Uniform convergence and No-Free-Lunch theorem

This lecture covers the concepts of uniform convergence, loss functions, and the No-Free-Lunch theorem in machine learning. It explains the challenges of evaluating the performance of classifiers and the implications of the No-Free-Lunch theorem in the context of learning algorithms.