https://github.com/trident09/neural-network-mnist

Mnist dataset number recognition models
https://github.com/trident09/neural-network-mnist

keras mnist scratch

Last synced: 15 days ago
JSON representation

Mnist dataset number recognition models

• Host: GitHub
• URL: https://github.com/trident09/neural-network-mnist
• Owner: Trident09
• Created: 2024-10-23T17:05:51.000Z (16 days ago)
• Default Branch: main
• Last Pushed: 2024-10-23T17:09:21.000Z (16 days ago)
• Last Synced: 2024-10-24T00:37:13.883Z (15 days ago)
• Topics: keras, mnist, scratch
• Language: Jupyter Notebook
• Homepage:
• Size: 1.13 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Neural Network MNIST

This repository contains code for training and evaluating a neural network on the MNIST dataset.

## Table of Contents

- [Introduction](#introduction)

- [Installation](#installation)

- [Usage](#usage)

- [Contributing](#contributing)

- [License](#license)

## Introduction

The MNIST dataset is a collection of 70,000 handwritten digits commonly used for training various image processing systems. This project demonstrates how to build and train a neural network to recognize these digits.

## Installation

To get started, clone the repository and install the required dependencies:

```bash

git clone https://github.com/Trident09/Neural-Network-Mnist.git

cd Neural-Network-Mnist

```

## Usage

To train the neural network, run the following command:

```bash

python train.py

```

To evaluate the trained model, use:

```bash

python main.py

```

for testing the model made from scratch check out the `number-recognition-scratch/minst-dataset-model.ipynb`

## Contributing

Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.

## License

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