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Principles of data science

Arabnia, Hamid R.

Principles of data science

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Principles of data scienceedited by Hamid R. Arabnia ... [et al.].
其他作者:	Arabnia, Hamid R.
出版者:	Cham :Springer International Publishing :2020.
面頁冊數:	xiv, 278 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Big data.
電子資源:	https://doi.org/10.1007/978-3-030-43981-1
ISBN:	9783030439811$q(electronic bk.)

Principles of data science
Principles of data science[electronic resource] /edited by Hamid R. Arabnia ... [et al.]. - Cham :Springer International Publishing :2020. - xiv, 278 p. :ill., digital ;24 cm. - Transactions on computational science and computational intelligence,2569-7072. - Transactions on computational science and computational intelligence..

Introduction -- Data Acquisition, Extraction, and Cleaning -- Data Summarization and Modeling -- Data Analysis and Communication Techniques -- Data Science Tools -- Deep Learning in Data Science -- Data Science Applications -- Conclusion.

This book provides readers with a thorough understanding of various research areas within the field of data science. The book introduces readers to various techniques for data acquisition, extraction, and cleaning, data summarizing and modeling, data analysis and communication techniques, data science tools, deep learning, and various data science applications. Researchers can extract and conclude various future ideas and topics that could result in potential publications or thesis. Furthermore, this book contributes to Data Scientists' preparation and to enhancing their knowledge of the field. The book provides a rich collection of manuscripts in highly regarded data science topics, edited by professors with long experience in the field of data science. Introduces various techniques, methods, and algorithms adopted by Data Science experts Provides a detailed explanation of data science perceptions, reinforced by practical examples Presents a road map of future trends suitable for innovative data science research and practice.

ISBN: 9783030439811$q(electronic bk.)

Standard No.: 10.1007/978-3-030-43981-1doiSubjects--Topical Terms:

609582
Big data.

LC Class. No.: QA76.9.B45 / P756 2020

Dewey Class. No.: 005.7

Principles of data science
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505 0 $a Introduction -- Data Acquisition, Extraction, and Cleaning -- Data Summarization and Modeling -- Data Analysis and Communication Techniques -- Data Science Tools -- Deep Learning in Data Science -- Data Science Applications -- Conclusion.
520 $a This book provides readers with a thorough understanding of various research areas within the field of data science. The book introduces readers to various techniques for data acquisition, extraction, and cleaning, data summarizing and modeling, data analysis and communication techniques, data science tools, deep learning, and various data science applications. Researchers can extract and conclude various future ideas and topics that could result in potential publications or thesis. Furthermore, this book contributes to Data Scientists' preparation and to enhancing their knowledge of the field. The book provides a rich collection of manuscripts in highly regarded data science topics, edited by professors with long experience in the field of data science. Introduces various techniques, methods, and algorithms adopted by Data Science experts Provides a detailed explanation of data science perceptions, reinforced by practical examples Presents a road map of future trends suitable for innovative data science research and practice.
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