Overview
- Discusses implementations and case studies
- Identifies the best design practices
- Assesses data analytics business models and practices in industry, health care, administration and business
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Big Data (SBD, volume 24)
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Table of contents (12 chapters)
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Front Matter
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Fundamentals
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Front Matter
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Applications
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Front Matter
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Back Matter
Keywords
About this book
Data science and big data go hand in hand and constitute a rapidly growing area of research and have attracted the attention of industry and business alike. The area itself has opened up promising new directions of fundamental and applied research and has led to interesting applications, especially those addressing the immediate need to deal with large repositories of data and building tangible, user-centric models of relationships in data. Data is the lifeblood of today’s knowledge-driven economy.
Numerous data science models are oriented towards end users and along with the regular requirements for accuracy (which are present in any modeling), come the requirements for ability to process huge and varying data sets as well as robustness, interpretability, and simplicity (transparency). Computational intelligence with its underlying methodologies and tools helps address data analytics needs.
The book is of interest to those researchers and practitioners involved in data science, Internet engineering, computational intelligence, management, operations research, and knowledge-based systems.
Editors and Affiliations
Bibliographic Information
Book Title: Data Science and Big Data: An Environment of Computational Intelligence
Editors: Witold Pedrycz, Shyi-Ming Chen
Series Title: Studies in Big Data
DOI: https://doi.org/10.1007/978-3-319-53474-9
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing AG 2017
Hardcover ISBN: 978-3-319-53473-2Published: 29 March 2017
Softcover ISBN: 978-3-319-85162-4Published: 21 July 2018
eBook ISBN: 978-3-319-53474-9Published: 21 March 2017
Series ISSN: 2197-6503
Series E-ISSN: 2197-6511
Edition Number: 1
Number of Pages: VIII, 303
Number of Illustrations: 21 b/w illustrations, 80 illustrations in colour
Topics: Computational Intelligence, Data Mining and Knowledge Discovery, Artificial Intelligence, Big Data/Analytics, Health Informatics, Health Care Management