Convolutional neural networks

Convolutional neural networks are a class of neural network that resolve the high-dimensionality problem we alluded to in the previous section, and, as a result, excel at image-classification tasks. It turns out that image pixels in a given image region are highly correlated—they tell us similar information about that specific image region. Accordingly, using convolutional neural networks, we can scan regions of an image and summarize that region in lower-dimensional space. As we'll see, these lower-dimensional representations, called feature maps, tell us many interesting things about the presence of all sorts of shapes—from the simplest lines, shadows, loops, and swirls, to very abstract, complex forms specific to our data, in our case, cat ears, cat faces, or tortillas—and do this in fewer dimensions than the original...