I took some notes during studying Machine Learning with Python-From Linear Models to Deep Learning, I find it’s pretty useful for studying ML. And I would like to share it now.

1. Introduction to ML
2. Linear Classification
3. Linear Classification 2
4. Overview of Linear Classification and SVM
5. Non-Linear Classification and Kernels
6. Overview of Unit1
7. Muticlass Classification
8. Recommender System
9. Feed Forward Neural Network

I will keep updating my notes every week.

These notes are written under my understanding of the knowledge. Please feel free to point out any mistakes.