Fall 2023 Computer Science W4771 section 002


Call Number 11241
Day & Time
TR 2:40pm-3:55pm
451 Computer Science Building
Points 3
Grading Mode Standard
Approvals Required None
Instructor Daniel Hsu
Method of Instruction In-Person
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 80 students (110 max) as of 11:06AM Sunday, December 10, 2023
Subject Computer Science
Number W4771
Section 002
Division Interfaculty
Campus Morningside
Section key 20233COMS4771W002