ML2022-Spring

Why we included this project

This is the official code repository for Hung-yi Lee's Machine Learning course at National Taiwan University, spring 2022 edition. Rather than just lecture notes, it packages all 15 homework assignments as Jupyter notebooks with slides, and the earlier ones come with video walkthroughs. The sequence tracks the course itself, starting from regression and classification and moving through CNNs, self-attention, Transformers, GANs, BERT, autoencoders, explainable AI, adversarial attacks, and on to reinforcement learning, network compression, lifelong learning, and meta-learning. For self-learners that is a structured path from fundamentals to research-level material with real code to run at each step, and instructors get a complete set of lab exercises they can adapt. If you are working through the curriculum on your own, the notebooks, slides, and videos give you a dependable way to match your practice to what the course expects.