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

Integrating Human-in-the-Loop with Amazon Augmented AI (A2I)

Sometimes, the machine learning (ML) predictions are not accurate enough for your use case. Alternatively, you might require predictions with very high confidence (99% or higher) for use cases involving high-risk, high-impact decisions such as approving a loan application or taking down content on social media applications. In such cases, you will want to run the ML predictions through human reviewers. This is where Amazon Augmented AI (Amazon A2I) comes in. You can use Amazon A2I to easily build workflows that require human review for ML predictions. In other words, you can use Amazon A2I to set up human-in-the-loop workflows. Amazon A2I removes the complexity, cost, and heavy lifting involved in building human review workflows or managing a large group of human reviewers.

This chapter covers the following topics:

  • Introducing Amazon A2I
  • Learning how to build a human review workflow
  • Leveraging A2I’...