Industrial and Systems Engineering 568:
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.
- Crosslist: This course is offered by the CSCI department but may qualify for major credit in ISE. To register, enroll in CSCI 567.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 29995D | 048 | Lecture | 1:00-3:20pm | Friday | 243 of 330 | Dani Yogatama | SGM123 |  | |
| 30151R | 048 | Discussion | 3:30-4:20pm | Friday | 243 of 330 | SGM123 | | ||
| 29984R | 048 | Quiz | TBA | TBA | 243 of 330 | OFFICE | | ||
| 30259D | 034 | Lecture | 1:00-3:20pm | Friday | 15 of 30 | Dani Yogatama | DEN@Viterbi | | |
| 30272R | 034 | Discussion | 3:30-4:20pm | Friday | 15 of 30 | DEN@Viterbi | | ||
| 29985R | 034 | Quiz | TBA | TBA | 15 of 30 | DEN@Viterbi | |