Natural Language Processing in the Real World

Text Processing, Analytics, and Classification
1. Auflage 2023
ISBN: 978-1-032-19533-9
Verlag: Taylor & Francis Ltd

Buch, Englisch, 388 Seiten, Format (B × H): 261 mm x 182 mm, Gewicht: 868 g

Reihe: Chapman & Hall/CRC Data Science Series

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.

Zielgruppe

Academic, Further/Vocational Education, General, and Postgraduate

Autoren/Hrsg.

Singh, Jyotika

Fachgebiete

• Mathematik | Informatik EDV | Informatik Business Application Unternehmenssoftware
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Spiele-Programmierung, Rendering, Animation
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Spracherkennung, Sprachverarbeitung
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsarchitektur
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Datenbankdesign & Datenbanktheorie
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsvisualisierung

Inhaltsverzeichnis

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

Über Autor(innen)

Jyotika Singh is an accomplished data science expert specializing in Machine Learning and Natural Language Processing (NLP). With a burning passion for sharing knowledge, Jyotika has graced countless stages as a sought-after speaker at prestigious conferences worldwide. Her remarkable aptitude for crafting inventive solutions using NLP and real-world datasets has garnered numerous patents strategically adopted by prestigious tech enterprises. As Director of Data Science at Placemakr and having led the Data Science team at ICX Media, Jyotika's expertise shines through her invaluable contributions to multiple industry verticals generating multi-million dollar revenue using practical application of data science and NLP. Moreover, her research at University of California, Los Angeles (UCLA) has further solidified her profound expertise. Jyotika is revered as the visionary creator of multiple open-source Python libraries, most notably pyAudioProcessing. Beyond her technical accomplishments, Jyotika displays unwavering dedication to promoting diversity in STEM fields, mentoring aspiring talents, and actively engaging in global initiatives. Her exceptional contributions have garnered a multitude of prestigious awards, including her distinction as one of the top 50 Women of Impact in 2023 and her inclusion among the top 100 most influential people in Data 2022 by DataIQ. Additionally, Jyotika has been honored with the Data Science Leadership award in 2022 and the Leadership Excellence in Technology award in 2021, among other noteworthy accolades.