PSL_Book
1. Introduction
2. Linear Regression
2.1. Multiple linear regression
2.2. Geometric interpretation
2.3. Practical issues
3. Variable Selection and Regularization
4. Regression Trees and Ensemble
5. Nonlinear Regression
6. Clustering Analysis
7. Latent Structure Models
8. TBA
9. Discriminant Analysis
10. Logistic Regression
11. Support Vector Machine
12. Classification Trees and Boosting
13. Recommender System
PSL_Book
2.
Linear Regression
2.
Linear Regression
2.1. Multiple linear regression
2.2. Geometric interpretation
2.3. Practical issues