In Chapter 7, Feedforward Neural Networks, we saw how deep neural networks are built and how weights connect neurons in one layer to neurons in the previous or following layer. The layers in CNNs, however, are connected through a linear operation known as convolution, which is where their name comes from and what makes it such a powerful architecture for images.
Here, we will go over the various kinds of convolution and pooling operations used in practice and what the effect of each is. But first, let's see what convolution actually is.
