Book Image

Natural Language Processing with AWS AI Services

By : Mona M, Premkumar Rangarajan
Book Image

Natural Language Processing with AWS AI Services

By: Mona M, Premkumar Rangarajan

Overview of this book

Natural language processing (NLP) uses machine learning to extract information from unstructured data. This book will help you to move quickly from business questions to high-performance models in production. To start with, you'll understand the importance of NLP in today’s business applications and learn the features of Amazon Comprehend and Amazon Textract to build NLP models using Python and Jupyter Notebooks. The book then shows you how to integrate AI in applications for accelerating business outcomes with just a few lines of code. Throughout the book, you'll cover use cases such as smart text search, setting up compliance and controls when processing confidential documents, real-time text analytics, and much more to understand various NLP scenarios. You'll deploy and monitor scalable NLP models in production for real-time and batch requirements. As you advance, you'll explore strategies for including humans in the loop for different purposes in a document processing workflow. Moreover, you'll learn best practices for auto-scaling your NLP inference for enterprise traffic. Whether you're new to ML or an experienced practitioner, by the end of this NLP book, you'll have the confidence to use AWS AI services to build powerful NLP applications.
Table of Contents (23 chapters)
1
Section 1:Introduction to AWS AI NLP Services
5
Section 2: Using NLP to Accelerate Business Outcomes
15
Section 3: Improving NLP Models in Production

Overcoming challenges with document processing

Automating operational activities is very important for organizations looking to minimize costs, increase productivity, and enable faster go-to-market cycles. Typically, operations that are at the core of these businesses are prioritized for automation. Back-office support processes, including administrative tasks, are often relegated to the bottom of the priority list because they may not be deemed mission critical. According to this Industry Analysts report (https://www.industryanalysts.com/111015_konica/, written in 2015, with data collected from sources such as Gartner Group, AIIM, the US Department of Labor, Imaging Magazine, and Coopers and Lybrand, and accessed on March 30, 2021), organizations continue to be reliant on paper-based documents, and the effort required to maintain these documents poses significant challenges due to the lack of automation and inefficiencies in the document workflow.

Many organizations, such as financial...