Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying Computer Vision on AWS
  • Table Of Contents Toc
  • Feedback & Rating feedback
Computer Vision on AWS

Computer Vision on AWS

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

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’...

Unlock full access

Continue reading for free

A Packt free trial gives you instant online access to our library of over 7000 practical eBooks and videos, constantly updated with the latest in tech
bookmark search playlist download font-size

Change the font size

margin-width

Change margin width

day-mode

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Delete Bookmark

Modal Close icon
Are you sure you want to delete it?
Cancel
Yes, Delete

Confirmation

Modal Close icon
claim successful

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY