ECE 186: PROB MACH LEARN
University of California, Santa Barbara
An introductory course to topics in machine learning studied from a probabi lity theory viewpoint. Covers an overview of basic probability, inference a nd estimation, regression algorithms, Markov chains, inference for Markov m odels and the EM algorithm, Markov decision process, and reinforcement lear ning. In addition to covering mathematical and algorithmic details, the cou rse includes several hands-on projects to implement the machine learning al gorithms.
Average GPA: 3.59
Grade distribution records: 29 students across 1 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A+ | 3 | 10.3% |
| A | 9 | 31.0% |
| A- | 7 | 24.1% |
| B+ | 5 | 17.2% |
| B | 2 | 6.9% |
| B- | 2 | 6.9% |
| C+ | 1 | 3.4% |
Based on 29 student grade records across 1 term and 1 professor.
Instructors
- Pedarsani R 29 students, Average GPA 3.59