How do deep learning models learn?

Let's look at a multilayer-depth neural network recognizing a single-digit image, as follows:

Figure 2.3 – Rendering of the layer content of a neural network for digit classification

As you can see in the preceding diagram, the network extracts patterns from the digit image. In each layer, it obtains different representations, so each layer specializes in some specific features of the image, giving the necessary keys to identify the category to which it belongs.

This is basically DL, a multistage technique of learning patterns from data. It's based on a very simple concept, but by tweaking it and scaling it high enough, you can make amazing predictions.

Let's now see the reasons why AutoKeras is our preferred tool for automated ML (AutoML).