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 5: Creating NLP Search

In the previous chapters, you were introduced to Amazon Textract for extracting text from documents, and Amazon Comprehend to extract insights with no prior Machine Learning (ML) experience as a prerequisite. In the last chapter, we showed you how you can combine these features together to solve a real-world use case for document automation by giving an example of loan processing.

In this chapter, we will use the Amazon Textract and Amazon Comprehend services to show you how you can quickly set up an intelligent search solution with the integration of powerful elements, such as Amazon Elasticsearch, which is a managed service to set up search and log analytics, and Amazon Kendra, which is an intelligent managed search solution powered by ML for natural language search.

We will cover the following topics in this chapter:

  • Going over search use cases and choices for search solutions
  • Building a search solution for scanned images using Amazon...