-Image-Classification-with-PyTorch-and-CIFAR-10-dataset

PyTorch CIFAR-10 Image Classification

This repository contains code for image classification using a Convolutional Neural Network (CNN) in PyTorch. The model is trained on the CIFAR-10 dataset, which consists of 60,000 32x32 color images in 10 different classes.

Getting Started

Prerequisites

• Python 3.x
• PyTorch
• torchvision
• numpy
• matplotlib

Installation

1. Clone this repository:

   git clone https://github.com/mohamed-stifi/-Image-Classification-with-PyTorch-and-CIFAR-10-dataset.git
   

2. Navigate to the project directory:

   cd -Image-Classification-with-PyTorch-and-CIFAR-10-dataset
   

Contributing

If you'd like to contribute to this project, please follow these guidelines:

1. Fork the repository: Click the "Fork" button on the top right of the repository's page. This will create a copy of the project in your GitHub account.

2. Create a new branch: After forking the repository, create a new branch in your forked repository. You can do this by clicking on the "Branch" button and providing a name for your new branch.

3. Make your changes: Make the necessary changes or improvements to the code, documentation, or other project components in your newly created branch.

4. Submit a pull request: Once you're done with your changes, navigate to the original repository (the one you forked from). GitHub will detect your recent branch and suggest creating a pull request. Follow the prompts to create the pull request. Please provide a clear and concise description of your changes and any context that might be helpful.

The project maintainers will review your pull request and provide feedback. Thank you for contributing to the project!