Chapter 7. Deep Learning

In Chapter 2, Practical Approach to Real-World Supervised Learning, we discussed different supervised classification techniques that are general and can be used in a wide range of applications. In the area of supervised non-linear techniques, especially in computer-vision, deep learning and its variants are having a remarkable impact. We find that deep learning and associated methodologies can be applied to image-recognition, image and object annotation, movie descriptions, and even areas such as text classification, language modeling, translations, and so on. (References [1, 2, 3, 4, and 5])

To set the stage for deep learning, we will start with describing what neurons are and how they can be arranged to build multi-layer neural networks, present the core elements of these networks, and explain how they work. We will then discuss the issues and problems associated with neural networks that gave rise to advances and structural changes in deep learning...