MATH 253 - Statistical Computing and Machine Learning

Statistics as applied to “big data,” including large numbers of variables. The linear and logistic modeling techniques from Math 155 will be augmented with computer-based methods of data exploration, visualization, data mining, supervised and unsupervised clustering, and other techniques central to machine learning. The course also deals with methods of combining and organizing data from diverse sources and the high-level statistical computer programming needed to carry out sophisticated data analysis and graphical presentation. Prerequisite(s): MATH 155

Every semester (4 Credits)

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