MNIST Digit Recognizer

A neural network implemented from scratch using NumPy. It is trained to classify handwritten digits from the MNIST dataset.

Fully connected layers with ReLU activations and softmax output

Vectorized operations for efficiency

No ML libraries used (e.g., PyTorch, TensorFlow)

Designed for learning and understanding neural networks from the ground up.