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 |
|---|---|---|---|---|---|---|---|---|---|
| 30079R | 048 | Lecture | 1:00-3:20pm | Friday | 125 of 190 | Haipeng Luo | SGM124 |  | |
| 30081R | 048 | Discussion | 3:30-4:20pm | Friday | 125 of 190 | SGM124 | | ||
| 30265R | 048 | Quiz | TBA | TBA | 125 of 190 | OFFICE | | ||
| 30213D | 034 | Lecture | 1:00-3:20pm | Friday | 13 of 30 | Haipeng Luo | DEN@Viterbi | | |
| 30264R | 034 | Discussion | 3:30-4:20pm | Friday | 13 of 30 | DEN@Viterbi | | ||
| 30266R | 034 | Quiz | TBA | TBA | 13 of 30 | DEN@Viterbi | |