Now, let's take a step back and start with a simple, working definition of DL. As we work through this book, our understanding of this term will evolve, but, for now, let's consider a simple example. We have an image of a person. How can we show this image to a computer? How can we teach the computer to associate this image with the word person?
First, we figure out a representation of this image, say the RGB values for every pixel in the image. We then feed that array of values (together with several trainable parameters) into a series of operations we're quite familiar with (multiplication and addition). This produces a new representation that we can use to compare against a representation we know maps to the label, ...
