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 data capture with Amazon S3

Document capture or ingestion is a process to aggregate all our data in a secure, centralized, scalable data store. While building a data capture stage for your IDP pipeline, you have to take data sources, data format, and a data store into consideration.

Data store

The first step is to store our documents for transformation. To store documents, we can use any type of document store, such as a local filesystem or Amazon S3. For this IDP pipeline, we will be leveraging AWS AI services, and we recommend, for an easier, more secure, and more scalable document store, to leverage Amazon S3, an object storage service that offers industry-leading scalability, data availability, security, and performance. Amazon S3 has 11 9s of durability, and millions of customers all around the world leverage Amazon S3 for their data store.

Many regulatory industries, such as GE Healthcare, use Amazon S3 for data storage during their digital transformation...