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This project implements a convolutional neural network (CNN) to classify handwritten digits from the MNIST dataset. The model is trained on the MNIST training set and evaluated on the test set. The project demonstrates the application of deep learning techniques for image classification tasks.

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sowada23/Handwritten-Digit-Recognition-Model

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Handwrittena-Digit-Recognition-Model

Description

This project implements a convolutional neural network (CNN) to classify handwritten digits from the MNIST dataset. The model is trained on the MNIST training set and evaluated on the test set. The project demonstrates the application of deep learning techniques for image classification tasks.

Setup & Installation

Make sure you have the latest version of Python installed.

git clone <repo-url>
pip install -r requirements.txt

Running The App

python main.py

About

This project implements a convolutional neural network (CNN) to classify handwritten digits from the MNIST dataset. The model is trained on the MNIST training set and evaluated on the test set. The project demonstrates the application of deep learning techniques for image classification tasks.

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