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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

Interacting with Amazon Rekognition

A picture is worth a thousand words because it captures so much context. Imagine looking at a recent photo or video of a family trip. Your two kids are playing on the beach with the dog, and it’s sunny and warm. Their suits are still dry, so this must have occurred near your arrival time. There’s an endless ocean of contextually sensitive details your eyes can detect.

Since computers don’t have eyes, we need to use artificial intelligence to mimic this capability. Amazon Rekognition’s mission is to make computer vision accessible to every developer. With Rekognition, you can build faster by leveraging its APIs to access high-quality results. The built-in APIs can detect the following within photos and images: objects, faces, scenes, activities, text, pathing, and segmentations. These capabilities simplify operations without requiring data science teams to build custom models, and you continuously receive improvements...

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