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 |
|---|---|---|---|---|---|---|---|---|---|
| 30585R | 906 | Lecture | 12:00-1:50pm | TuWTh | 5 of 30 | Mohammad Reza Rajati | OHE120 | PDF (242102 KB) |  |
| 30589D | 911 | Lecture | 12:00-1:50pm | TuWTh | 2 of 20 | Mohammad Reza Rajati | DEN@Viterbi | PDF (242102 KB) | |
| 30587R | 906 | Discussion | 2:00-2:50pm | Friday | 5 of 30 | OHE120 | | ||
| 30590R | 911 | Discussion | 2:00-2:50pm | Friday | 2 of 20 | DEN@Viterbi | |