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STA 325L

Machine Learning and Data Mining

1 credits · Undergraduate

The rapid growth of digitalized data and the computer power available to analyze it has created immense opportunities for both machine learning and data mining. This course introduces machine learning and data mining methods. Topics covered include information retrieval, clustering, classification, modern regression, cross validation, boosting, and bagging. Course emphasizes selection of appropriate methods and justification of choice, use of programming for implementation of the method, and evaluation and effective communication of results in data analysis reports.

Topics

Topics explicitly listed in official catalogue description

Prerequisites & course information

004368

Sources