Sight is hands-down the most-used sub-process. You are using it right now! Of course, it was something researchers attempted to mimic with neural networks early on, except that nothing really worked well until the concept of convolution was applied and used to classify images. The concept of convolution is the idea behind detecting, sometimes grouping, and isolating common features in an image. For instance, if you cover up 3/4 of a picture of a familiar object and show it to someone, they will almost certainly recognize the image by recognizing just the partial features. Convolution works the same way, by blowing up an image and then isolating the features for later recognition.
Convolution works by dissecting an image into its feature parts, which makes it easier to train a network. Let's jump into a code sample that extends from where we left...
