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Statistical Machine Learning

STAT 6500: Statistical Machine Learning

Statistical models and algorithms for supervised and unsupervised learning; linear and logistic regression; classification and LDA; cross-validation and bootstrap; variable selection; ridge and LASSO penalization; smoothing splines and GAMs; SVM and kernels; CART and random forests; bagging; boosting; feed-forward and convolutional neural networks; k-means clustering and Gaussian mixtures; PCA.
Prereq: 6450, or permission of instructor. Not open to students with credit for 7620.
Credit Hours

Typical semesters offered are indicated at the bottom of this page. For confirmation check the Schedule of Classes list on the Registrar's website.

Recent Syllabi

SP19 STAT 6500 Lee [pdf]

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Semester(s) Offered: