COMS W 4771y Machine Learning
Topics from generative and discriminative machine learning including least
squares methods, support vector machines, kernel methods, neural networks,
Gaussian distributions, linear classification, linear regression, maximum
likelihood, exponential family distributions, Bayesian networks, Bayesian
inference, mixture models, the EM algorithm, graphical models and hidden
Markov models. Algorithms implemented in Matlab. - T. Jebara
Prerequisites: Any introductory course in linear algebra and any introductory course in statistics are both required. Highly recommended: COMS W4701 or knowledge of Artificial Intelligence. General Education Requirement: Quantitative and Deductive Reasoning (QUA).
3 points Lect: 3.