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Advances in data sciencemethodologie...

Esposito, Anna.

Advances in data sciencemethodologies and applications /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Advances in data scienceedited by Gloria Phillips-Wren, Anna Esposito, Lakhmi C. Jain.
其他題名:	methodologies and applications /
其他作者:	Phillips-Wren, Gloria.
出版者:	Cham :Springer International Publishing :2021.
面頁冊數:	xvii, 333 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Electronic data processing.
電子資源:	https://doi.org/10.1007/978-3-030-51870-7
ISBN:	9783030518707$q(electronic bk.)

Advances in data sciencemethodologies and applications /
Advances in data sciencemethodologies and applications /[electronic resource] :edited by Gloria Phillips-Wren, Anna Esposito, Lakhmi C. Jain. - Cham :Springer International Publishing :2021. - xvii, 333 p. :ill., digital ;24 cm. - Intelligent systems reference library,v.1891868-4394 ;. - Intelligent systems reference library ;v.24..

Big data and data science are transforming our world today in ways we could not have imagined at the beginning of the twenty-first century. The accompanying wave of innovation has sparked advances in healthcare, engineering, business, science, and human perception, among others. The tremendous advances in computing power and intelligent techniques have opened many opportunities for managing data and investigating data in virtually every field, and the scope of data science is expected to grow over the next decade. These future research achievements will solve old challenges and create new opportunities for growth and development. Thus, the research presented in this book is interdisciplinary and covers themes embracing emotions, artificial intelligence, robotics applications, sentiment analysis, smart city problems, assistive technologies, speech melody, and fall and abnormal behavior detection. The book is directed to the researchers, practitioners, professors and students interested in recent advances in methodologies and applications of data science. An introduction to the topic is provided, and research challenges and future research opportunities are highlighted throughout.

ISBN: 9783030518707$q(electronic bk.)

Standard No.: 10.1007/978-3-030-51870-7doiSubjects--Topical Terms:

201945
Electronic data processing.

LC Class. No.: QA76 / .A38 2021

Dewey Class. No.: 004

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