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

Setting up your AWS environment

Important Note

Please do not execute the instructions in this section on their own. This section is a reference for all the basic setup tasks needed throughout the book. You will be guided to this section when building your solution in this chapter and the rest of the chapters in this book. Only execute these tasks when so guided.

Depending on the chapter you are in, you will be running tasks using the AWS Management Console, an Amazon SageMaker Jupyter notebook, from your command line, or a combination of any of these. Either way, you need the right AWS Identity and Access Management (IAM) permissions, resources, and, in most cases, one or more Amazon Simple Storage Service (S3) buckets, as prerequisites for your solution builds. This section provides instructions for setting up these basic tasks. We will be referring to this section throughout the rest of the chapters in the book as needed.

Signing up for an AWS account

In this chapter...