PSL_Book
1. Introduction
1.1. Introduction to statistical learning
1.2. Least squares vs. nearest neighbors
1.2.1. Introduction to LS and kNN
1.2.2. Simulation Study
1.2.3. Compute Bayes rule
1.2.4. Discussion
2. Linear Regression
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
1.
Introduction
1.2.
Least squares vs. nearest neighbors
1.2.
Least squares vs. nearest neighbors
1.2.1. Introduction to LS and kNN
1.2.2. Simulation Study
1.2.3. Compute Bayes rule
1.2.4. Discussion