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Natural Language Processing with AWS AI Services

Natural Language Processing with AWS AI Services

By : M, Premkumar Rangarajan
5 (21)
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Natural Language Processing with AWS AI Services

Natural Language Processing with AWS AI Services

5 (21)
By: 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)
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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

Summary

In this chapter, we covered why you would need to use Amazon Comprehend and Amazon Comprehend Medical. We also discussed the challenges associated with setting NLP pipelines.

Then, we introduced these services, and covered some key benefits they provide, for example, not needing ML skills, or easily using the APIs to build scalable NLP solutions. After that, we showed some key product features of Amazon Comprehend and Amazon Comprehend Medical through a Console demo. Some of Amazon Comprehend's features are identifying entities, key phrases, and sentiment, as well as detecting dominant language, topic modeling, and so on. For Amazon Comprehend Medical, we covered how you can use both text analysis APIs and oncology APIs to enrich and extract key information from medical notes. Then we gave you a quick walkthrough of these APIs using a Jupyter notebook and covered sync and batch sync APIs. We gained a basic theoretical understanding of creating a serverless application...

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