Mar 29, 2024  
2019-2020 Undergraduate Bulletin 
    
2019-2020 Undergraduate Bulletin [ARCHIVED]

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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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