This is one of the classic "Hello World" type problem in the field of deep learning. We already covered one very simple case study of flower classification earlier and in this one we are going to classify hand written digits. For this case study we are using the MNIST dataset. The MNIST database of handwritten digits is available at http://yann.lecun.com/exdb/mnist/. It has a training set of 60,000 examples, and a test set of 10,000 examples. Some of the sample images in this dataset are as shown:
A typical hello world neural network that we are building is to train our network with the training set and to classify the images based on the test set. For this we will use a CNN or convolutional neural network.
A convolutional neural network is a special type of feed forward neural network and is especially suited for image classification. Explaining the entire concept of a convolution network is beyond scope of this chapter but we will explain it briefly...