MNIST Classification Project

This project aims to develop a machine learning model for classifying handwritten digits using the MNIST dataset. The MNIST dataset is a widely used benchmark dataset in the field of machine learning and computer vision. It consists of a large collection of 28x28 pixel grayscale images of handwritten digits (0-9) along with their corresponding labels.

Getting Started

To get started with this project, follow these steps:

1. Clone the repository to your local machine.
2. Install the required dependencies listed in the requirements.txt file.
3. Train the machine learning model using the provided training script.