Stony Brook University 3 credits AMS
This course will teach the basic ingredients of classical and contemporary statistical data mining methods, including dimension reduction, model selection, pattern recognition, and predictive modeling using traditional general linear models and generalized linear models, and modern statistical learning methods, such as decision trees, random forests, neural networks, etc. This course will teach how to employ these methods with the programming language Python. 3 credits Prerequisite: AMS 210 or MAT 211 or MAT 307 ; AMS 311
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