This project builds and trains a neural network to recognize handwritten digits from the MNIST dataset.
- Architecture:
- Input layer (784)
- Dense(512, ReLU)
- Dense(256, ReLU)
- Dense(128, ReLU)
- Dropout(0.5)
- Dense(10, Softmax)
The trained model is saved to disk and can predict digits from new images.