IEORE4540 Data Mining for Engineers

Fall and Spring 
The course will cover major statistical learning methods for data mining under both supervised and unsupervised settings. Topics covered include linear regression and classi fication, model selection and regularization, tree-based methods, support vector machines, and unsupervised learning. Students will learn about the principles underlying each method, how to determine which methods are most suited to applied settings, concepts behind model fi tting and parameter tuning, and how to apply methods in practice and assess their performance. We will emphasize roles of statistical modeling and optimization in data mining.

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