  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).
