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)
Part 1: Accurate Extraction of Documents and Categorization
Part 2: Enrichment of Data and Post-Processing of Data
Part 3: Intelligent Document Processing in Industry Use Cases


In this chapter, we discussed the extraction stage of an IDP pipeline, and how we can leverage Amazon Textract to accurately extract elements from documents. Documents can be of different types, such as an unstructured dense text type of document, a semi-structured document such as a form, or a structured document such as a table. We walked through the sample code and its API response to accurately extract elements from any type of scanned document.

We then reviewed the need for accurate extraction of elements from specialized document types, such as ID documents such as a US driver’s license, a US passport, or invoice/receipt types of documents. We discussed Amazon Textract’s analyze_id and analyze_expense APIs to accurately extract elements from ID and invoice/receipt types of documents respectively. We walked you through the sample code for your accurate extraction of specialized document types.

In the next chapter, we will extend the extraction stage...