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Data science in societal applicationsconcepts and implications /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Data science in societal applicationsedited by Siddharth Swarup Rautaray, Manjusha Pandey, Nhu Gia Nguyen.
其他題名:	concepts and implications /
其他作者:	Rautaray, Siddharth Swarup.
出版者:	Singapore :Springer Nature Singapore :2022.
面頁冊數:	xi, 193 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Data mining.
電子資源:	https://doi.org/10.1007/978-981-19-5154-1
ISBN:	9789811951541$q(electronic bk.)

Data science in societal applicationsconcepts and implications /
Data science in societal applicationsconcepts and implications /[electronic resource] :edited by Siddharth Swarup Rautaray, Manjusha Pandey, Nhu Gia Nguyen. - Singapore :Springer Nature Singapore :2022. - xi, 193 p. :ill., digital ;24 cm. - Studies in big data,v. 1142197-6511 ;. - Studies in big data ;v.1..

Cloud GIS Model for Coastal Geospatial Big Data Analytics -- Appealing AI in Appalling Covid-19 Crisis and the Impending -- Role of Data Science in Programmatic Advertising -- Social Development Data and Societal Modelling: A study in Indian Context -- Deep learning Trends and Inspired Systems in Natural Language Processing.

The book provides an insight into the practical applications and theoretical foundation of data science. The book discusses new ways of embracing agile approaches to various facets of data science, including machine learning and artificial intelligence, data mining, data visualization, and communication. The book includes contributions from academia and industry experts detailing the shortfalls of current tools and techniques used and generating the blueprint of the new technologies. The topics covered in the book range from theoretical and foundational research, platforms, methods, applications, and tools in data science. The chapters in the book add a social, geographical, and temporal dimension to data science research. The papers included are application-oriented that prepare and use data in discovery research. This book will provide researchers and practitioners with a detailed snapshot of current progress in data science. Moreover, it will stimulate new study, research, and the development of new applications.

ISBN: 9789811951541$q(electronic bk.)

Standard No.: 10.1007/978-981-19-5154-1doiSubjects--Topical Terms:

184440
Data mining.

LC Class. No.: QA76.9.D343 / D37 2022

Dewey Class. No.: 006.312

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