Book Image

Computer Vision on AWS

By : Lauren Mullennex, Nate Bachmeier, Jay Rao
Book Image

Computer Vision on AWS

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)
Part 1: Introduction to CV on AWS and Amazon Rekognition
Part 2: Applying CV to Real-World Use Cases
Part 3: CV at the edge
Part 4: Building CV Solutions with Amazon SageMaker
Part 5: Best Practices for Production-Ready CV Workloads


In this chapter, we covered establishing an AI governance framework. We discussed processes and procedures to help minimize risk and maximize the results of AI/ML systems. Next, we defined the key roles and responsibilities of business stakeholders for effective governance. We also summarized how AI governance applies to CV and how to mitigate unfair bias. Lastly, we detailed how to use Amazon SageMaker to apply governance and explainability across your workloads.

In this book, we’ve taken a journey into exploring the world of CV. From simple image classification tasks to the recent excitement surrounding generative AI, we’ve only just begun to discover the applications of CV. We hope you’ve enjoyed walking through some real-world examples and learning tips and tricks for using Amazon Rekognition, Amazon Lookout for Vision, and Amazon SageMaker along the way. Now, you’re ready to solve your business challenges with CV and incorporate AWS AI/ML...