Applied Machine Learning
Course #: CS 438
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: Pre-req: CS 310
Offered in:
2024 Fall
| Section | Class Number | Schedule/Time | Instructor | Location | |
|---|---|---|---|---|---|
| 01 | 3632 | MW 4:00 - 5:15 pm |
Babur,Ozgun | McCormack M02-0208 | |
|
Session:
Regular
Class Dates:
09/03/2024 - 12/13/2024
Capacity:
18
Enrolled:
14
Status:
Open
Credits:
3/3
Class Notes:
Pre Requisites:
Pre-req: CS 310
Course Attributes:
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2025 Spring
| Section | Class Number | Schedule/Time | Instructor | Location | |
|---|---|---|---|---|---|
| 01 | 9478 | MW 5:30 - 6:45 pm |
TBD | HLL-3507 Media Auditorium | |
|
Session:
Regular
Class Dates:
01/27/2025 - 05/14/2025
Capacity:
22
Enrolled:
0
Status:
Open
Credits:
3/3
Class Notes:
Pre Requisites:
Pre-req: CS 310
Course Attributes:
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