https://github.com/82luli02/ccai321_artificial_neural_network

https://github.com/82luli02/ccai321_artificial_neural_network

Last synced: 2 months ago
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• Host: GitHub
• URL: https://github.com/82luli02/ccai321_artificial_neural_network
• Owner: 82Luli02
• Created: 2024-09-09T23:55:56.000Z (4 months ago)
• Default Branch: main
• Last Pushed: 2024-09-17T23:23:24.000Z (4 months ago)
• Last Synced: 2024-09-18T03:45:50.680Z (4 months ago)
• Language: Jupyter Notebook
• Size: 1.11 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
## Overview

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.

## Description

- ### Lab 1 

  Introduction to Transfer Functions using Python

- ### Lab 2 

  Building a multiple input Neuron using Python

- ### Lab 3

  Building a Hamming Network using Python

- ### Lab 4

  Implementing Perceptron Learning Rule using Python

- ### Lab 5

  Implementing Supervised Hebb Rule using Python

- ### Lab 6

  Implementing Multilayer Networks using Python 

- ### Lab 7

  Implementing the Backpropagation Algorithm using Python

- ### Lab 8

  Neural Networks using sickit-learn Python

## Tools

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. 

## Date Created

Winter 2023