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Mar 03, 2026
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EE 4630 - Machine Learning Principles and Application (3)
This course is repeatable: No
Max # of units may be repeated: 0
Total # of units allowed for credit: 3
Max times this course can be taken for credit: 1
Course Description: Review of linear algebra and probability theory, statistical inference, feature extraction, clustering, classification, independent component analysis, time series modeling, regression analysis, curve fitting, model extraction, neural networks, fuzzy logic.
Credit Hours: 3 lecture hour(s) per week
Grading: ABCDF
Mode of Delivery: Face to Face
Campus: Main Campus
Prerequisite(s): (EE 3020 and EE 3040 ) or admission to EE MS program
Needs Permission to Enroll: No
Special Fee Applied: No
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