-
Book Overview & Buying
-
Table Of Contents
-
Feedback & Rating

Computer Vision on AWS
By :

Computer Vision on AWS
By:
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)
Preface
In Progress
| 0 / 9 sections completed |
0%
Part 1: Introduction to CV on AWS and Amazon Rekognition
In Progress
| 0 / 1 sections completed |
0%
Chapter 1: Computer Vision Applications and AWS AI/ML Services Overview
In Progress
| 0 / 7 sections completed |
0%
Chapter 2: Interacting with Amazon Rekognition
In Progress
| 0 / 6 sections completed |
0%
Chapter 3: Creating Custom Models with Amazon Rekognition Custom Labels
In Progress
| 0 / 7 sections completed |
0%
Part 2: Applying CV to Real-World Use Cases
In Progress
| 0 / 1 sections completed |
0%
Chapter 4: Using Identity Verification to Build a Contactless Hotel Check-In System
In Progress
| 0 / 9 sections completed |
0%
Chapter 5: Automating a Video Analysis Pipeline
In Progress
| 0 / 5 sections completed |
0%
Chapter 6: Moderating Content with AWS AI Services
In Progress
| 0 / 6 sections completed |
0%
Part 3: CV at the edge
In Progress
| 0 / 1 sections completed |
0%
Chapter 7: Introducing Amazon Lookout for Vision
In Progress
| 0 / 7 sections completed |
0%
Chapter 8: Detecting Manufacturing Defects Using CV at the Edge
In Progress
| 0 / 5 sections completed |
0%
Part 4: Building CV Solutions with Amazon SageMaker
In Progress
| 0 / 1 sections completed |
0%
Chapter 9: Labeling Data with Amazon SageMaker Ground Truth
In Progress
| 0 / 6 sections completed |
0%
Chapter 10: Using Amazon SageMaker for Computer Vision
In Progress
| 0 / 5 sections completed |
0%
Part 5: Best Practices for Production-Ready CV Workloads
In Progress
| 0 / 1 sections completed |
0%
Chapter 11: Integrating Human-in-the-Loop with Amazon Augmented AI (A2I)
In Progress
| 0 / 6 sections completed |
0%
Chapter 12: Best Practices for Designing an End-to-End CV Pipeline
In Progress
| 0 / 7 sections completed |
0%
Chapter 13: Applying AI Governance in CV
In Progress
| 0 / 5 sections completed |
0%
Index
In Progress
| 0 / 2 sections completed |
0%
Other Books You May Enjoy
In Progress
| 0 / 4 sections completed |
0%
Customer Reviews