MSAN 630 - Advanced Machine Learning

Credits: 2

A deeper exploration of the specic properties and algorithms used in machine learning and clustering, with special attention to cutting-edge extensions of the more basic techniques learned in MSAN 621. Examples include k means ++, regularized logistic regression, topic modeling, stratied k-fold sampling, partitioning around medoids, deep learning, etc. Using industry standard machine learning and natural language processing packages, students will learn how to eciently implement advanced applications set in high-dimensional feature spaces, including text mining and image classication.

Restriction: Restricted to Graduate level; Restricted to Analytics Majors SC