MSSC 6250 - Statistical Machine Learning (Spring 2025)

The course discuss machine learning from statistical and modeling points of view, covering supervised learning and unsupervised learning models and algorithms. Supervised learning methods include various regression and classification methods, and unsupervised learning methods involves dimension reduction and clustering techniques. Topics include Bayesian linear regression, shrinkage and regularization, regression splines, Gaussian processes, logistic regression, discriminant analysis, nearest neighbors, tree-based methods, principal components, K-means, Gaussian mixture clustering, neural networks, etc.