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EECE 592 Architecture for Learning Systems

Learning in neural networks; error backpropagation, simulated annealing, content addressable memories. Data representation topics. Reinforcement learning (RL). Implementation challenges in real world scale problems. Architectures for function approximation in RL. Comparison with conventional AI; history and emerging trends.

This course is not eligible for Credit/D/Fail grading.

Credits: 3


Status Section Activity Term Interval Days Start Time End Time Comments
Full EECE 592 101 Lecture 1 Wed 18:00 21:00