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Fall 2019 Computer Science W4771 section D02
MACHINE LEARNING

Call Number 18216
Points 3
Grading Mode Standard
Approvals Required None
Instructor Kriste Krstovski
Type LECTURE
Method of Instruction Online 100%
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 Video Network
Enrollment 10 students (99 max) as of 4:04PM Tuesday, February 25, 2020
Subject Computer Science
Number W4771
Section D02
Division Interfaculty
Campus Video Network
Fee $395 CVN Course Fee
Section key 20193COMS4771WD02

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SIS update 02/25/20 16:04    web update 02/25/20 21:19