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Natural Language Understanding with Python

You're reading from Natural Language Understanding with Python

Product type Book

Published in Jun 2023

Publisher Packt

ISBN-13 9781804613429

Pages 326 pages

Edition 1st Edition

Languages

Concepts

Machine Learning

Author (1):

Deborah A. Dahl

Table of Contents (21) Chapters

Preface

Part 1: Getting Started with Natural Language Understanding Technology

Chapter 1: Natural Language Understanding, Related Technologies, and Natural Language Applications

Chapter 2: Identifying Practical Natural Language Understanding Problems

Part 2:Developing and Testing Natural Language Understanding Systems

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

Chapter 4: Selecting Libraries and Tools for Natural Language Understanding

Chapter 5: Natural Language Data – Finding and Preparing Data

Chapter 6: Exploring and Visualizing Data

Chapter 7: Selecting Approaches and Representing Data

Chapter 8: Rule-Based Techniques

Chapter 9: Machine Learning Part 1 – Statistical Machine Learning

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

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

Chapter 12: Applying Unsupervised Learning Approaches

Chapter 13: How Well Does It Work? – Evaluation

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

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

Chapter 15: Summary and Looking to the Future

Index

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Technical requirements

We will be using the following data and software to run the examples in this chapter:

Our usual development environment – that is, Python 3 and Jupyter Notebook
The TREC dataset
The Matplotlib and Seaborn packages, which we will use to display graphical charts
pandas and NumPy for numerical manipulation of data
The BERT NLU system, previously used in Chapter 11 and Chapter 13
The Keras machine learning library, for working with BERT
NLTK, which we will use for generating new data
An OpenAI API key which we will use to access the OpenAI tools

The rest of the chapter is locked

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Authors (1)

Deborah A. Dahl

Deborah A. Dahl is the principal at Conversational Technologies, with over 30 years of experience in natural language understanding technology. She has developed numerous natural language processing systems for research, commercial, and government applications, including a system for NASA, and speech and natural language components on Android. She has taught over 20 workshops on natural language processing, consulted on many natural language processing applications for her customers, and written over 75 technical papers. Th is is Deborah's fourth book on natural language understanding topics. Deborah has a PhD in linguistics from the University of Minnesota and postdoctoral studies in cognitive science from the University of Pennsylvania.

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