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Intelligent Document Processing with AWS AI/ML: A comprehensive guide to building IDP pipelines with applications across industries

Intelligent Document Processing with AWS AI/ML: A comprehensive guide to building IDP pipelines with applications across industries

Intelligent Document Processing with AWS AI/ML: A comprehensive guide to
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Intelligent Document Processing with AWS AI/ML: A comprehensive guide to building IDP pipelines with applications across industries Paperback - 2022

by Sonali Sahu

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Packt Publishing, 10/21/2022 12:00:01. paperback. Very Good. 0.6299 9.1339 7.4016.
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  • Title Intelligent Document Processing with AWS AI/ML: A comprehensive guide to building IDP pipelines with applications across industries
  • Author Sonali Sahu
  • Binding Paperback
  • Condition Used - Very good
  • Pages 246
  • Volumes 1
  • Language ENG
  • Publisher Packt Publishing
  • Publication date 10/21/2022 12:00:01
  • Bookseller's Inventory # mon0004121101
  • ISBN 9781801810562 / 1801810567
  • Weight 0.95 lbs (0.43 kg)
  • Dimensions 9.25 x 7.5 x 0.52 in (23.50 x 19.05 x 1.32 cm)
  • Size 0.6299 9.1339 7.4016
  • Category Computers - General Information
  • Quantity available 1
  • Bookseller catalogues Book

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From the publisher

Build real-world artificial intelligence applications across industries with the help of intelligent document processing


Key Features:

  • Tackle common document processing problems to extract value from any type of document
  • Unlock deeper levels of insights on IDP in a more structured and accelerated way using AWS AI/ML
  • Apply your knowledge to solve real document analysis problems in various industry applications


Book Description:

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.


What You Will Learn:

  • Understand the requirements and challenges in deriving insights from a document
  • Explore common stages in the intelligent document processing pipeline
  • Discover how AWS AI/ML can successfully automate IDP pipelines
  • Find out how to write clean and elegant Python code by leveraging AI
  • Get to grips with the concepts and functionalities of AWS AI services
  • Explore IDP across industries such as insurance, healthcare, finance, and the public sector
  • Determine how to apply business rules in IDP
  • Build, train, and deploy models with serverless architecture for IDP


Who this book is for:

This book is for technical professionals and thought leaders who want to understand and solve business problems by leveraging insights from their documents. If you want to learn about machine learning and artificial intelligence, and work with real-world use cases such as document processing with technology, this book is for you. To make the most of this book, you should have basic knowledge of AI/ML and python programming concepts. This book is also especially useful for developers looking to explore AI/ML with industry use cases.

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