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Sep 30, 2024
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MSCS-335 Machine Learning (3 cr.) Repeatable for Credit: No Methods for supervised learning of labelled data sets, and unsupervised learning of unlabelled data sets. Theory, application, and validation of models, including linear-subset, nearest-neighbor, support-vector machines, forests, neural networks, and other geometric methods. Prerequisites: take CS 145 , MATH 158 , MATH 275 , and either STAT 330 or STAT 331 .
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