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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:

2023 Fall

Section Class Number Schedule/Time Instructor Location
01 3851 MW
4:00 - 5:15 pm
Babur,Ozgun McCormack M01-0409
Session: Regular
Class Dates: 09/05/2023 - 12/13/2023
Capacity: 18
Enrolled: 17
Status: Open
Credits: 3/3
Class Notes:
Pre Requisites: Pre-req: CS 310
Course Attributes:

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: 11
Status: Open
Credits: 3/3
Class Notes:
Pre Requisites: Pre-req: CS 310
Course Attributes:

2024 Spring

Section Class Number Schedule/Time Instructor Location
01 10068 MW
5:30 - 6:45 pm
Ding,Wei Wheatley W01-0005
Session: Regular
Class Dates: 01/22/2024 - 05/08/2024
Capacity: 22
Enrolled: 22
Status: Closed
Credits: 3/3
Class Notes:
Pre Requisites: Pre-req: CS 310
Course Attributes:

2024 Summer

Section Class Number Schedule/Time Instructor Location
01 3873 MW
6:00 - 9:00 pm
Chaudhari,Karmesh Siddharam
Session: SS2 6W
Class Dates: 07/15/2024 - 08/22/2024
Capacity: 25
Enrolled: 1
Status: Open
Credits: 3/3
Class Notes:
Pre Requisites: Pre-req: CS 310
Course Attributes: