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

Summary

In this chapter, we built a solution using Amazon Kendra to automate searching for and deriving insights from document corpuses without having to manually read through the documents, understand the context, interpret the meaning, identify content across documents relevant to a common topic, and so on. We also saw how to set up an intelligent AI-based chat assistant using Amazon Lex that implicitly integrated with the Amazon Kendra intelligent search feature to provide a seamless chat and voice interface for (literally) "talking" to the document. Finally, we used a best practices approach with AWS CloudFormation to deploy our chatbot to a parent website as an embedded widget and distributed it using the Amazon CloudFront content delivery network.

Interestingly, NLP has diverse uses in the field of medicine, as we will see in the next chapter, where we will review how NLP and AI technologies have helped transform modern-day medical claims processing. We will start...