Teaching Computers to Read - Effective Best Practices in Building Valuable NLP Solutions

This book provides clarity and guidance on how to design, develop, deploy, and maintain Natural Language Processing (NLP) solutions that address real-world business problems. It will help organizations use critical thinking to understand how, when, and why to build NLP solutions, and how to address or avoid common challenges.

List of contents

1. Natural Language Processing: Debunking Common Myths 2. The Trajectory of Natural Language Processing: Classic, Modern, and Generative 3. Large Language Models and Generative Artificial Intelligence 4. Pre-Processing and Exploratory Data Analysis for NLP 5. Framing the Task and Data Labeling 6. Data Curation for NLP Corpora 7. Machine Learning Approaches for Natural Language Problems 8. Working Across Languages in NLP 9. Evaluating Performance of NLP Solutions 10. Maintaining Value: Deploying and Monitoring NLP Solutions 11. NLPOps: The Mechanics of NLP Production at Scale 12. Ethics in Data Science and NLP 13. Key Factors for Successful NLP Solutions

About the author

Rachel Wagner-Kaiser has 15 years of experience in data and AI, entering the data science field after completing her Ph.D. in astronomy. She specializes in building natural language processing solutions for real-world problems constrained by limited or messy data. Rachel leads technical teams to design, build, deploy, and maintain NLP solutions, and her expertise has helped companies organize and decode their unstructured data to solve a variety of business problems and drive value through automation.

Product details

• Authors: Rachel Wagner-Kaiser
• Publisher: Taylor and Francis
• Languages: English
• Product format: Hardback
• Release: 04.11.2025
• EAN: 9781032484372
• ISBN: 978-1-032-48437-2
• No. of pages: 232
• Illustrations: schwarz-weiss Illustrationen, Raster,schwarz-weiss, Zeichnungen, schwarz-weiss, Tabellen, schwarz-weiss
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; Data Mining, Artificial Intelligence, COMPUTERS / Computer Science, BUSINESS & ECONOMICS / Statistics, COMPUTERS / Programming / Games, COMPUTERS / Machine Theory, Technical design, Probability & statistics, Ethical & social aspects of IT, Legal aspects of IT, Automatic control engineering, Probability and statistics, COMPUTERS / Artificial Intelligence / General, Database design and theory, COMPUTERS / Data Science / Machine Learning, COMPUTERS / Data Science / Data Analytics, COMPUTERS / Languages / Python, Digital and information technologies: Legal aspects, Database design & theory