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. Prerequisite: Prerequisite: Statistical Science 210 and (Statistical Science 240L or 230 or 231).
Prerequisite: STA 210 and (STA 240L OR 230 OR 231)