Intelligent Systems Reference Library: Foundations, Models, Frameworks, Architectures, Standards, Processes, Practices, Platforms and Tools for Small and Big Data

Mora, Manuel; Gómez, Jorge Marx; Wang, Fen; Duran-Limon, Hector A.

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.

Details

Published by: Springer

Publication Date: 2025-11-16

Format: Hardcover

ISBN-13: 9783032068880

DOI: 10.1007/978-3-032-06889-7

Dimensions: 235cm x155cm

Pages: 139