Summer 2025 Computer Science W3770 section 001

Mathematics for Machine Learning

MATH FOR MACHINE LEARNING

Call Number 10757
Day & Time
Location		 TR 5:30pm-8:40pm
To be announced
Points 3
Grading Mode Standard
Approvals Required None
Instructors Samuel Deng
Tony B Dear
Type LECTURE
Method of Instruction In-Person
Course Description

Mathematical foundations of machine learning: Linear algebra, multivariable calculus, and probability and statistics. Comprehensive review and additional treatment of
relevant topics used in the analysis and design of machine learning models. Preliminary exposure to core algorithms such as linear regression, gradient descent, principal
component analysis, low-rank approximations, and kernel methods.

Web Site Vergil
Subterm 05/27-07/03 (A)
Department Computer Science
Enrollment 16 students (120 max) as of 5:06PM Tuesday, April 22, 2025
Subject Computer Science
Number W3770
Section 001
Division School of Engineering and Applied Science: Undergrad
Section key 20252COMS3770W001