.”
TensorFlow Tutorials with YouTube Videos
calls PyTorch-Tutorial “Older Chinese PyTorch tutorial series, still valid but unmaintained since 3.4y.”
PyTorch Tutorial for Deep Learning Researchers
calls PyTorch-Tutorial “choose if you want the classic Morvan Chinese PyTorch walkthrough despite being outdated.”
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
calls PyTorch-Tutorial “Chinese PyTorch-specific tutorials, narrower and older (no recent updates).”
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。
calls PyTorch-Tutorial “Choose if you need a beginner PyTorch tutorial in Chinese, but it lacks the theoretical depth and breadth of the seed.”
《李宏毅深度学习教程》（李宏毅老师推荐👍，苹果书🍎），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases
calls PyTorch-Tutorial “When you want a Chinese-language PyTorch tutorial series, but it's older and unmaintained.”
A collection of machine learning examples and tutorials.
calls PyTorch-Tutorial “Choose when you want minimal Chinese PyTorch examples for quick neural-network demos rather than MIT's full course.”
Lab Materials for MIT 6.S191: Introduction to Deep Learning