Intelligent Document Processing with AWS AI/ML

Intelligent Document Processing with AWS AI/ML

by Sonali Sahu
Released October 2022
Publisher(s): Packt Publishing
ISBN: 9781801810562

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Book description

Build real-world artificial intelligence applications across industries with the help of intelligent document processing

Key Features

  • Tackle common document processing problems to extract value from any type of document
  • Unlock deeper levels of insights on IDP in a more structured and accelerated way using AWS AI/ML
  • Apply your knowledge to solve real document analysis problems in various industry applications

Book Description

With the volume of data growing exponentially in this digital era, it has become paramount for professionals to process this data in an accelerated and cost-effective manner to get value out of it. Data that organizations receive is usually in raw document format, and being able to process these documents is critical to meeting growing business needs.

This book is a comprehensive guide to helping you get to grips with AI/ML fundamentals and their application in document processing use cases. You'll begin by understanding the challenges faced in legacy document processing and discover how you can build end-to-end document processing pipelines with AWS AI services. As you advance, you'll get hands-on experience with popular Python libraries to process and extract insights from documents. This book starts with the basics, taking you through real industry use cases for document processing to deliver value-based care in the healthcare industry and accelerate loan application processing in the financial industry. Throughout the chapters, you'll find out how to apply your skillset to solve practical problems.

By the end of this AWS book, you'll have mastered the fundamentals of document processing with machine learning through practical implementation.

What you will learn

  • Understand the requirements and challenges in deriving insights from a document
  • Explore common stages in the intelligent document processing pipeline
  • Discover how AWS AI/ML can successfully automate IDP pipelines
  • Find out how to write clean and elegant Python code by leveraging AI
  • Get to grips with the concepts and functionalities of AWS AI services
  • Explore IDP across industries such as insurance, healthcare, finance, and the public sector
  • Determine how to apply business rules in IDP
  • Build, train, and deploy models with serverless architecture for IDP

Who this book is for

This book is for technical professionals and thought leaders who want to understand and solve business problems by leveraging insights from their documents. If you want to learn about machine learning and artificial intelligence, and work with real-world use cases such as document processing with technology, this book is for you. To make the most of this book, you should have basic knowledge of AI/ML and python programming concepts. This book is also especially useful for developers looking to explore AI/ML with industry use cases.

Table of contents

  1. Intelligent Document Processing with AWS AI/ML
  2. Contributors
  3. About the authors
  4. About the reviewer
  5. Preface
    1. Who this book is for
    2. What this book covers
    3. To get the most out of this book
    4. Download the example code files
    5. Download the color images
    6. Conventions used
    7. Get in touch
    8. Share your thoughts
  6. Part 1: Accurate Extraction of Documents and Categorization
  7. Chapter 1: Intelligent Document Processing with AWS AI and ML
    1. Understanding common document processing use cases across industries
    2. Understanding the AWS ML and AI stack
    3. Introducing Intelligent Document Processing pipeline
      1. Data capture
      2. Document classification
      3. Document extraction
      4. Document enrichment
      5. Document post-processing (review and verification)
      6. Consumption
    4. Summary
    5. References
  8. Chapter 2: Document Capture and Categorization
    1. Technical requirements
      1. Signing up for an AWS account
    2. Understanding data capture with Amazon S3
      1. Data store
      2. Data sources
      3. Sensitive document processing
    3. Understanding document classification with the Amazon Comprehend custom classifier
      1. Training a Comprehend custom classification model
    4. Understanding document categorization with computer vision
    5. Summary
  9. Chapter 3: Accurate Document Extraction with Amazon Textract
    1. Technical requirements
    2. Understanding the challenges in legacy document extraction
    3. Using Amazon Textract for the accurate extraction of different types of documents
      1. Introducing Amazon Textract
    4. Using Amazon Textract for the accurate extraction of specialized documents
      1. Accurate extraction of ID document (driver’s license)
      2. ID document (US passport) accurate extraction
      3. Receipt document accurate extraction
      4. Invoice document accurate extraction
    5. Summary
  10. Chapter 4: Accurate Extraction with Amazon Comprehend
    1. Technical requirements
    2. Using Amazon Comprehend for accurate data extraction
    3. Understanding document extraction – the IDP extraction stage with Amazon Comprehend
    4. Understanding custom entities extraction with Amazon Comprehend
      1. Training an Amazon Comprehend custom entity recognizer
      2. Checking the performance of a trained model
      3. Inference result from the Amazon Comprehend custom entity recognizer
    5. Summary
  11. Part 2: Enrichment of Data and Post-Processing of Data
  12. Chapter 5: Document Enrichment in Intelligent Document Processing
    1. Technical requirements
    2. Understanding document enrichment
    3. Learning to use Amazon Comprehend Medical for accurate extraction of medical entities
      1. Amazon Comprehend Medical
    4. Learning to use Amazon Comprehend Medical for medical ontology
    5. Summary
  13. Chapter 6: Review and Verification of Intelligent Document Processing
    1. Technical requirements
    2. Learning post-processing for a completeness check
      1. Post-processing sensitive data
      2. Learning about the document review process with human-in-the-loop
    3. Summary
    4. References
  14. Chapter 7: Accurate Extraction, and Health Insights with Amazon HealthLake
    1. Technical requirements
    2. Introducing Fast Healthcare Interoperability Resources (FHIR)
    3. Using Amazon HealthLake as a health data store
      1. FHIR operations with Amazon HealthLake
      2. READ operation
      3. HealthLake PUT request
    4. Handling documents with an FHIR data store
    5. Summary
    6. References
  15. Part 3: Intelligent Document Processing in Industry Use Cases
  16. Chapter 8: IDP Healthcare Industry Use Cases
    1. Technical requirements
    2. Understanding IDP with healthcare prior authorization
      1. An introduction to the healthcare prior authorization process
      2. Automate prior authorization form filling using Amazon HealthLake
    3. Learning IDP for pharmacy receipt automation
    4. Understanding healthcare claims processing and risk adjustment with IDP
    5. Summary
  17. Chapter 9: Intelligent Document Processing – Insurance Industry
    1. Technical requirements
    2. Automating the benefits enrollment process with IDP
    3. Understanding insurance claims processing extraction with IDP
      1. The data capture and document classification stages of the IDP pipeline
      2. Document extraction stage of the IDP pipeline
    4. Understanding insurance claims processing document enrichment and review and verification
      1. Claims processing for an invalid claims form
    5. Summary
  18. Chapter 10: Intelligent Document Processing – Mortgage Processing
    1. Technical requirements
    2. Automating mortgage processing data capture and data categorization with IDP
    3. Automating mortgage processing data capture and data categorization with IDP
    4. Understanding mortgage processing extraction and enrichment with IDP
      1. Extraction with Comprehend
      2. Document enrichment for mortgage application processing
      3. Understanding the mortgage processing review and verification stage of the IDP pipeline
      4. Understanding financial services use cases for document processing
    5. Summary
    6. References:
  19. Index
    1. Why subscribe?
  20. Other Books You May Enjoy
    1. Packt is searching for authors like you
    2. Share your thoughts

Product information

  • Title: Intelligent Document Processing with AWS AI/ML
  • Author(s): Sonali Sahu
  • Release date: October 2022
  • Publisher(s): Packt Publishing
  • ISBN: 9781801810562