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Intelligent Workloads at the Edge
Intelligent Workloads at the Edge

Intelligent Workloads at the Edge: Deliver cyber-physical outcomes with data and machine learning using AWS IoT Greengrass

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Profile Icon Indraneel (Neel) Mitra Profile Icon Ryan Burke
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$12.99 per month
Full star icon Full star icon Full star icon Full star icon Half star icon 4.8 (17 Ratings)
Paperback Jan 2022 374 pages 1st Edition
eBook
$39.99
Paperback
$48.99
Subscription
Free Trial
Renews at $12.99p/m
Arrow left icon
Profile Icon Indraneel (Neel) Mitra Profile Icon Ryan Burke
Arrow right icon
$12.99 per month
Full star icon Full star icon Full star icon Full star icon Half star icon 4.8 (17 Ratings)
Paperback Jan 2022 374 pages 1st Edition
eBook
$39.99
Paperback
$48.99
Subscription
Free Trial
Renews at $12.99p/m
eBook
$39.99
Paperback
$48.99
Subscription
Free Trial
Renews at $12.99p/m

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Key benefits

  • 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

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.

Who is this book 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.

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

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jan 14, 2022
Length: 374 pages
Edition : 1st
Language : English
ISBN-13 : 9781801811781
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Product Details

Publication date : Jan 14, 2022
Length: 374 pages
Edition : 1st
Language : English
ISBN-13 : 9781801811781
Category :
Concepts :
Tools :

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Frequently bought together


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Customer reviews

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Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.8
(17 Ratings)
5 star 94.1%
4 star 0%
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1 star 5.9%
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James Gosling Jan 31, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
For everyone from students, to hardware and software engineers, this book provides remarkably complete and comprehensible coverage for building edge computing devices that interconnect with the cloud, all told in a learn-by-doing style. From simple "hello world" applications to complex image recognition using machine learning. It could even be used as a textbook. One of the special features of this book is that it uses tools from Amazon Web Services to show you how to do remote management. Among other things, whether you're deploying one device, or a million, the management infrastructure scales. Once your IoT device goes from prototype to product, it is secure, updatable and secure.
Amazon Verified review Amazon
David G Jan 23, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book provides a great introduction to the many aspects of designing and operating workloads for the edge and combined with cloud architectural services; as well as going deeper into design patterns and hands on setup of an edge workload with machine learning.It is easy to read and setup in a step by step format to enable progress through each chapter mixing design and theory with hands on working examples. I recommend this book for those that are interested in designing edge/hybrid workloads, MLOps engineers, and those that are interested in increasing their AWS and IoT knowledge.
Amazon Verified review Amazon
Rob Tiffany Dec 10, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The authors do a great job of plunging you into the AWS world of IoT. From devices to edge computing with AWS IoT Greengrass, and on up the stack to the cloud where machine learning models are trained with Amazon SageMaker, no stone is left unturned. I highly recommend this book to anyone interested in learning how to build IoT solutions.
Amazon Verified review Amazon
Michael Garcia Jan 18, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
What I loved the most about this book is getting all in one place a lot of information that usually has to be pieced together. For instance this book provide introduction on IoT technologies in the context of the broader use of IT for companies, explanation of IoT best practices and AWS best practices that comes only with experience of implementing the technologies referenced at scale, hands-on labs based on AWS services with dedicated github repository, and terminology explanations so neophytes can start familiarizing themselves with the IoT domain nomenclature. Therefore I believe this book will be particularly enjoyed by people who have basic IT notions and are interested in ramping up on AWS IoT technologies or have a specific interest in one of the IoT topics detailed in the book.I wish the example taken throughout the book would have been a smart home project that the reader could accomplish with some additional hardware (think an alarm monitoring system for a door/window, detection of a pet making noises, monitoring food level in a pantry, etc...) although I understand it comes with additional challenges for the reader such as sourcing the hardware.
Amazon Verified review Amazon
Rudra Bhattacharjee Jan 14, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Great book Neel and Ryan. I really enjoyed reading it. Looking forward to your next publications.This book is for anyone who wants to learn how to combine the technologies of edge computing and machine learning to deliver next-generation cyber-physical outcomes.The book has been written in a very easy to understand structure and language. This should make it possible for most people who are interested in edge and machine learning to be able to get into the remarkable journey of delivery next gen outcomes at edge.If you are still not sure why you should ready this subject maybe the benefits will.1. Reducing the latency of reacting to a measured event,2. Improving the solution's availability by reducing its runtime dependency ona remote network entity such as a server,3. Reducing the cost of operations by reducing the quantity of data to transmit over the WAN, and4. Enabling compliance with data governance policies by handling protected data exclusively at the edge
Amazon Verified review Amazon
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