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Dec 08, 2024
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CSE 616 - Pattern Recognition and Machine Learning (4 credits)
Introduction to recognition and learning; Bayes decision theory; parametric and nonparametric methods including Hidden Markov models; Discriminant functions including support vector machines; Multilayer neural networks; Decision and regression trees for learning; Performance estimation; Unsupervised learning and clustering; Subspace methods; Application.
Prerequisite(s): Students must meet prerequisites (CSE 506 and CSE 507 or equivalent).
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