MNIST Digit Recognizer

A deep learning project to recognize handwritten digits (0–9) using the MNIST dataset and a Convolutional Neural Network (CNN) built with TensorFlow/Keras.

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Features

• Preprocessing of image data (normalization, reshaping)
• Training a CNN with 32 convolution filters
• Achieves ~98% test accuracy
• Prediction visualization on sample digits
• Model saved as model.h5

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Project Structure

src/ ├── mnist_train.py # Train the model └── mnist_predict.py # Run predictions and generate sample images outputs/ ├── model.h5 # Trained model ├── training_history.png # Training loss/accuracy graphs └── sample_predictions.png # Prediction visualization

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Results

Sample Predictions

Training History

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Installation

pip install -r requirements.txt

Run

python src/mnist_train.py
python src/mnist_predict.py

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License

This project is licensed under the MIT License.