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

Part 1: Introduction to CV on AWS and Amazon Rekognition

As a machine learning engineer or data scientist, this section helps you better understand how CV can be applied to solve business challenges and gives a comprehensive overview of the AWS AI/ML services available.

This first part consists of three cumulative chapters that will cover the core concepts of CV, a detailed introduction to Amazon Rekognition, and how to create a custom classification model using Amazon Rekognition Custom Labels.

By the end of this part, you will understand how to apply CV to accelerate your business outcomes, what AWS AI/ML services for your CV workloads, and how to use Amazon Rekognition for tasks including classification and object detection.

This part comprises the following chapters:

  • Chapter 1, Computer Vision Applications and AWS AI/ML Overview
  • Chapter 2, Interacting with Amazon Rekognition
  • Chapter 3, Creating Custom Models with Amazon Rekognition Custom Labels