Media Summary: Topics: clustering, hierarchical clustering methods, k-means, mixture of Gaussians Graphical models: junction trees, belief propagation. Note that the first Topics: course logistics, high-level overview of
10 701 Machine Learning Fall 2014 Lecture 20 - Detailed Analysis & Overview
Topics: clustering, hierarchical clustering methods, k-means, mixture of Gaussians Graphical models: junction trees, belief propagation. Note that the first Topics: course logistics, high-level overview of Topics: error bounds for infinite hypothesis spaces, Vapnik–Chervonenkis (VC) dimension, Rademacher complexity Topics: overview of topics that may tested on exam, open Q&A Topics: overview of topics tested on exam, Q&A
Topics: hidden Markov models, forward-backward algorithm, Viterbi algorithm for finding the most probable state sequence, EM ...