Applied Machine Learning
Course #: CS 638
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.
Notes:
This course does not assume any prior exposure to machine learning theory or practice.
Pre Requisites:
Offered in:
2026 Fall
| Section | Class Number | Schedule/Time | Instructor | Location | |
|---|---|---|---|---|---|
| 01 | 3230 | MW 4:00 - 5:15 pm |
Babur,Ozgun | Wheatley-Peters W01-0042 | |
|
Session:
Regular
Class Dates:
09/08/2026 - 12/11/2026
Capacity:
17
Enrolled:
1
Status:
Open
Credits:
3/3
Class Notes:
Pre Requisites:
Course Attributes:
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2026 Spring
| Section | Class Number | Schedule/Time | Instructor | Location | |
|---|---|---|---|---|---|
| 01 | 3742 | MW 2:30 - 3:45 pm |
Ding,Wei | University Hall Y01-1350 TEAL | |
|
Session:
Regular
Class Dates:
01/26/2026 - 05/13/2026
Capacity:
15
Enrolled:
9
Status:
Open
Credits:
3/3
Class Notes:
Pre Requisites:
Course Attributes:
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