In this lesson we are going to take a deeper dive in to CNNs and their variants. Almost all imagery projects will use CNNs in one form or another.
Remeber from last time, CNNs have their weights arranged into blocks called filters. This forces the weights to have an explicit spatial relationship.

One layer of a CNN will be composed of many filters (sometimes called kernels). Each filter produces one output.
