Using the MNIST dataset which consists of greyscale handwritten digits. It contains 70,000 images of handwritten digits: 60,000 for training and 10,000 for testing. Each image is 28x28 pixels. Building a basic neural network that can take one of these images and predict the digit in the image. I have used Pytorch to train the neural network. PyTorch is a very popular framework for deep learning. PyTorch is an open source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing.