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

Scale up your Windows containers seamlessly on AWS powered by field-proven expertise and best practices on Amazon ECS, EKS, and Fargate

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.

在AWS上無縫擴展您的Windows容器，借助Amazon ECS、EKS和Fargate的實踐經驗和最佳實踐。

購買印刷版或Kindle書籍將包含免費的PDF電子書。

主要特點：
- 學習如何在AWS上快速部署和自動化端到端的CV流程
- 實施設計原則以減輕偏見並擴展CV工作負載的生產
- 使用AWS AI/ML服務的代碼示例來掌握CV概念

書籍描述：
計算機視覺（CV）是人工智能領域的一個領域，它幫助將視覺數據轉化為可操作的洞察，以解決各種業務挑戰。本書為任何希望學習如何快速構建和部署生產就緒模型的人提供了指導。

您將首先探索CV的應用和Amazon Rekognition和Amazon Lookout for Vision的功能。然後，本書將引導您通過身份驗證、實時視頻分析、內容審核和檢測製造缺陷等實際用例，讓您了解如何實施AWS AI/ML服務。隨著進展，您還將使用Amazon SageMaker進行數據標註、訓練和部署CV模型。在結尾章節中，您將使用實際代碼示例，發現擴展、降低成本、改善安全性和減輕CV工作負載偏見的最佳實踐和設計原則。

通過閱讀本AWS書籍，您將能夠借助AWS AI/ML服務在生產環境中構建和實施CV，加速業務成果。

您將學到：
- 在電子商務、物流和媒體等行業應用CV
- 使用Amazon Rekognition Custom Labels構建自定義圖像分類器
- 在AWS上創建自動化的端到端CV工作流程
- 使用Amazon Lookout for Vision在邊緣設備上檢測產品缺陷
- 使用Amazon SageMaker構建、部署和監控CV模型
- 發現設計和評估CV工作負載的最佳實踐
- 在整個機器學習生命周期中制定AI治理策略

本書適合機器學習工程師或數據科學家，希望發現最佳實踐並學習如何在AWS上構建全面的CV解決方案。為了更有效地理解本書中涵蓋的概念，需要了解AWS基礎知識。對機器學習概念和Python編程語言有扎實的理解也將有益。