Data Representations: Learning Methods

This lecture covers the concept of data representations, focusing on polynomial feature expansion, kernel functions, the representer theorem, kernel regression, and kernel SVM. It also discusses the importance of choosing functions for feature expansion and the use of kernels to circumvent this choice.