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.
Image classification and transfer learning
CIFAR-10
CIFAR-10 is one of the most widely used image datasets in the world of deep learning. Prepared by the Canadian Institute for Advanced Research, this is a fairly decent-sized dataset. The major advantage of this dataset...
