Computer Vision on AWS: Build and deploy real-world CV solutions with Amazon Rekognition, Lookout for Vision, and SageMaker


Computer Vision on AWS: Build and deploy real-world CV solutions with Amazon Rekognition, Lookout for Vision, and SageMaker
by Lauren Mullennex(Author), Nate Bachmeier(Author), Jay Rao(Author)
Publisher Finelybook 出版社: Packt Publishing (March 31, 2023)
Language 语言: English
pages 页数: 324 pages
ISBN-10 书号: 1801078688
ISBN-13 书号: 9781801078689


Book Description
Develop scalable computer vision solutions for real-world business problems and discover scaling, cost reduction, security, and bias mitigation best practices with AWS AI/ML services
Purchase of the print or Kindle book includes a free PDF eBook

Key Features
Learn how to quickly deploy and automate end-to-end CV pipelines on AWS
Implement design principles to mitigate bias and scale production of CV workloads
Work with code examples to master CV concepts using AWS AI/ML services

Book Description
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.

What you will learn
Apply CV across industries, including e-commerce, logistics, and media
Build custom image classifiers with Amazon Rekognition Custom Labels
Create automated end-to-end CV workflows on AWS
Detect product defects on edge devices using Amazon Lookout for Vision
Build, deploy, and monitor CV models using Amazon SageMaker
Discover best practices for designing and evaluating CV workloads
Develop an AI governance strategy across the entire machine learning life cycle

Who this book is for
If you are a machine learning engineer or data scientist looking to discover best practices and learn how to build comprehensive CV solutions on AWS, this book is for you. Knowledge of AWS basics is required to grasp the concepts covered in this book more effectively. A solid understanding of machine learning concepts and the Python programming language will also be beneficial.

Table of contents
1.Product Information Document
2.Computer Vision Applications and AWS Al/ML Overview
3.Interacting with Amazon Rekognition
4.Creating Custom Models with Amazon Rekognition Custom Labels
5.Using Identity Verification to Build a Contactless Hotel Check-In System
6.Automating a Video Analysis Pipeline
7.Moderating Content with AWS Al Services
8.Introducing Amazon Lookout for Vision
9.Detecting Manufacturing Defects using CV at the Edge
10.Labeling Data with Amazon SageMaker Ground Truth
11.Using Amazon SageMaker for Computer Vision
12.Integrating Human-in-the-Loop with Amazon Augmented Al (A21)
13.Best Practices for Designing an End-to-End CV Pipeline
14.Applying Al Governance in CV

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