Digit Recognition System is a machine learning project that recognizes handwritten digits using the MNIST dataset. It employs popular machine learning algorithms such as Support Vector Machines (SVMs) and Convolutional Neural Networks (CNNs) to classify handwritten digits with high accuracy.

To use the Digit Recognition System project, you'll need to follow these steps:

1. Clone the repository to your local machine using git clone https://github.com/your-username/digit-recognition-system.git
2. Create a virtual environment for the project using python -m venv venv
3. Activate the virtual environment using source venv/bin/activate on Mac/Linux or venv\Scripts\activate on Windows
4. Install the necessary dependencies using pip install -r requirements.txt

To use the Digit Recognition System project, follow these steps:

1. Open the command line interface and navigate to the project directory.
2. Activate the virtual environment using source venv/bin/activate on Mac/Linux or venv\Scripts\activate on Windows.
3. Start the application by running python main.py.
4. Enter the path to an image of a handwritten digit when prompted.
5. The application will display the predicted digit.

If you'd like to contribute to the Digit Recognition System project, here are some ways you can get started:

• Test the application and report any bugs or issues you encounter.
• Help improve the accuracy of the machine learning algorithms by experimenting with different models or techniques.
• Add new features or functionality to the application.

To contribute to the project, simply fork the repository, make your changes, and submit a pull request.

• requirements.txt
• Anaconda/Condas
• Tensorflow
• SciKit
• Keras
• Pillow
• USPS Dataset

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