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Apr 20, 2024
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CPSC 428 - Applied Machine Learning 3 Credit Hours
This course explores the basic ideas, principles and methods of machine learning along with some of the social and ethical issues that can arise from the widespread use of this technology. This hands-on application-oriented course will cover the terminology and underlying concepts of machine learning using mostly Python, scikit-learn, and various scientific libraries. The focus of the course is broad, rather than narrow, providing a survey of the machine learning landscape. Topics include supervised vs unsupervised learning, classification and regression, model selection, training and evaluation. Algorithms covered include Linear and Logistic Regression, K-Means clustering, K-Nearest Neighbors, and Decision Trees, among others.
Prerequisite(s): CPSC 275
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