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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
3

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:

Spring