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Computer Vision on AWS

Computer Vision on AWS

By : Lauren Mullennex, Nate Bachmeier, Jay Rao
4.9 (8)
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Computer Vision on AWS

Computer Vision on AWS

4.9 (8)
By: Lauren Mullennex, Nate Bachmeier, Jay Rao

Overview of this book

Computer vision (CV) is a field of artificial intelligence that helps transform visual data into actionable insights to solve a wide range of business challenges. This book provides prescriptive guidance to anyone looking to learn how to approach CV problems for quickly building and deploying production-ready models. You’ll begin by exploring the applications of CV and the features of Amazon Rekognition and Amazon Lookout for Vision. The book will then walk you through real-world use cases such as identity verification, real-time video analysis, content moderation, and detecting manufacturing defects that’ll enable you to understand how to implement AWS AI/ML services. As you make progress, you'll also use Amazon SageMaker for data annotation, training, and deploying CV models. In the concluding chapters, you'll work with practical code examples, and discover best practices and design principles for scaling, reducing cost, improving the security posture, and mitigating bias of CV workloads. By the end of this AWS book, you'll be able to accelerate your business outcomes by building and implementing CV into your production environments with the help of AWS AI/ML services.
Table of Contents (21 chapters)
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1
Part 1: Introduction to CV on AWS and Amazon Rekognition
5
Part 2: Applying CV to Real-World Use Cases
9
Part 3: CV at the edge
12
Part 4: Building CV Solutions with Amazon SageMaker
15
Part 5: Best Practices for Production-Ready CV Workloads

Preface

Computer vision (CV) transforms visual data into actionable insights to solve many business challenges. In recent years, due to the availability of increased computing power and access to vast amounts of data, CV has become more accessible. Amazon Web Services (AWS) has played an important role in democratizing CV by providing services to build, train, and deploy CV models.

In this book, you will begin by exploring the applications of CV and features of Amazon Rekognition and Amazon Lookout for Vision. Then, you’ll walk through real-world use cases such as identity verification, real-time video analysis, content moderation, and detecting manufacturing defects to understand how to implement AWS AI/ML services. You’ll also use Amazon SageMaker for data annotation, training, and deploying CV models. As you progress, you’ll learn best practices and design principles for scaling, reducing cost, improving the security posture, and mitigating the bias of CV workloads.

By the end of this book, you’ll be able to accelerate your business outcomes by building and implementing CV into your production environments with AWS AI/ML services.

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