University of Calgary

ENEL 525 - Machine Learning for Engineers - Fall 2019

Neural networks: neuron models and network architectures, perceptrons, Widrow-Hoff learning and backpropagation algorithm, associative memory, Hebbian learning, pseudo-inverse learning. Fuzzy systems: basic operations and properties of fuzzy sets; fuzzy rule generation and defuzzification of fuzzy logic; fuzzy neural networks. Applications such as pattern recognition, character recognition, stock market prediction and control.
This course may not be repeated for credit.

Hours

  • H(3-2)

Prerequisite(s)

  • Electrical Engineering 327.

Sections

This course will be offered next in Fall 2020.
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