Introduction to TensorFlow

Before the era of TensorFlow, the landscape of deep learning was markedly different. Data professionals had fewer comprehensive tools to aid in the development, training, and deployment of neural networks. This posed challenges in experimenting with various architectures and tuning model settings to solve complex tasks, as data experts often had to construct their models from scratch. The process was time-consuming, with some experts spending days or even weeks developing effective models. Another bottleneck was the difficulty in deploying trained models, which made the practical application of neural networks challenging during those early days.

But today, everything has changed; with TensorFlow, you can do lots of amazing things. In this chapter, we will begin by examining the TensorFlow ecosystem and discussing, at a high level, the various components relevant to building state-of-the-art applications with TensorFlow. We will begin our journey by setting...