In this section, we're going to go beyond what we did with the pre-built classifier and use our own images with our own labels.
The first thing I should mention is that this isn't really training from scratch with deep learning—there are multiple layers and algorithms for training the whole thing, which are very time-consuming—but we can take advantage of something called transfer learning, where we take the first few layers that were trained with a very large number of images, as illustrated in the following diagram:
It's one of the caveats of deep learning that having a few hundred or a few thousand images isn't enough. You need hundreds of thousands or even millions of samples in order to get good results, and gathering that much data is very time-consuming. Also, running it on a personal computer, which I expect...
