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

Chapter 17: Visualizing Insights from Handwritten Content

In the previous chapters, we talked about and learned how to build Intelligent Document Processing (IDP) pipelines using Amazon Textract, Amazon Comprehend, and Amazon A2I. The advantage of setting up such pipelines is that you introduce automation into your operational processes and unlock insights that were previously not so evident. Speaking of insights, what are they exactly and why is everyone so interested in mining text, and of what use can they be?

To answer this, let's summon Doc Brown and Marty McFly's time-traveling car, the DeLorean from the movie Back to the Future, and travel back to Chapter 1, NLP in the Business Context and Introduction to AWS AI Services, to re-read the Understanding why NLP is becoming mainstream section. Remember now? Maybe this will help: according to Webster's dictionary (https://www.merriam-webster.com/), the word "insight" is defined as "the act or result...