The current course materials include ...
Precursors: |
Introduction to Statistical Learning: |
Linear Regression: |
Classification: |
Resampling Methods: |
Linear Model Selection and Regularization: |
Moving Beyond Linearity: |
Tree-Based Methods: |
Support Vector Machines: |
Unsupervised Learning: |
Neural Networks and Genetic Algorithms: |