Neural Networks at Work in Industry

Artificial Intelligence and Machine Learning AI & Computing

Neural Networks at Work in Industry

The proposed book takes neural networks and industry applications as one coherent problem rather than two disconnected topics. Historical and contemporary materials are used selectively, giving the reader enough conceptual depth to judge competing explanations. The emphasis is on neural networks viewed through industry applications, with architecture examples, reproducible experiments, benchmarks, and technology tradeoffs. Which claims can be tested independently, and which remain interpretive?

PublisherLighthouse Books, Delaware, USA

Universal Book ID22601

SeriesArtificial Intelligence and Machine Learning

SubjectNeural Networks

DisciplineAI & Computing

LanguageEnglish

CategoryComputing and information-systems study

TagsNeural Networks

Introduction — Neural Networks at Work in Industry
1. The Problem and Its Vocabulary in Neural Networks
2. Evidence, Sources, and Their Limits for Industry Applications
3. Historical and Conceptual Foundations of Neural Networks
4. Methods for Comparative Inquiry in Artificial Intelligence and Machine Learning
5. Institutions, Practices, and Context: Neural Networks
6. Conclusions and Research Agenda: Industry Applications
7. Historical Pathways and Change: Artificial Intelligence and Machine Learning
8. Why Definitions Matter: Neural Networks
9. Ethics, Access, and Practical Limits: Industry Applications
10. Mechanisms and Explanatory Models: Artificial Intelligence and Machine Learning
11. Synthesis and Further Questions: Neural Networks
12. Observation, Measurement, and Meaning: Industry Applications
Conclusion — What the Evidence Allows
References and Further Reading
Index