1. Building Blocks of Deep Learning

Introduction

In this chapter, you will be introduced to deep learning and its relationship with artificial intelligence and machine learning. We will also learn about some of the important deep learning architectures, such as the multi-layer perceptron, convolutional neural networks, recurrent neural networks, and generative adversarial networks. As we progress, we will get hands-on experience with the TensorFlow framework and use it to implement a few linear algebra operations. Finally, we will be introduced to the concept of optimizers. We will understand their role in deep learning by utilizing them to solve a quadratic equation. By the end of this chapter, you will have a good understanding of what deep learning is and how programming with TensorFlow works.