COMS W4771y - Machine Learning

Institution:

Barnard College

Subject:

Description:

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). Lect: 3. 3 pts.

Credits:

3.00

Credit Hours:

Prerequisites:

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

www.barnard.edu

Phone Number:

(212) 854-5262

Regional Accreditation:

Middle States Association of Colleges and Schools

Calendar System:

Semester

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