Deep learning is a subset of machine learning inspired by the neural networks in the human brain. It has been around for a decade, but the reason it is so popular right now is due to the computational advancements and availability of the huge volume of data. With a huge volume of data, deep learning algorithms outperform classic machine learning. It has already been transfiguring and extensively used in several interdisciplinary scientific fields such as computer vision, natural language processing (NLP), speech recognition, and many others.

In this chapter, we will learn about the following topics:

• Fundamental concepts of deep learning
• Biological and artificial neurons
• Artificial neural network and its layers
• Activation functions
• Forward and backward propagation in ANN
• Gradient checking algorithm
• Building an artificial neural network from scratch