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Python Natural Language Processing Cookbook

You're reading from   Python Natural Language Processing Cookbook Over 60 recipes for building powerful NLP solutions using Python and LLM libraries

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Product type Paperback
Published in Sep 2024
Publisher Packt
ISBN-13 9781803245744
Length 312 pages
Edition 2nd Edition
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Authors (2):
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Saurabh Chakravarty Saurabh Chakravarty
Author Profile Icon Saurabh Chakravarty
Saurabh Chakravarty
Zhenya Antić Zhenya Antić
Author Profile Icon Zhenya Antić
Zhenya Antić
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Toc

Table of Contents (13) Chapters Close

Preface 1. Chapter 1: Learning NLP Basics 2. Chapter 2: Playing with Grammar FREE CHAPTER 3. Chapter 3: Representing Text – Capturing Semantics 4. Chapter 4: Classifying Texts 5. Chapter 5: Getting Started with Information Extraction 6. Chapter 6: Topic Modeling 7. Chapter 7: Visualizing Text Data 8. Chapter 8: Transformers and Their Applications 9. Chapter 9: Natural Language Understanding 10. Chapter 10: Generative AI and Large Language Models 11. Index 12. Other Books You May Enjoy

Natural Language Understanding

In this chapter, we will explore recipes that will allow us to interpret and understand the text contained in short as well as long passages. Natural language understanding (NLU) is a very broad term and the various systems developed as part of NLU do not interpret or understand a passage of text the same way a human reader would. However, based on the specificity of the task, we can create some applications that can be combined to generate an interpretation or understanding that can be used to solve a given problem related to text processing.

Organizations that have a huge document corpus need a seamless way to search through documents. More specifically, what users really need is an answer to a specific question without having to glean through a list of documents that are returned as part of a document search. Users would prefer the query to be formulated as a question in natural language and the answer to be emitted in the same manner.

Another...

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