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

Creating an Amazon Kendra index with Amazon S3 as a data source

In this section, we will first create an Amazon Kendra index and add the S3 bucket to which we uploaded our sample research documents in the previous section, as an Amazon S3 data source.

Note

Before you continue, please ensure you have executed the steps in the Technical requirements section and the pre-requisites mentioned in the Introducing the chatbot use case section.

Please execute the following steps to create your Amazon Kendra index:

  1. If not already done, log in to your AWS Management Console as per the instructions in the Technical requirements section in Chapter 2, Introducing Amazon Textract.
  2. Type kendra in the Services search bar in the top center of the page and select Amazon Kendra from the list. When the Amazon Kendra console opens up, click Create an Index, as shown here:
    Figure 11.1 – Creating an Amazon Kendra index

    Figure 11.1 – Creating an Amazon Kendra index

  3. In the Specify index details page, type a name for your...