MNIST Digit Classifier

This project demonstrates how to classify handwritten digits using a neural network trained on the MNIST dataset.

Features

• Preprocesses images for input into the neural network.
• Trains a simple feedforward neural network using TensorFlow/Keras.
• Supports testing with custom handwritten digit images.

Installation

1. Clone the repository:

   git clone https://github.com/ShouqSaadRu/mnist-digit-classifier.git
   cd mnist-digit-classifier
   
   

2. Install dependencies: pip install tensorflow numpy pillow matplotlib

Testing with a Handwritten Image:

I tested the model with this custom handwritten image:

The model correctly predicted the digit as 5. This shows the neural network works well with user-provided input after proper preprocessing.

How to Test Your Own Image: Save your handwritten digit as 28x28 pixels, black digit on a white background. Place the image in the project folder and run this code:

custom_image = preprocess_custom_image("your_image.png") prediction = model.predict(custom_image) print(f"Predicted digit: {np.argmax(prediction)}")