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Data science in practice

Said, Alan.

Data science in practice

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Data science in practiceedited by Alan Said, Vicenc Torra.
其他作者:	Said, Alan.
出版者:	Cham :Springer International Publishing :2019.
面頁冊數:	viii, 195 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Big data.
電子資源:	https://doi.org/10.1007/978-3-319-97556-6
ISBN:	9783319975566$q(electronic bk.)

Data science in practice
Data science in practice[electronic resource] /edited by Alan Said, Vicenc Torra. - Cham :Springer International Publishing :2019. - viii, 195 p. :ill., digital ;24 cm. - Studies in big data,v.462197-6503 ;. - Studies in big data ;v.1..

Artiﬁcial intelligence -- Machine learning: a concise overview -- Information fusion -- Information retrieval & recommender systems -- Business intelligence -- Data privacy -- Visual data analysis -- Complex data analysis -- Big data programming with Apache Spark.

This book approaches big data, artificial intelligence, machine learning, and business intelligence through the lens of Data Science. We have grown accustomed to seeing these terms mentioned time and time again in the mainstream media. However, our understanding of what they actually mean often remains limited. This book provides a general overview of the terms and approaches used broadly in data science, and provides detailed information on the underlying theories, models, and application scenarios. Divided into three main parts, it addresses what data science is; how and where it is used; and how it can be implemented using modern open source software. The book offers an essential guide to modern data science for all students, practitioners, developers and managers seeking a deeper understanding of how various aspects of data science work, and of how they can be employed to gain a competitive advantage.

ISBN: 9783319975566$q(electronic bk.)

Standard No.: 10.1007/978-3-319-97556-6doiSubjects--Topical Terms:

609582
Big data.

LC Class. No.: QA76.9.B45 / D383 2019

Dewey Class. No.: 005.7

Data science in practice
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520 $a This book approaches big data, artificial intelligence, machine learning, and business intelligence through the lens of Data Science. We have grown accustomed to seeing these terms mentioned time and time again in the mainstream media. However, our understanding of what they actually mean often remains limited. This book provides a general overview of the terms and approaches used broadly in data science, and provides detailed information on the underlying theories, models, and application scenarios. Divided into three main parts, it addresses what data science is; how and where it is used; and how it can be implemented using modern open source software. The book offers an essential guide to modern data science for all students, practitioners, developers and managers seeking a deeper understanding of how various aspects of data science work, and of how they can be employed to gain a competitive advantage.
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