Nonuniform Learnability and Structural Risk Minimization

This lecture covers the concept of nonuniform learnability and structural risk minimization, discussing the fundamental theorems of PAC learning, the definition of non-uniformly learnable hypothesis classes, and the relationship between PAC learnable classes and SRM. It also explores the conditions under which a hypothesis class is non-uniformly learnable and the implications of this in machine learning.