In this chapter, we will look at how we can stack layers of convolutions to scale up our network to tackle a slightly more real-world problem of distinguishing between color pictures of animals and vehicles, called CIFAR.
CIFAR dataset
Where do we go from here? Let’s take on a slightly larger, more complicated problem. This is a dataset called CIFAR. It’s a collection of color pictures. So we have pictures of cats, dogs, animals, as well as human vehicles – cars and trucks. We have ten categories. Now we’re going to be working with color data, so ...
