CSE 290D: Neural Computation
University of California, Santa Cruz
An introduction to the design and analysis of neural network algorithms. Concentrates on large artificial neural networks and their applications in pattern recognition, signal processing, and forecasting and control. Topics include Hopfield and Boltzmann machines, perceptions, multilayer feed forward nets, and multilayer recurrent networks. (Formerly Computer Science 290D.) May be repeated for credit.
Average GPA: 3.91
Grade distribution records: 97 students across 4 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A+ | 25 | 25.8% |
| A | 50 | 51.5% |
| A- | 12 | 12.4% |
| B+ | 1 | 1.0% |
| F | 1 | 1.0% |
| S | 8 | 8.2% |
Based on 97 student grade records across 4 terms and 2 professors.
Instructors
- Cihang Xie 77 students, Average GPA 3.89
- Yuyin Zhou 20 students, Average GPA 4.00