Call Number | 15258 |
---|---|
Day & Time Location |
MW 2:40pm-3:55pm 702 Hamilton Hall |
Points | 3 |
Grading Mode | Standard |
Approvals Required | None |
Instructor | Genevera Allen |
Type | LECTURE |
Method of Instruction | In-Person |
Course Description | Probabilistic Models and Machine Learning is a PhD-level course about how to design and use probability models. We study their mathematical properties, algorithms for computing with them, and applications to real problems. We study both the foundations and modern methods in this field. Our goals are to understand probabilistic modeling, to begin research that makes contributions to this field, and to develop good practices for building and applying probabilistic models. |
Web Site | Vergil |
Department | Statistics |
Enrollment | 29 students (100 max) as of 9:14PM Wednesday, November 20, 2024 |
Subject | Statistics-Computer Science |
Number | GR6701 |
Section | 001 |
Division | Graduate School of Arts and Sciences |
Open To | Engineering:Graduate, GSAS |
Note | PhD students only. |
Section key | 20243STCS6701G001 |