6YL

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🧑‍🏫 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, ... 🧠

2022-Machine-Learning-Specialization

AndrewNg-DeepLearning

微专业: 吴恩达 深度学习工程师 作业

Coursera-ML-AndrewNg-Notes

吴恩达老师的机器学习课程个人笔记

CycleGAN

interesting!

graphcast

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.