This repository contains all the labs I completed during the CCAI 321 Course on Artificial Neural Network. The course consisted of 8 labs focused on building, training, and testing neural networks, exploring various architectures, learning rules, and activation functions.
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Introduction to Transfer Functions using Python
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Building a multiple input Neuron using Python
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Building a Hamming Network using Python
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Implementing Perceptron Learning Rule using Python
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Implementing Supervised Hebb Rule using Python
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Implementing Multilayer Networks using Python
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Implementing the Backpropagation Algorithm using Python
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Neural Networks using sickit-learn Python
Python: Used for implementing neural networks and various learning algorithms.
scikit-learn: Utilized for training and testing the networks on both toy and real datasets.
Kaggle: Used as a platform for testing and experimenting with code in an interactive environment.
Winter 2023