• Resource: Elements of Statistical Learning (Hastie, Tibshirani, and Friedman)
• Topics Covered:
  • Chapter 3: Linear Regression
  • Chapter 4: Linear Classification
  • Chapter 6: Kernel Methods
  • Chapter 7: Model Assessment and Selection
  • Chapter 8: Model Inference and Averaging
  • Chapter 9: Additive Models, Trees, and Related Methods
  • Chapter 10: Boosting and Additive Trees
  • Chapter 15: Random Forests