Rachel Wagner-Kaiser

Teaching Computers to Read

Effective Best Practices in Building Valuable NLP Solutions

• Gebundenes Buch

Produktbeschreibung

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.

Produktdetails

• Verlag: Chapman and Hall/CRC
• Seitenzahl: 238
• Erscheinungstermin: 5. November 2025
• Englisch
• Abmessung: 240mm x 161mm x 17mm
• Gewicht: 526g
• ISBN-13: 9781032484372
• ISBN-10: 1032484373
• Artikelnr.: 74263604

Autorenporträt

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.

Inhaltsangabe

1. Debunking Common Myths in Natural Language Processing
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