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Summer 2021 Computer Science W4771 section 001

Call Number 11365
Day & Time
TR 1:10pm-3:40pm
Points 3
Grading Mode Standard
Approvals Required None
Instructor Nakul Verma
Method of Instruction On-Line Only
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
Subterm 05/03-06/14 (A)
Department Computer Science
Enrollment 120 students (120 max) as of 3:03PM Wednesday, April 21, 2021
Status Full
Subject Computer Science
Number W4771
Section 001
Division Interfaculty
Campus Morningside
Section key 20212COMS4771W001

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SIS update 04/21/21 15:03    web update 04/21/21 15:21