SuchitaSri18/AI-Project

MNIST Handwritten Digit Classification

This project implements a deep learning model to classify handwritten digits from the MNIST dataset. The entire process, from data preprocessing to model evaluation, is documented in a Jupyter Notebook.

Table of Contents

• Introduction
• Features
• Usage
• Project Structure

Introduction

The MNIST dataset is a well-known dataset used for training image processing systems. This project uses a neural network to classify these digits with high accuracy. The complete workflow, including the dataset exploration, model training, and evaluation, is contained within the Jupyter Notebook.

Features

• Deep Learning Model: A neural network built with TensorFlow/Keras to classify MNIST digits.
• Interactive Visualization: The Jupyter Notebook includes visualizations of the dataset and the model's performance.

Usage

To explore the project, you can open the Jupyter Notebook available in this repository.

1. Clone the repository:

   git clone https://github.com/SuchitaSri18/AI-Project.git
   cd AI-Project

2. Run the Jupyter Notebook:

   Ensure you have Jupyter Notebook installed, then run:

   jupyter notebook AI_Project_SuchitaSrivastava.ipynb

   You can also view the notebook directly on GitHub here.

Project Structure

AI-Project/
│
├── AI_Project_SuchitaSrivastava.ipynb  # Jupyter Notebook with model training
└── README.md                           # Project README file