CS638: Applied Machine Learning
Credits: 3
Catalog Description
This course presents the practical side of machine learning for applications, such as pattern recognition from images or building predictive classifiers. Topics will include linear models for regression, decision trees, rule based classification, support vector machines, Bayesian networks, and clustering. The emphasis of the course will be on the hands-on application of machine learning to a variety of problems. This course does not assume any prior exposure to machine learning theory or practice.
Current & Upcoming Offerings
2025-2026
Fall 2025 1 section
| Section | Schedule / Time | Instructor | Location |
|---|---|---|---|
| 01 |
MW 04:00PM - 05:15PM
|
Babur, Ozgun |
M01-0207
|
Spring 2026 1 section
| Section | Schedule / Time | Instructor | Location |
|---|---|---|---|
| 01 |
MW 02:30PM - 03:45PM
|
TBA |
M02-0404
|
Prerequisites
Notes
This course is co-taught with CS438.
Graduate course in applied machine learning for graduate students covering practical machine learning methods and applications.