Catalog Entries |
Fall 2025 Semester
Oct 17, 2026 |
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| EECE 5644 - Introduction to Machine Learning and Pattern Recognition |
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Studies machine learning (the study and design of algorithms that enable computers/machines to learn from experience/data). Covers a range of algorithms, focusing on the underlying models between each approach. Emphasizes the foundations to prepare students for research in machine learning. Topics include Bayes decision theory, maximum likelihood parameter estimation, model selection, mixture density estimation, support vector machines, neural networks, probabilistic graphics models, and ensemble methods (boosting and bagging). Offers students an opportunity to learn where and how to apply machine learning algorithms and why they work.
4.000 Credit hours 4.000 Lecture hours Levels: Graduate, Undergraduate Schedule Types: Lecture Electrical and Comp Engineerng Department Course Attributes: GSEN Engineering |
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