Statistical Machine Learning (机器学习基础)
Undergraduate course, Renmin University of China, 2024
This is a math intensive machine learning course lectured by Prof. Hongteng Xu from GSAI, Renmin University of China. The course has a focus on the mathematical derivations and theorems behind machine learning algorithms, covering four major topics in statistical machine learning: Regression, Dimensionality Reduction, Clustering, and Classification.
The lecture notes of this course and correspondng code for each lecture is provided below.
| Lecture | Note | Code |
|---|---|---|
| Lecture 1: Introduction to Machine Learning | Note | Random Matrices Practice |
| Lecture 2: Mathematical Preliminaries for ML | Note | |
| Lecture 3-5: Linear Regression | Note | Polynomial Regression, Ridge & LASSO, Kernel Regression |
| Lecture 6: Linear Dimensionality Reduction | Note | Linear Dimensionality Reduction |
| Lecture 7: Nonlinear Dimensionality Reduction | Note | Nonlinear Dimensionality Reduction |
| Lecture 8: Clustering and Typical Methods | Note | |
| Lecture 9: Gaussian Mixture Models and EM Algorithm | Note | |
| Lecture 10: Non-parametric Clustering | Note | |
| Lecture 11: Introduction to Classification | Note | |
| Lecture 12: Support Vector Machine | Note | |
| Lecture 13: Decision Tree and Ensemble Learning | Note |