CS 307 - Model & Learning in Data Sci
|Model & Learning in Data Sci||CS307||AB1||73189||LAB||0||1400 - 1450||T||1105 Siebel Center for Comp Sci||Bo Li|
|Model & Learning in Data Sci||CS307||AL1||71618||LCD||4||1100 - 1215||W F||112 Transportation Building||Bo Li|
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.