Introduction to Machine Learning: Class Notes 67577

Abstract

Introduction to Machine learning covering Statistical Inference (Bayes, EM, ML/MaxEnt duality), algebraic and spectral methods (PCA, LDA, CCA, Clustering), and PAC learning (the Formal model, VC dimension, Double Sampling theorem).

109 pages, class notes of Machine Learning course given at the Hebrew University of Jerusalem