2024-2025 Undergraduate Catalogue
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STT 450 - Statistical Machine Learning Introduction to fundamental principles and applications of machine learning techniques. Topics include linear regression, classification, re-sampling methods, model selection, tree-based classification methods, and Support Vector Machines (SVM). Students learn how to analyze large/high-dimensional real-world application data to build effective machine learning systems using standard programming tools.
Credit Hours: 3
Prerequisite Courses: STT 215. Additional Restrictions/Requirements: Prerequisite course and 3 hours of statistics or data science at the 300 level, or consent of instructor. Course Repeatability: Course may not be repeated.
Click here for the Spring 2025 Class Schedule.
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