Book Image

Intelligent Document Processing with AWS AI/ML

By : Sonali Sahu
Book Image

Intelligent Document Processing with AWS AI/ML

By: Sonali Sahu

Overview of this book

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.
Table of Contents (16 chapters)
1
Part 1: Accurate Extraction of Documents and Categorization
6
Part 2: Enrichment of Data and Post-Processing of Data
10
Part 3: Intelligent Document Processing in Industry Use Cases

Review and Verification of Intelligent Document Processing

In the previous chapter, you understood the requirements for the enrichment process in Intelligent Document Processing (IDP). Often in healthcare industries, there is a requirement to derive medical insights to augment the document processing pipeline. We looked into Amazon Comprehend Medical and its features to derive medical insights for accurate document processing. We will now dive into the detailed post-processing stage of IDP. We will see how the Review and Verification steps can be automated by AWS AI services. We will also discuss the requirement and need to have human review and verification options for sensitive, business-critical, or accurate information processing in IDP. We will navigate through the following sections in this chapter:

  • Learning post-processing for a completeness check
  • Post-processing sensitive data
  • Learning about the document review process with human-in-the-loop