Practical Simulations for Machine Learning

Chapter 1. Introducing Synthesis and Simulation

The world is hungry for data. Machine learning and artificial intelligence are some of the most data-hungry domains around. Algorithms and models are growing ever bigger, and the real world is insufficient. Manual creation of data and real-world systems are not scalable, and we need new approaches. That’s where Unity, and software traditionally used for video game development, steps in.

This book is all about synthesis and simulation, and leveraging the power of modern video game engines for machine learning. Combining machine learning with simulations and synthetic data sounds relatively straightforward on the surface, but the reality is the idea of including video game technology in the serious business world of machine learning scares an unreasonable number of companies and businesses away from the idea.

We hope this book will steer you into this world and alleviate your concerns. Three of the authors of this book are video game developers with a significant background in computer science, and one is a serious machine learning and data scientist. Our combined perspectives and knowledge, built over many years in a variety of industries and approaches, are presented here for you.

This book will take you on a journey through the approaches and techniques that can be used to build and train machine learning systems using, and using data generated by, the Unity video game engine. There are two distinct domains in this book: simulation ...