Computer Science 567:
Machine Learning (4.0 units)
Statistical methods for building intelligent and adaptive systems that improve performance from experiences; Focus on theoretical understanding of these methods and their computational implications. Recommended preparation: Undergraduate level training or coursework in linear algebra, multivariate calculus, basic probability and statistics; an undergraduate level course in Artificial Intelligence may be helpful but is not required.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 30079D | 048 | Lecture | 10:00-11:50am | Mon, Wed | 71 of 85 | Yan Liu | OHE132 |   | |
| 30081R | 048 | Discussion | TBA | TBA | 71 of 85 | OFFICE | | ||
| 30265R | 048 | Quiz | TBA | TBA | 71 of 85 | OFFICE | | ||
| 30213D | 034 | Lecture | 10:00-11:50am | Mon, Wed | 17 of 30 | Yan Liu | DEN@Viterbi | | |
| 30264R | 034 | Discussion | TBA | TBA | 17 of 30 | DEN@Viterbi | | ||
| 30266R | 034 | Quiz | TBA | TBA | 17 of 30 | DEN@Viterbi | | ||
| 30339D | 048 | Lecture | 10:00-11:50am | Mon, Wed | 124 of 150 | Yan Liu | ONLINE | | |
| 30344R | 048 | Discussion | TBA | TBA | 124 of 150 | OFFICE | | ||
| 30345R | 048 | Quiz | TBA | TBA | 124 of 150 | OFFICE | |