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

Document Capture and Categorization

One of the first stages of an Intelligent Document Processing (IDP) pipeline is to collect your documents and store them in a highly available, reliable, and secure data store. Data is our gold mine, and to extract insights from our documents, we need to understand our data and pre-process it as needed. Most of the time, organizations receive a package of documents that are not labeled. To understand the documents, you need to manually scan these documents and label them into the right category, which is known as the document classification stage of the IDP pipeline. Thus, we are looking for an automated process for data collection and document classification.

In this chapter, we will be covering the following topics:

  • Understanding data capture with Amazon S3
  • Understanding document classification with Amazon Comprehend’s custom classifier
  • Understanding document categorization with computer vision