CS 229: Machine Learning

← 2010-11 2011-12 2012-13 →
← 2010-11 changes (lax) changes (strict) ▾ 2012-13 → 2012-13 →

Units: 4

Hours: Lecture, 3 hours; outside research, 3 hours

Catalog page 209

Prerequisites: CS 141, STAT 160A

Description: A study of supervised machine learning that emphasizes dis- criminative methods. Covers the areas of regression and classification. Topics include linear methods, instance- based learning, neural networks, kernel machines, and additive models. May be taken Satisfactory (S) or No Credit (NC) by students advanced to candidacy for the Ph.D.

Derived Information — The following is not part of the official catalog but is computed from catalog data.
Prerequisite graph not available.

Referenced in

Enrollment History (from UCR Banner, not catalog)
Combined: CS 229 / EE 242B
Year F W S Su Total
2025-26  52/ 65  52/ 65
2024-25  42/100  42/100
2023-24 125/125 125/125
2022-23  59/ 80  59/ 80
2020-21  11/100  11/100
2019-20  47/ 90  47/ 90
2018-19  67/118  67/118
2016-17 49/50  49/ 50