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Data science in theory and practice = techniques for big data analytics and complex data sets /
Record Type:
Electronic resources : 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 practice
techniques 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:
2045508
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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techniques for big data analytics and complex data sets /
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"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."--
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https://onlinelibrary.wiley.com/doi/book/10.1002/9781119674757
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W9463714
電子資源
11.線上閱覽_V
電子書
EB QA76.9.B45 M36 2022
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1 records • Pages 1 •
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