CS 229: Machine Learning

← 2011-12 2012-13 2013-14 →
← 2011-12 ← 2011-12 changes (lax) changes (strict) ▾ 2013-14 → 2013-14 →

Units: 4

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

Catalog page 205

Prerequisites: CS 141, STAT 160A

Description: A study of supervised machine learning that emphasizes discriminative 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. Computer Science and Engineering 206 / Programs and Courses

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