Multi-Layer Perceptron for Digit Classification
A multi-layer perceptron (MLP) model for digit classification using the MNIST dataset. The model is trained using the backpropagation algorithm and achieves high accuracy in classifying handwritten digits. The project demonstrates the implementation of a neural network for image recognition tasks using pytorch.