So far, we have discussed what image classification is all about. In this section, we will get our hands dirty by building our own classifiers. In one of the earlier sections of the chapter, we briefly mentioned famous benchmarking datasets, including CIFAR-10 and Stanford Dogs datasets, which we will be concentrating on in the coming sections. We will also utilize pretrained models to understand how we can leverage transfer learning to improve upon our models.