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Principles of Data Science

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Principles of Data Science/ edited by Hamid R. Arabnia, Kevin Daimi, Robert Stahlbock, Cristina Soviany, Leonard Heilig, Kai Brüssau.
other author:	Arabnia, Hamid R.
Description:	XIV, 276 p. 102 illus., 55 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Electrical engineering. -
Online resource:	https://doi.org/10.1007/978-3-030-43981-1
ISBN:	9783030439811

Principles of Data Science
Principles of Data Science[electronic resource] /edited by Hamid R. Arabnia, Kevin Daimi, Robert Stahlbock, Cristina Soviany, Leonard Heilig, Kai Brüssau. - 1st ed. 2020. - XIV, 276 p. 102 illus., 55 illus. in color.online resource. - 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

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

596380
Electrical engineering.

LC Class. No.: TK1-9971

Dewey Class. No.: 621.382

Principles of Data Science
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