Engineering and Management of Data Science, Analytics, and AI/ML Projects, Gebunden
Engineering and Management of Data Science, Analytics, and AI/ML Projects
- Foundations, Models, Frameworks, Architectures, Standards, Processes, Practices, Platforms and Tools for Small and Big Data
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- Herausgeber:
- Manuel Mora, Jorge Marx Gómez, Fen Wang, Hector A. Duran-Limon
- Verlag:
- Springer-Verlag GmbH, 01/2026
- Einband:
- Gebunden
- Sprache:
- Englisch
- ISBN-13:
- 9783032068880
- Artikelnummer:
- 12421056
- Umfang:
- 154 Seiten
- Sonstiges:
- Approx. 230 p.
- Erscheinungstermin:
- 5.1.2026
- Hinweis
-
Achtung: Artikel ist nicht in deutscher Sprache!
Klappentext
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.
