ECE 283: MACHINE LEARNING
University of California, Santa Barbara
Machine learning algorithms from a signal processing viewpoint; unsupervised learning (K-means, deterministic annealing, EM algorithm); supervised learning (Support Vector Machines, neural networks); regression; Bayesian inference and tracking using Markov chain Monte Carlo and sequential Monte Carlo (particle filter) techniques.
Average GPA: 3.82
Grade distribution records: 205 students across 8 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A+ | 33 | 16.1% |
| A | 112 | 54.6% |
| A- | 40 | 19.5% |
| B+ | 16 | 7.8% |
| B | 1 | 0.5% |
| F | 3 | 1.5% |
Based on 205 student grade records across 8 terms and 2 professors.