MATH 450 - Data Analytics

4.00 credit hours

An overview of the field of statistical learning. Survey of techniques for predictive analytics including model selection and validation methods, linear and non-linear models and supervised and unsupervised learning. Implementation of all techniques will employ appropriate software.

Prerequisite(s): MATH 340 and CSCE 160.

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