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 6: Using NLP to Improve Customer Service Efficiency

So far, we have seen a couple of interesting real-world NLP use cases with intelligent document processing solutions for loan applications in Chapter 4, Automating Document Processing Workflows, and built smart search indexes in Chapter 5, Creating NLP Search. NLP-based indexing for content search is becoming very popular because it bridges the gap between traditional keyword-based searches, which can be frustrating unless you know exactly what keyword to use, and natural language, to quickly search for what you are interested in. We also saw how we can use Amazon Textract and Amazon Comprehend with services such as Amazon Elasticsearch (https://aws.amazon.com/elasticsearch-service/), a service that's fully managed by AWS and provides search and analytics capabilities offered by the open source Elasticsearch, but without the need for infrastructure heavy lifting, installation, or maintenance associated with setting up...