Preface

The Internet of Things (IoT) has transformed how businesses think about and interact with the world. Sensors can measure the performance of high-volume industrial manufacturing operations or the daily environmental health of a remote island. The IoT makes it possible to study the world at various levels of precision and enable data-driven decision making anywhere. Machine learning (ML) and Elastic cloud computing have accelerated our ability to understand and analyze the huge amount of data generated by the IoT. With edge computing, data analytics and ML models can process information locally at the source where the data is generated.

This book will teach you to combine the technologies of edge computing and machine learning to deliver next-generation cyber-physical outcomes. You'll begin by discovering how to create software applications that run on edge devices using software from Amazon Web Services, such as AWS IoT Greengrass. As you advance, you'll learn how to process and stream IoT data from the edge to the cloud and use it to train ML models using Amazon SageMaker. The book also shows you how to optimize these models and run them at the edge for optimal performance, cost savings, and data compliance.

By the end of this book, you'll be able to scope your own IoT workloads, bring the power of machine learning to the edge, and operate those workloads in a production setting.