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hebbian-learning-rule

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This repository is dedicated to the lab work completed for the CCAI 321 course. It demonstrates practical work in artificial neural networks, including the implementation of activation functions, Hamming networks, perceptron and Hebb learning rules, and two-layer networks in Python. Networks were trained and tested on both examples and real data.

  • Updated Oct 2, 2024
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