Intelligent Workloads at the Edge
Intelligent Workloads at the Edge
Language - English
Updated on Jan, 2023
About the Book
Book description
Explore IoT, data analytics, and machine learning to solve cyber-physical problems using the latest capabilities of managed services such as AWS IoT Greengrass and Amazon SageMaker
Key Features
- Accelerate your next edge-focused product development with the power of AWS IoT Greengrass
- Develop proficiency in architecting resilient solutions for the edge with proven best practices
- Harness the power of analytics and machine learning for solving cyber-physical problems
Book Description
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.
What 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 fleets of edge devices at scale
- Review edge-based workloads against industry best practices
Who this book is for
This book is for IoT architects and software engineers responsible for delivering analytical and machine learning–backed software solutions to the edge. AWS customers who want to learn and build IoT solutions will find this book useful. Intermediate-level experience with running Python software on Linux is required to make the most of this book.

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Author Details

Packt Publishing
Founded in 2004 in Birmingham, UK, Packt's mission is to help the world put software to work in new ways, through the delivery of effective learning and information services to IT professionals.
Working towards that vision, we have published over 6,500 books and videos so far, providing IT professionals with the actionable knowledge they need to get the job done - whether that's specific learning on an emerging technology or optimizing key skills in more established tools.
As part of our mission, we have also awarded over $1,000,000 through our Open Source Project Royalty scheme, helping numerous projects become household names along the way.
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