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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
Languages
Concepts
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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

Index

As this ebook edition doesn't have fixed pagination, the page numbers below are hyperlinked for reference only, based on the printed edition of this book.

B

bag of words

documents, putting into 55-59

BART model 224

BERTopic

reference link 192

topics, visualizing from 187-191

used, for topic modeling 157-162

Best Match 25 (bm25) 217

Bidirectional Encoder Representations from Transformer (BERT)

used, for K-Means topic modeling 153-157

using, instead of word embeddings 73-76

bigram model 59

C

Central Processing Unit (CPU) 199

character n-grams 64

chatbot

creating, with LLM 257-262

classification (CLS) tokens 197

classifier-invariant approach

explainability, enhancing via 228-232

Closed Domain Question Answering (CDQA) 214

CNN DailyMail dataset 224

code generation

with LLM 263-269

community detection clustering

with SBERT 150-152

Compute Unified Device Architecture (CUDA) 198

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