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https://github.com/sreeeswaran/handwritten-digit-classification

This project implements a Convolutional Neural Network (CNN) to classify handwritten digits from the MNIST dataset. The model is built using TensorFlow and Keras.
https://github.com/sreeeswaran/handwritten-digit-classification

classification-model cnn cnn-classification cnn-keras deep-learning handwritten-digit-recognition handwritten-text-recognition keras keras-classification-models keras-models keras-tensorflow mnist mnist-classification mnist-dataset mnist-handwriting-recognition tensorflow

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This project implements a Convolutional Neural Network (CNN) to classify handwritten digits from the MNIST dataset. The model is built using TensorFlow and Keras.

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# Handwritten-digit-Classification

This project implements a Convolutional Neural Network (CNN) to classify handwritten digits from the MNIST dataset. The model is built using TensorFlow and Keras.

## Project Structure

- `data`: Contains information on data acquisition.
- `models`: Stores the trained models.
- `notebooks`: Jupyter notebooks for various stages of the project.
- `scripts`: Python scripts for data processing, model building, training, evaluation, and visualization.

## Installation

1. Clone the repository:
```bash
git clone https://github.com/SreeEswaran/Handwritten-digit-Classification.git
cd Handwritten-digit-Classification
```
2. Create a virtual environment and activate it
```bash
python -m venv venv
source venv/bin/activate # On Windows use `venv\Scripts\activate`
```
3. Install the required packages:
```bash
pip install -r requirements.txt
```
4. To run the model
```bash
python scripts/model_training.py
```