leedl-tutorial

Why we included this project

Hung-yi Lee's machine learning lectures have been reworked into a structured, self-contained book that walks through the math behind the models, with full derivations and patient explanations of the tricky parts. The coverage runs from transformers, CNNs, and RNNs through GANs, diffusion models, and reinforcement learning, then pushes into network compression, pruning, and transfer learning, so it carries a reader from fundamentals to research-flavored topics. Everything ships as Jupyter notebooks with a rendered online version and a downloadable PDF, which makes it easy to read on screen, annotate, or work through in a study group. For anyone learning deep learning in Chinese who wants one coherent path instead of scattered videos and slides, this is a practical companion to the lectures.