One of the latest advancements in neural networks is the so-called deep learning. Nowadays it is nearly impossible to talk about neural networks without mentioning deep learning, because the recent research on feature extraction, data representation, and transformation has found that many layers of processing information are able to abstract and produce better representations of data for learning. Throughout this book we have seen that neural networks require input data in numerical form, no matter if the original data is categorical or binary, neural networks cannot process non-numerical data directly. But it turns out that in the real world most of the data is non-numerical or is even unstructured, such as images, videos, audios, texts, and so on.
In this sense a deep network would have many layers that could act as data processing units to transform this data and provide it to the next layer for subsequent data processing. This is analogous to the process that happens in...