Part 3:Synthetic Data Generation Approaches

In this part, you will be introduced to the main synthetic data generation approaches. You will learn how to leverage simulators and rendering engines, Generative Adversarial Networks (GANs), video games, and diffusion models to generate synthetic data. You will explore the potential of these approaches in ML. Moreover, you will understand the challenges and pros and cons of each method. This part will be supported with hands-on practical examples to learn how to generate and utilize synthetic data in practice.

This part has the following chapters:

• Chapter 6, Leveraging Simulators and Rendering Engines to Generate Synthetic Data
• Chapter 7, Exploring Generative Adversarial Networks
• Chapter 8, Video Games as a Source of Synthetic Data
• Chapter 9, Exploring Diffusion Models for Synthetic Data