CSE 142: Machine Learning
University of California, Santa Cruz
Introduction to machine learning algorithms and their applications. Topics include classification learning, density estimation and Bayesian learning regression, and online learning. Provides introduction to standard learning methods such as neural networks, decision trees, boosting, and nearest neighbor techniques.
Average GPA: 3.39
Grade distribution records: 919 students across 12 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A+ | 78 | 8.5% |
| A | 308 | 33.5% |
| A- | 88 | 9.6% |
| B+ | 80 | 8.7% |
| B | 81 | 8.8% |
| B- | 36 | 3.9% |
| C+ | 29 | 3.2% |
| C | 45 | 4.9% |
| C- | 6 | 0.7% |
| D+ | 5 | 0.5% |
| D | 10 | 1.1% |
| D- | 4 | 0.4% |
| F | 15 | 1.6% |
| P | 41 | 4.5% |
| NP | 39 | 4.2% |
| S | 3 | 0.3% |
| W | 51 | 5.5% |
Based on 919 student grade records across 12 terms and 5 professors.
Instructors
- Xin Wang 282 students, Average GPA 2.86
- Alexander J Rudnick 262 students, Average GPA 3.71
- Yang Liu 196 students, Average GPA 3.68
- Snigdha Chaturvedi 93 students, Average GPA 2.98
- Razvan V Marinescu 86 students, Average GPA 3.61