國立虎尾科技大學 |

Data science in theory and practice = techniques for big data analytics and complex data sets /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Data science in theory and practice/ Maria Cristina Mariani, Osei Kofi Tweneboah, Maria Pia Beccar-Varela.
Reminder of title:	techniques for big data analytics and complex data sets /
Author:	Mariani, Maria C.
other author:	Tweneboah, Osei Kofi,
Published:	Hoboken, NJ :Wiley, : 2022.,
Description:	1 online resource (xxiv, 370 p.) :ill. (some col.) :
Subject:	Big data. -
Online resource:	https://onlinelibrary.wiley.com/doi/book/10.1002/9781119674757
ISBN:	9781119674757

Data science in theory and practice = techniques for big data analytics and complex data sets /
Mariani, Maria C.

Data science in theory and practicetechniques for big data analytics and complex data sets /[electronic resource] :Maria Cristina Mariani, Osei Kofi Tweneboah, Maria Pia Beccar-Varela. - Hoboken, NJ :Wiley,2022. - 1 online resource (xxiv, 370 p.) :ill. (some col.)

Includes bibliographical references and index.

"This textbook is dedicated to practitioners, graduate, and advanced undergraduate students who have interest in Data Science, Business analytics, and Statistical and Mathematical Modeling in different disciplines such as Finance, Geophysics, and Engineering. This book is designed to serve as a textbook for several courses in the aforementioned areas and a reference guide for practitioners in the industry. The book has a strong theoretical background and several applications to specific practical problems. It contains numerous techniques applicable to modern data science and other disciplines. In today's world, many fields are confronted with increasingly large amounts of complex data. Financial, healthcare, and geophysical data sampled with high frequency is no exception. These staggering amounts of data pose special challenges to the world of finance and other disciplines such as healthcare and geophysics, as traditional models and information technology tools can be poorly suited to grapple with their size and complexity. Probabilistic modeling, mathematical modeling, and statistical data analysis attempt to discover order from apparent disorder; this textbook may serve as a guide to various new systematic approaches on how to implement these quantitative activities with complex data sets."--

ISBN: 9781119674757Subjects--Topical Terms:

981821
Big data.

LC Class. No.: QA76.9.B45 / M36 2022

Dewey Class. No.: 005.7

Data science in theory and practice = techniques for big data analytics and complex data sets /
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020 $a 9781119674757 $q (electronic bk.)
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020 $a 9781119674702 $q (electronic bk.)
020 $z 9781119674689 $q (hbk.)
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050 0 4 $a QA76.9.B45 $b M36 2022
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100 1 $a Mariani, Maria C. $3 1421411
245 1 0 $a Data science in theory and practice $h [electronic resource] : $b techniques for big data analytics and complex data sets / $c Maria Cristina Mariani, Osei Kofi Tweneboah, Maria Pia Beccar-Varela.
260 $a Hoboken, NJ : $b Wiley, $c 2022.
300 $a 1 online resource (xxiv, 370 p.) : $b ill. (some col.)
504 $a Includes bibliographical references and index.
520 $a "This textbook is dedicated to practitioners, graduate, and advanced undergraduate students who have interest in Data Science, Business analytics, and Statistical and Mathematical Modeling in different disciplines such as Finance, Geophysics, and Engineering. This book is designed to serve as a textbook for several courses in the aforementioned areas and a reference guide for practitioners in the industry. The book has a strong theoretical background and several applications to specific practical problems. It contains numerous techniques applicable to modern data science and other disciplines. In today's world, many fields are confronted with increasingly large amounts of complex data. Financial, healthcare, and geophysical data sampled with high frequency is no exception. These staggering amounts of data pose special challenges to the world of finance and other disciplines such as healthcare and geophysics, as traditional models and information technology tools can be poorly suited to grapple with their size and complexity. Probabilistic modeling, mathematical modeling, and statistical data analysis attempt to discover order from apparent disorder; this textbook may serve as a guide to various new systematic approaches on how to implement these quantitative activities with complex data sets."-- $c Provided by publisher.
588 $a Description based on print version record.
650 0 $a Big data. $3 981821
650 0 $a Data mining. $3 528622
700 1 $a Tweneboah, Osei Kofi, $d 1988- $3 1421412
700 1 $a Beccar-Varela, Maria Pia. $3 1421413
856 4 0 $u https://onlinelibrary.wiley.com/doi/book/10.1002/9781119674757