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 |
---|---|---|---|---|---|---|---|---|---|
30260D | 048 | Lecture | 5:00-7:20pm | Tuesday | 214 of 230 | Victor Adamchik | SGM124 | ||
30297R | 048 | Discussion | 1:00-1:50pm | Thursday | 24 of 30 | OHE122 | |||
30299R | 048 | Discussion | 2:00-2:50pm | Wednesday | 35 of 40 | SOSB44 | |||
30300R | 048 | Discussion | 3:00-3:50pm | Wednesday | 40 of 40 | WPH207 | |||
30301R | 048 | Discussion | 4:00-4:50pm | Wednesday | 35 of 40 | WPH207 | |||
30302R | 001 | Discussion | 5:00-5:50pm | Wednesday | 24 of 40 | WPH207 | |||
30310R | 048 | Discussion | 12:00-12:50pm | Thursday | 18 of 30 | THH112 | |||
30311R | 048 | Discussion | 2:00-2:50pm | Thursday | 16 of 40 | WPH102 | |||
30312R | 048 | Discussion | 3:00-3:50pm | Thursday | 22 of 30 | WPH202 | |||
30265R | 048 | Quiz | 6:00-8:20pm | Wednesday | 214 of 230 | OFFICE | |||
30213D | 034 | Lecture | 5:00-7:20pm | Tuesday | 14 of 20 | Victor Adamchik | DEN@Viterbi | ||
30264R | 034 | Discussion | 1:00-1:50pm | Thursday | 14 of 20 | DEN@Viterbi | |||
30266R | 034 | Quiz | 6:00-8:20pm | Wednesday | 14 of 20 | DEN@Viterbi |