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

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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

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20. Other Books You May Enjoy

Preface

Natural language understanding (NLU) is a technology that structures language so that computer systems can further process it to perform useful applications.

Developers will find that this practical guide enables them to use NLU techniques to develop many kinds of NLU applications, and managers will be able to identify areas where NLU can be applied to solve real problems in their enterprises.

Complete with step-by-step explanations of essential concepts and practical examples, you will begin by learning what NLU is and how it can be applied. You will then learn about the wide range of current NLU techniques, and you will learn about the best situations to apply each one, including the new large language models (LLMs). In the process, you will be introduced to the most useful Python NLU libraries. Not only will you learn the basics of NLU, but you will also learn about many practical issues such as acquiring data, evaluating systems, improving your system’s results, and deploying NLU applications. Most importantly, you will not just learn a rote list of techniques, but you will learn how to take advantage of the vast number of NLU resources on the web in your future work.

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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

Preface

Authors (1)

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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

Preface

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