-
Book Overview & Buying
-
Table Of Contents
-
Feedback & Rating

Intelligent Workloads at the Edge
By :

Intelligent Workloads at the Edge
By:
Overview of this book
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.
Table of Contents (17 chapters)
Preface
In Progress
| 0 / 8 sections completed |
0%
Section 1: Introduction and Prerequisites
In Progress
| 0 / 1 sections completed |
0%
Chapter 1: Introduction to the Data-Driven Edge with Machine Learning
In Progress
| 0 / 10 sections completed |
0%
Section 2: Building Blocks
In Progress
| 0 / 1 sections completed |
0%
Chapter 2: Foundations of Edge Workloads
In Progress
| 0 / 10 sections completed |
0%
Chapter 3: Building the Edge
In Progress
| 0 / 10 sections completed |
0%
Chapter 4: Extending the Cloud to the Edge
In Progress
| 0 / 9 sections completed |
0%
Chapter 5: Ingesting and Streaming Data from the Edge
In Progress
| 0 / 9 sections completed |
0%
Chapter 6: Processing and Consuming Data on the Cloud
In Progress
| 0 / 8 sections completed |
0%
Chapter 7: Machine Learning Workloads at the Edge
In Progress
| 0 / 9 sections completed |
0%
Section 3: Scaling It Up
In Progress
| 0 / 1 sections completed |
0%
Chapter 8: DevOps and MLOps for the Edge
In Progress
| 0 / 9 sections completed |
0%
Chapter 9: Fleet Management at Scale
In Progress
| 0 / 8 sections completed |
0%
Section 4: Bring It All Together
In Progress
| 0 / 1 sections completed |
0%
Chapter 10: Reviewing the Solution with AWS Well-Architected Framework
In Progress
| 0 / 7 sections completed |
0%
Other Books You May Enjoy
In Progress
| 0 / 3 sections completed |
0%
Customer Reviews