Recognize Handwritten Digits Using a Deep Neural Network

It might be easy for us to recognize the blurred image given below owing to the amazing functionality of the human brain, but it is not so simple for computers.

We can recognize it with such ease, possibly because we’ve seen so many different variants of the digit “6” that our brain has learned to recognize this digit in various forms. There is an area of machine learning called deep learning that mimics this learning mechanism of the human brain—learning by example.

Deep learning is based on neural networks that are made up of different layers of linked “neurons.” It is inspired by the structure and function of the neurons in the human brain. We need massive amounts of data and complex algorithms to train a neural network.

In this project, we will use PyTorch to implement a deep learning algorithm to recognize handwritten digits. We will use the MNIST dataset to complete this project. It is a collection of 70000 handwritten digits divided into a training set of 60000 images and a test set of 10000 images.