CS 307
CS 307 - Model & Learning in Data Sci
Fall 2023
Title | Rubric | Section | CRN | Type | Hours | Times | Days | Location | Instructor |
---|---|---|---|---|---|---|---|---|---|
Model & Learning in Data Sci | CS307 | D1 | 77587 | DIS | 0 | 0930 - 1045 | F | 1302 Everitt Laboratory | David M Dalpiaz |
Model & Learning in Data Sci | CS307 | MLD | 77586 | LEC | 4 | 0930 - 1045 | M W | 1302 Everitt Laboratory | David M Dalpiaz |
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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 227, MATH 257, MATH 415, MATH 416, ASRM 406.