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

Understanding document categorization with computer vision

In document preprocessing, you will come across use cases where documents are classified based on a branded logo on the document or having tables. These are visual clues that we want to use to classify documents before processing. We can use Amazon Rekognition, computer vision software with deep learning-powered image recognition, to detect visual clues such as objects, scenes, and text from any scanned images for document classification.

You can leverage an Amazon Rekognition Custom Label to detect a logo from any document and classify the document based on the logo. For example, a healthcare provider supports multiple insurance providers. Patients when visiting a doctor’s office submit insurance cards. These insurance cards can be processed automatically to detect the logos from them, and the documents can be classified according to their corresponding categories.

Now, let’s look at a hands-on example...