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Data science in theory and practice ...

Beccar-Varela, Maria Pia,

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

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Data science in theory and practice :Maria C. Mariani, Osei Kofi Tweneboah, Maria Pia Beccar-Varela.
其他題名:	techniques for big data analytics and complex data sets /
作者:	Mariani, Maria C.,
其他作者:	Beccar-Varela, Maria Pia,
出版者:	Hoboken, NJ :Wiley,2022.
面頁冊數:	xxiv, 370 p. :ill. ;24 cm.
標題:	Big data.
ISBN:	9781119674689 :

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 /Maria C. Mariani, Osei Kofi Tweneboah, Maria Pia Beccar-Varela. - 1st ed. - Hoboken, NJ :Wiley,2022. - xxiv, 370 p. :ill. ;24 cm.

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 differentdisciplines such as Finance, Geophysics, and Engineering. This book isdesigned to serve as a textbook for several courses in the aforementioned areas and a reference guide for practitioners in the industry. The book hasa 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 noexception. These staggering amounts of data pose special challenges to the world of finance and other disciplines such as healthcare and geophysics, astraditional 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: 9781119674689 :NT$3402

LCCN: 2021043993Subjects--Topical Terms:

609582
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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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 differentdisciplines such as Finance, Geophysics, and Engineering. This book isdesigned to serve as a textbook for several courses in the aforementioned areas and a reference guide for practitioners in the industry. The book hasa 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 noexception. These staggering amounts of data pose special challenges to the world of finance and other disciplines such as healthcare and geophysics, astraditional 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.
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