Data Science and Big Data: An Environment of Computational Intelligence
Softcover reprint of the original 1st ed. 2017
Book Details
Format
Paperback / Softback
Book Series
Studies in Big Data
ISBN-10
3319851624
ISBN-13
9783319851624
Edition
Softcover reprint of the original 1st ed. 2017
Publisher
Springer International Publishing AG
Imprint
Springer International Publishing AG
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Jul 21st, 2018
Print length
303 Pages
Product Classification:
Health economicsHealth economicsComputer aided manufacture (CAM)Digital and Information technology: general topicsInformation technology: general issuesDatabasesDatabases / Data managementData miningArtificial intelligenceArtificial intelligence (AI)Expert systems / knowledge-based systems
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This book presents a comprehensive and up-to-date treatise of a range of methodological and algorithmic issues. It also discusses implementations and case studies, identifies the best design practices, and assesses data analytics business models and practices in industry, health care, administration and business.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.
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