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:
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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.
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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.
Reihe
Sprache
Verlagsort
Verlagsgruppe
Springer International Publishing
Illustrationen
XV, 139 p. 24 illus., 15 illus. in color.
Dateigröße
ISBN-13
978-3-032-06889-7 (9783032068897)
DOI
10.1007/978-3-032-06889-7
Schweitzer Klassifikation
