Course Notes
Week 1 — Introduction to Machine Learning
Key Concepts
- Statistical learning framework
- Supervised vs unsupervised learning
- Model complexity and generalization
Reading Materials
- Chapter 1: The Elements of Statistical Learning
- Chapter 2: An Introduction to Statistical Learning
Week 2 — Linear Regression
Key Concepts
- Least squares estimation
- Bias-variance tradeoff
- Model selection
Exercises
- Problem set 1: Linear regression with real data
- Problem set 2: Cross-validation techniques