Lecture
This lecture covers learning bounds for the misclassification error, Rademacher complexities for binary classifiers, Massart's lemma, growth function, shattering, and Vapnik-Chervonenkis dimension. It also includes examples with linear classifiers and rectangles, Sauer's lemma, polynomial upper bound, and learning bound based on VC dimension.