This chapter provides the essential background for working with deep learning and Keras. We start by defining deep learning and positioning it relative to machine learning and artificial intelligence. You will learn about the basic computational unit, the artificial neuron, and how neurons are arranged in layers to create network architectures. We will also discuss how these networks learn patterns from data using supervised learning techniques.

The chapter then introduces Keras, the high-level API used for building and training models throughout this course. We'll look at its features and integration with TensorFlow. Finally, we cover the practical steps needed to set up your Python environment with TensorFlow and Keras, concluding with a simple check to confirm everything is installed correctly.

By the end of this chapter, you will understand foundational deep learning terminology, the structure of basic neural networks, and have a ready-to-use Keras environment for building your first models.