Description: Survey of ideas, methods, and tools for analyzing large data sets. Topics from supervised and unsupervised learning include penalized regression and classification, support vector machines, kernel methods, model selection, matrix factorizations and completion, graphical models, clustering, boosting and ensemble learning. STAT 640 will have advanced assignments and exams focusing on theory and methods. Cross-list: STAT 444. Mutually Exclusive: Cannot register for STAT 640 if student has credit for STAT 444.