ABSTRACT
'Natural Language Processing in the Real World' is a practical guide for applying data science and machine learning to build Natural Language Processing (NLP) solutions. Where traditional, academic-taught NLP is often accompanied by a data source or dataset to aid solution building, this book is situated in the real-world where there may not be an existing rich dataset.
This book covers the basic concepts behind NLP and text processing and discusses the applications across 15 industry verticals. From data sources and extraction to transformation and modelling, and classic Machine Learning to Deep Learning and Transformers, several popular applications of NLP are discussed and implemented.
This book provides a hands-on and holistic guide for anyone looking to build NLP solutions, from students of Computer Science to those involved in large-scale industrial projects.
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Table of Contents:
List of Figures
List of Tables
Contributors
Preface
Acknowledgements
Chapter 1: NLP Basics
Chapter 2: Data Sources and Extraction
Chapter 3: Data Preprocessing and Transformation
Chapter 4: Data Modeling
Chapter 5: NLP Applications – Active Usage
Chapter 6: NLP Applications – Developing Usage
Chapter 7: Information Extraction and Text Transforming Models
Chapter 8: Text Categorisation and Affinities
Chapter 9: Chatbots
Chapter 10: Customer Review Analysis
Chapter 11: Recommendations and Predictions
Chapter 12: More Real-World Scenarios and Tips
Bibliography
Index
