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Lieferstatus:	Auf Bestellung (Lieferzeit unbekannt)
Veröffentlichung:	November 2025
Genre:	EDV / Informatik
	angewandte informatik / Application of Blockchain / Applications of Data Science / Basic Theory and Techniques for Data Science / Big Data Management and Applications / Computer and Information Systems Applications / Computers and Education / Data Mining and Knowledge Discovery / Data security and privacy / Data-driven Scientific Research / education research / Education using big data / Industrial Digitization and Applications / intelligent computing or data mining / Lehrmittel, Lerntechnologien, E-Learning / machine learning / Machine Learning for Data Science / Maschinelles Lernen / methods and materials for data science and engineering / Novel methods for data analytics / Wissensbasierte Systeme, Expertensysteme mehr...
ISBN:	9789819525652
EAN-Code:	9789819525652
Verlag:	Springer EN
Einband:	Kartoniert
Sprache:	English
Dimensionen:	H 235 mm / B 155 mm / D
Seiten:	636
Illustration:	XIX, 636 p. 215 illus., 179 illus. in color., farbige Illustrationen, schwarz-weiss Illustrationen
Zus. Info:	EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025.
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

This book constitutes the refereed proceedings of the 11th International Conference on Data Science, ICPCSEE 2025, held in Hiroshima, Japan, during September 19–21, 2025. The 41 full papers and 1 short papers included in this book were carefully reviewed and selected from 135 submissions. They were organized in topical sections as follows: Education using big data, intelligent computing or data mining, etc.; Education research, methods and materials for data science and engineering; Machine Learning for Data Science; Basic Theory and Techniques for Data Science; Application of Blockchain; Big Data Management and Applications; Industrial Digitization and Applications; Applications of Data Science; Data Security and Privacy; Data-driven Scientific Research; and Novel methods for data analytics.