In the previous chapters, we looked at the process of developing deep neural network models for classification and regression problems. In both cases, we were dealing with structured data and the models were of the supervised learning type, where target variables were available. Images or pictures belong to the unstructured category of data. In this chapter, we will illustrate the use of deep learning neural networks for image classification and recognition using the Keras package with the help of an easy-to-follow example. We will get started with a small sample size to illustrate the steps involved in developing an image-classification model. We will apply this model to a supervised learning situation involving the labeling of images or pictures.
Keras contains several built-in datasets for image classification, such as CIFAR10, CIFAR100...
