Material covered

• Administrative details
• Course motivation and applications
• Formalizing a learning task, experience, reward
• Unsupervised learning example -- image segmentation
• Supervised learning example -- handwriting recognition
• Regression and classification
• Loss functions, square loss, 0/1 loss
• Fitting polynomials, overfitting, regularization
• Bayesian learning, prior, posterior, prediction

Homework

(Will be collected into formal homeworks soon.)