Lecture 1: Feature vectors and Models
Lecture 2: Maximum Likelihood, Optimization, and Outlier Removal
Lecture 2 supplement: Mixture of Gaussians example and handout
Lecture 3: Bayesian Learning, Binary Data, Beta Distributions
Lecture 4: Bayesian Content Based Image Retrieval [3.8 MB PowerPoint file]