Intelligent Workloads at the Edge_ Deliver cyber-physical outcomes with data and machine learning using AWS IoT_,,,,.pdf

Intelligent Workloads at the Edge Deliver cyber-physical outcomes with data and machine learning using AWS IoT Greengrass Indraneel Mitra | Ryan Burke Intelligent Workloads at the EdgeIndraneel Mitra | Ryan Burke Things you will learn: • Build an end-to-end IoT solution from the edge to the cloud • Design and deploy multi-faceted intelligent solutions on the edge • Process data at the edge through analytics and ML • Package and optimize models for the edge using Amazon SageMaker • Implement MLOps and DevOps for operating an edge-based solution • Onboard and manage fl eets of edge devices at scale • Review edge-based workloads against industry best practices The Internet of Things (IoT) has transformed how people think about and interact with the world. The ubiquitous deployment of sensors around us makes it possible to study the world at any level of accuracy and enable data-driven decision-making anywhere. Data analytics and machine learning (ML) powered by elastic cloud computing have accelerated our ability to understand and analyze the huge amount of data generated by IoT. Now, edge computing has brought information technologies closer to the data source to lower latency and reduce costs. This book will teach you how to combine the technologies of edge computing, data analytics, and ML to deliver next-generation cyber-physical outcomes. You’ll begin by discovering how to create software applications that run on edge devices with 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 train these models and run them at the edge for optimized performance, cost savings, and data compliance. By the end of this IoT book, you’ll be able to scope your own IoT workloads, bring the power of ML to the edge, and operate those workloads in a production setting. Intelligent Workloads at the Edge Intelligent Workload