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Fall 2019 Computer Science W4771 section H02

Call Number 17928
Points 3
Grading Mode Standard
Approvals Required None
Instructor Rocco Servedio
Method of Instruction Classroom
Course Description 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. 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.
Web Site Vergil
Department Computer Science
Enrollment 57 students (100 max) as of 3:03PM Wednesday, February 19, 2020
Status Full
Subject Computer Science
Number W4771
Section H02
Division Interfaculty
Campus Morningside
Section key 20193COMS4771WH02

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SIS update 02/19/20 15:03    web update 02/19/20 20:21