Overview

This repo is the self-made notes of Machine Learning course from Hong-yi Lee.

All the notes are in the ./notes/ folder.

This repo is used for owner to document learning outcomes. If it helps you a little, please star it.

The Recommended Way to Read

All the Markdown files are written by Obsidian. So I recommend you to clone them down and browser them in Obsidian.

Contents

1. Introduction of Machine/Deep Learning (First Part)
2. Introduction of Machine/Deep Learning (Second Part)
3. General Guide
4. PyTorch Tutorial
5. Pytorch tutorial with example
6. Optimization Failure
7. Batch and Momentum
8. Adaptive Learning Rate
9. Classification
10. (To Learn) Deep Learning
11. (To Learn) Backpropagation
12. (To Learn) Regression
13. Convolutional Neural Network
14. Validation Failure
15. Spatial Transformer
16. Self-attention
17. Batch Normalization
18. Tranformer
19. More Self-attention

To be continued...