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 1: NLP in the Business Context and Introduction to AWS AI Services

Natural language processing, or NLP, is quite popular in the scientific community, but the value of using this Artificial Intelligence (AI) technique to gain business benefits is not immediately obvious to mainstream users. Our focus will be to raise awareness and educate you on the business context of NLP, provide examples of the proliferation of data in unstructured text, and show how NLP can help derive meaningful insights to inform strategic decisions within an enterprise.

In this introductory chapter, we will be establishing the basic context to familiarize you with some of the underlying concepts of AI and Machine Learning (ML), the types of challenges that NLP can help solve, common pitfalls when building NLP solutions, and how NLP works and what it's really good at doing, with examples.

In this chapter, we will cover the following:

  • Introducing NLP
  • Overcoming the challenges in building NLP solutions
  • Understanding why NLP is becoming mainstream
  • Introducing the AWS ML stack