Engineering and Management of Data Science, Analytics, and AI/ML Projects: Foundations, Models, Frameworks, Architectures, Standards, Processes, ... (Intelligent Systems Reference Library, 282) - Hardcover

 
9783032068880: Engineering and Management of Data Science, Analytics, and AI/ML Projects: Foundations, Models, Frameworks, Architectures, Standards, Processes, ... (Intelligent Systems Reference Library, 282)
Hardcover
ISBN 10: 3032068886 ISBN 13: 9783032068880
Publisher: Springer, 2025

Synopsis

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.

"synopsis" may belong to another edition of this title.

From the Back Cover

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.

"About this title" may belong to another edition of this title.

Publisher
Springer
Publication date
2025
Language
English
ISBN 10 
3032068886
ISBN 13 
9783032068880
Binding
Hardcover
Number of pages
154
Editor
Mora Manuel, Gómez Jorge Marx, Wang Fen, Duran-Limon Hector A.