Course Websites

CS 307 - Model & Learning in Data Sci

Last offered Fall 2022

Official Description

Introduction to the use of classical approaches in data modeling and machine learning in the context of solving data-centric problems. A broad coverage of fundamental models is presented, including linear models, unsupervised learning, supervised learning, and deep learning. A significant emphasis is placed on the application of the models in Python and the interpretability of the results. Course Information: Prerequisite: STAT 207; one of MATH 225, MATH 257, MATH 415, MATH 416, ASRM 406.

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Course Director

Model & Learning in Data SciD177587DIS00930 - 1045 F  1302 Siebel Center for Comp Sci Mahesh Viswanathan
Model & Learning in Data SciMLD77586LEC40930 - 1045 M W  1302 Siebel Center for Comp Sci Mahesh Viswanathan