ML 20
- ML M1: Introduction
- ML M2: Decision Trees
- ML M3: Regression
- ML M4: Neural Networks
- ML M5: Instance-Based Learning
- ML M7: Kernel Methods and SVMs
- ML M6: Ensemble Learning
- ML M8: Computational Learning Theory
- ML M9: VC Dimension
- ML M10: Bayesian Learning
- ML M11: Randomized Optimization
- ML M11: Bayesian Inference
- ML M12: Clustering
- ML M13: Feature Selection
- ML M14: Feature Extraction
- ML M15: Information Theory
- ML M16: Markov Decision Processes
- ML M17: Reinforcement Learning
- ML M18: Game Theory (Part 1)
- ML M19: Game Theory (Part 2)