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 | 1:00-3:20pm | Friday | 170 of 210 | Vatsal Sharan | SGM124 | ||
30081R | 048 | Discussion | 3:30-4:20pm | Friday | 170 of 210 | SGM124 | |||
30265R | 048 | Quiz | TBA | TBA | 170 of 210 | OFFICE | |||
30213D | 034 | Lecture | 1:00-3:20pm | Friday | 8 of 30 | Vatsal Sharan | DEN@Viterbi | ||
30264R | 034 | Discussion | 3:30-4:20pm | Friday | 8 of 30 | DEN@Viterbi | |||
30266R | 034 | Quiz | TBA | TBA | 8 of 30 | DEN@Viterbi |