Metadata-Version: 2.1
Name: barebonesnn
Version: 0.1.1
Summary: A neural network library built from scratch.
Home-page: https://github.com/AmirMohammadiKarbalaei/BareBonesNN/barebonesnn
Author: Amir Mohammadikarbalaei
Author-email: a.mohammadikarbalaei@gmail.com
Requires-Python: >=3.6
License-File: LICENSE
Requires-Dist: numpy >=1.21.0

**BareBonesNN** is a lightweight neural network library implemented from scratch in Python, without relying on high-level machine learning libraries. This project aims to provide a clear and fundamental understanding of neural network concepts and operations, making it an excellent educational resource for learning and experimentation.

## Features

- **Basic Neural Network Components**: Core classes including `Value`, `Neuron`, `Layer`, and `MLP` (Multi-Layer Perceptron).
- **Automatic Differentiation**: Built-in backpropagation for gradient computation.
- **Customisable and Extensible**: Easily modify and extend the code to experiment with various neural network architectures.
- **Lightweight**: Minimal dependencies, focusing on core principles.

## Installation

To install BareBonesNN, use pip:

```bash
pip install barebonesnn==0.1.0
```

## Contributing

Contributions are welcome! If you have suggestions, bug reports, or feature requests, please open an issue or submit a pull request.

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
