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CSCI 441. Neural Networks

Credits: 3
Department: Computer Science
Description: Natural and artificial neural networks. Back propagation, conjugate gradients, cascade-correlation training methods, associative memory. Self-organizing nets, adaptive resonance nets, Hopfield nets, constraint satisfaction networks. Design and applications.
Prerequisites: CSCI 320
Semester Offered: DEMAND
Grading Method: ABCDF

Student Learning Outcomes

1. Understand the fundamental concepts and methodology of neural networks.
2. Understand the structure, design, and training of various types of neural networks.
3. Gain knowledge in solving real-world problems using neural networks.
4. Understand the advantages and limitations of neural networks.

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