Syllabus
Textbook:
1. An Introduction to Statistical Learning with Applications in R
2. The elements of statistical learning
Slides:
1. Introduction
2. Statistical Learning
3. Linear Regression
4. Classification
5. Resampling Methods
6. Linear Model Selection and Regularization
7. Moving Beyond Linearity
8. Tree-Based Methods
9. Support Vector Machines
10. Unsupervised Learning
11. Deep Learning
Homework:
HW1
HW2
HW3
HW4
HW5
Project