PSL_Book
1. Introduction
1.1. Introduction to statistical learning
1.1.1. Types of statistical learning problems
1.1.2. Challenge of supervised learning
1.1.3. Curse of dimensionality
1.1.4. A Glimpse of Learning Theory
1.1.5. Bias and variance tradeoff
1.2. Least squares vs. nearest neighbors
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
1.1.
Introduction to statistical learning
1.1.4.
A Glimpse of Learning Theory
1.1.4.
A Glimpse of Learning Theory
Check slides:
lec_W1.3_Introduction_LearningTheory.pdf