Summer 2023 Computer Science W4771 section 002

MACHINE LEARNING

Call Number 10978
Day & Time
Location
TR 1:00pm-4:10pm
To be announced
Points 3
Grading Mode Standard
Approvals Required None
Instructor Nakul Verma
Type LECTURE
Course 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.

Web Site Vergil
Subterm 07/03-08/11 (B)
Department Computer Science
Enrollment 28 students (120 max) as of 9:07PM Monday, July 22, 2024
Subject Computer Science
Number W4771
Section 002
Division Interfaculty
Campus Morningside
Section key 20232COMS4771W002