CSE 290DNeural Computation
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.)
Enrollment is restricted to graduate students.
Find a section and add it to your scheduleLive seat counts, time-conflict checks and the walk from your previous class.
When it runs
Winter 2027Open Winter 2027
| Section | Type | When | Where | Instructor | Seats |
|---|---|---|---|---|---|
| 01 | Lecture | Asynchronous | — | C. Xie | Open 0/30 |
Fall 2025Open Fall 2025
| Section | Type | When | Where | Instructor | Seats |
|---|---|---|---|---|---|
| 01 | Lecture | Tue Thu 9:50am–11:25am | PhysSciences 136 | C. Xie | Open 32/33 |
Who teaches it
| Instructor | Rating | Difficulty | Would take again | Reviews |
|---|---|---|---|---|
| CiHang Xie | 2.8 / 5 | 2.6 / 5 | 45% | 11 |
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