Image credits go to LeewayHertz@google.

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Simple Neural Network from Scratch

This repository contains a simple implementation of a feedforward neural network from scratch using Python. The neural network is designed to learn and perform logical operations like XOR.

Table of Contents

• Introduction
• Installation
• Usage
• Example
• Contributing
• License

Introduction

The neural network architecture includes classes for Connection, Neuron, and Network. It's a basic implementation to understand the principles of backpropagation and feedforward neural networks.

Installation

To use this implementation, you need Python 3.x installed on your system. Additionally, you will require the numpy library. You can install it via pip:

pip install numpy

Usage

1. Clone the repository:

git clone https://github.com/Transcendental-Programmer/neural-network-from-scratch.git

2. Navigate to the repository directory:

cd neural-network-from-scratch

3. Run the main script:

python neural_network.py

Example

To demonstrate the network's capabilities, we've included an example that trains the network to perform the XOR logical operation.

Contributing

Contributions are welcome! If you find any bugs or have suggestions for improvement, feel free to open an issue or create a pull request.

License

This project is licensed under the MIT License - see the LICENSE file for details.