CSE 290C: Adv Machin Learning
University of California, Santa Cruz
In-depth study of current research topics in machine learning. Topics vary from year to year but include multi-class learning with boosting and SUM algorithms, belief nets, independent component analysis, MCMC sampling, and advanced clustering methods. Students read and present research papers; theoretical homework in addition to a research project. (Formerly Computer Science 290C.) May be repeated for credit.
Average GPA: 3.92
Grade distribution records: 85 students across 5 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A+ | 25 | 29.4% |
| A | 35 | 41.2% |
| A- | 9 | 10.6% |
| B+ | 5 | 5.9% |
| S | 11 | 12.9% |
Based on 85 student grade records across 5 terms and 3 professors.
Instructors
- Razvan V Marinescu 35 students, Average GPA 3.80
- Yuyin Zhou 26 students, Average GPA 4.00
- Yang Liu 24 students, Average GPA 4.00