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Dec 30, 2024
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CSC 156 - Introduction to Machine LearningSemester Hours: 3
Periodically
The course introduces the mathematical, algorithmic and practical aspects of machine learning. Students will learn how to design applications that learn from data and past experience. Applications include classification, clustering, prediction, decision making. Among topics covered in the class are: regression, neural networks, decision trees, support vector machines, model and feature selection, ensemble methods, boosting, clustering, graphical models.
Prerequisite(s)/Course Notes:
CSC 017 , 185 ; MATH 071 ; or permission of instructor. May not be taken on a Pass/D+/D/Fail basis.
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