In this course, the student learns the algorithms, tools, and techniques used in modern machine learning applications. Approaches covered include regressions; decision trees and forests of trees; nearest neighbor; and ANNs, CNNs, RNNs, GANs, and SCVMs. The entire ML life cycle is considered, ranging from exploratory data analysis, data preparation, and proper evaluation of learned models.
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School
School of Engineering and Computing
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Number
5320
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Subject
Computer (CIS)
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Semester
As Required
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Lecture/Lab/Seminar Hours
3 hours of lecture per week
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Prerequisites
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Credits
3