Handwritten Digit Classification using Artificial Neural Networks (ANN)

Table of Contents

• Project Overview
• Dataset
• Requirements
• Installation

Project Overview

This project focuses on building and training an Artificial Neural Network (ANN) to classify handwritten digits from the MNIST dataset. The MNIST dataset is a well-known dataset in the machine learning community, containing 60,000 training images and 10,000 testing images of handwritten digits ranging from 0 to 9.

Dataset

The MNIST dataset is available from various sources. For this project, it can be downloaded using popular libraries like TensorFlow or directly from the official website.

Requirements

• Python 3.7 or higher
• TensorFlow
• NumPy
• Pandas
• Matplotlib
• Scikit-learn

Installation

Clone the repository:

git clone https://github.com/yourusername/Handwritten-Digit-Classification-using-ANN.git