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 | Wed, Fri | 77 of 85 | Sirisha Rambhatla | OHE132 & ONLINE | ||
30081R | 048 | Discussion | TBA | TBA | 77 of 85 | OFFICE & ONLINE | |||
30265R | 048 | Quiz | TBA | TBA | 77 of 85 | OFFICE & ONLINE | |||
30213D | 034 | Lecture | 10:00-11:50am | Wed, Fri | 6 of 15 | Sirisha Rambhatla | DEN@Viterbi | ||
30264R | 034 | Discussion | TBA | TBA | 6 of 15 | DEN@Viterbi | |||
30266R | 034 | Quiz | TBA | TBA | 6 of 15 | DEN@Viterbi |