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.
4 terms
Other grades
University of California, Santa Cruz
CSE 290D at UCSC: average GPA 3.91 across 97 students. Grade distribution by term. An introduction to the design and analysis of neural network algorithms…
Average GPA: 3.91
Grade distribution records: 97 students across 4 terms.
| 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.
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