Students design and deploy analytical systems that serve as the basis for the analysis, processing, storage, and interface of the machine learing process. Students choose learning models appropriate to the result desired using decision tree, Bayesian, neural net, and vector machine approaches. Students use multiple statistical approaches to evaluate results that lead to best results.
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