Engineering and Management of Data Science, Analytics and Ai/Ml Projects: Foundations, Models, Frameworks, Architectures, Standards, Processes, ... and Tools for Small and Big Data: 282 - Rilegato

Rilegato

ISBN 10: 3032068886 ISBN 13: 9783032068880

Casa editrice: Springer-Nature New York Inc, 2025

Riassunto

This book presents a dual perspective on modern research and praxis on Data Science, Analytics, and AI/Machine Learning (DSA-AI/ML) system with small or big data. Consequently, potential readers—academics, researchers and practitioners interested in the systematic development and implementation of DSA-AI/ML systems—can be benefited with the high-quality conceptual and empirical research chapters focused on:

• Foundations,  Development  Platforms, and Tools on Engineering and Management of DSA-AI/ML Projects:
  • DSA-AI/ML reference architectures.
  • Data visualization principles for DSA-AI/ML.
  • Federated Learning in large-scale DSA-AI/ML systems.
• Achievements, Challenges, Trends, and Future Research Directions on DSA-AI/ML Projects:
  • Large multimodal model-based simulation game for DSA-AI/ML systems.
  • Value stream analysis and design applied to DSA-AI/ML systems.
  • Quality management 4.0 and AI for DSA-AI/ML systems.

Hence, this research-oriented co-edited book contributes to achieve the systematic development and implementation of Data Science, Analytics, and AI/ML systems.

Su questo libro

Dalla quarta di copertina

This book presents a dual perspective on modern research and praxis on Data Science, Analytics, and AI/Machine Learning (DSA-AI/ML) system with small or big data. Consequently, potential readers—academics, researchers and practitioners interested in the systematic development and implementation of DSA-AI/ML systems—can be benefited with the high-quality conceptual and empirical research chapters focused on:

• Foundations,  Development  Platforms, and Tools on Engineering and Management of DSA-AI/ML Projects:
  • DSA-AI/ML reference architectures.
  • Data visualization principles for DSA-AI/ML.
  • Federated Learning in large-scale DSA-AI/ML systems.
• Achievements, Challenges, Trends, and Future Research Directions on DSA-AI/ML Projects:
  • Large multimodal model-based simulation game for DSA-AI/ML systems.
  • Value stream analysis and design applied to DSA-AI/ML systems.
  • Quality management 4.0 and AI for DSA-AI/ML systems.

Hence, this research-oriented co-edited book contributes to achieve the systematic development and implementation of Data Science, Analytics, and AI/ML systems.

Dettagli dell'edizione

• Editore: Springer-Nature New York Inc
• Data di pubblicazione: 2025
• Lingua: Inglese
• ISBN 10: 3032068886
• ISBN 13: 9783032068880
• Rilegatura: Copertina rigida
• Numero di pagine: 230
• Redattore: Mora Manuel, Gmez Jorge Marx, Wang Fen, Duran-limon Hector A.
• Contatto del produttore: ProductSafety@springernature.com; ProductSafety@springernature.com; ; Poststr. 9; Darmstadt; 64293; Germania