You're reading from Natural Language Understanding with Python Combine natural language technology, deep learning, and large language models to create human-like language comprehension in computer systems

Product type Paperback

Published in Jun 2023

Publisher Packt

ISBN-13 9781804613429

Length 326 pages

Edition 1st Edition

Languages

Python

Tools

Combine

Concepts

Deep Learning

Author (1):

Deborah A. Dahl

View More author details

Table of Contents (21) Chapters

Preface

1. Part 1: Getting Started with Natural Language Understanding Technology

2. Chapter 1: Natural Language Understanding, Related Technologies, and Natural Language Applications FREE CHAPTER

3. Chapter 2: Identifying Practical Natural Language Understanding Problems

4. Part 2:Developing and Testing Natural Language Understanding Systems

5. Chapter 3: Approaches to Natural Language Understanding – Rule-Based Systems, Machine Learning, and Deep Learning

6. Chapter 4: Selecting Libraries and Tools for Natural Language Understanding

7. Chapter 5: Natural Language Data – Finding and Preparing Data

8. Chapter 6: Exploring and Visualizing Data

9. Chapter 7: Selecting Approaches and Representing Data

10. Chapter 8: Rule-Based Techniques

11. Chapter 9: Machine Learning Part 1 – Statistical Machine Learning

12. Chapter 10: Machine Learning Part 2 – Neural Networks and Deep Learning Techniques

13. Chapter 11: Machine Learning Part 3 – Transformers and Large Language Models

14. Chapter 12: Applying Unsupervised Learning Approaches

15. Chapter 13: How Well Does It Work? – Evaluation

16. Part 3: Systems in Action – Applying Natural Language Understanding at Scale

17. Chapter 14: What to Do If the System Isn’t Working

18. Chapter 15: Summary and Looking to the Future

19. Index

Why subscribe?

20. 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.

ablation 232

accuracy 164, 236

accuracy problems

application, restructuring 270

changing data 264

fixing 263

activation function 181, 186

example 187

air travel information system (ATIS) 233

analytics 12

annotations 29, 30

APIsList 31

URL 31

Apple Translate app

reference link 285

application data 31

application programming interfaces (APIs) 20

application, restructuring 270

classes, dividing 272, 273

classes, merging 272

need, visualizing 270, 271

applications, without NLP 26

graphical interfaces, using 27, 28

inputs, recognizing from known list of words 27

sufficient data availability, ensuring 28, 29

text, analyzing with regular expressions 26

application-specific types, techniques 89

class labels, substituting...

The rest of the chapter is locked

You're reading from Natural Language Understanding with Python Combine natural language technology, deep learning, and large language models to create human-like language comprehension in computer systems

Table of Contents (21) Chapters

Index

Authors (1)

Personalised recommendations for you

You're reading from Natural Language Understanding with Python Combine natural language technology, deep learning, and large language models to create human-like language comprehension in computer systems

Table of Contents (21) Chapters

Index

Unlock this book and the full library FREE for 7 days

Authors (1)

Personalised recommendations for you