MNIST Handwritten Digit Classifier Using LeNet-5

A deep learning project implementing LeNet-5 architecture to classify handwritten digits using the MNIST dataset.

Overview

This project builds and trains a Convolutional Neural Network (CNN) based on the LeNet-5 architecture on the MNIST dataset.

Files

• mnist_lenet5.ipynb: Main notebook containing the code.
• requirements.txt: List of dependencies.

Results

Achieved 98.6% accuracy on the test dataset.

How to Run

1. Clone the repository.
2. Install dependencies: pip install -r requirements.txt
3. Open leNet5_implementation.ipynb in Jupyter Notebook or run it on Google Colab.