Computer Science 559:
Machine Learning I: Supervised Methods (4.0 units)
Distribution-free and probabilistic methods for supervised classification and regression; learning algorithms; optimization techniques; feature-space transformations; parametric and nonparametric methods; Bayes decision theory; artificial neural networks.
- Corequisite: EE 503 and EE 510
- Crosslist: This course is offered by the EE department but may qualify for major credit in CSCI. To register, enroll in EE 559.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 30490R | 048 | Lecture | 4:00-5:50pm | Mon, Wed | 101 of 115 | Keith Jenkins | OHE122 | PDF (405498 KB) |   |
| 30561D | 034 | Lecture | 4:00-5:50pm | Mon, Wed | 9 of 20 | Keith Jenkins | DEN@Viterbi | PDF (405498 KB) | |
| 30565R | 048 | Discussion | 11:00-11:50am | Friday | 101 of 115 | Keith Jenkins | OHE122 | | |
| 30489D | 034 | Discussion | 11:00-11:50am | Friday | 9 of 20 | Keith Jenkins | DEN@Viterbi | |