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100%: Vladimir Shikhman; David Müller: Mathematical Foundations of Big Data Analytics (ISBN: 9783662625217) Springer Shop, in Englisch, auch als eBook.Nur diese Ausgabe anzeigen…
76%: Shikhman, Vladimir, Müller, David: Mathematical Foundations of Big Data Analytics (ISBN: 9783662625200) Springer Berlin Heidelberg, Erstausgabe, in Deutsch, Taschenbuch.Nur diese Ausgabe anzeigen…
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Mathematical Foundations of Big Data Analytics
~EN NW EB DLISBN: 9783662625217 bzw. 3662625210, vermutlich in Englisch, Springer Shop, neu, E-Book, elektronischer Download.
Lieferung aus: Vereinigtes Königreich Grossbritannien und Nordirland, Lagernd, zzgl. Versandkosten.
In this textbook, basic mathematical models used in Big Data Analytics are presented and application-oriented references to relevant practical issues are made. Necessary mathematical tools are examined and applied to current problems of data analysis, such as brand loyalty, portfolio selection, credit investigation, quality control, product clustering, asset pricing etc. – mainly in an economic context. In addition, we discuss interdisciplinary applications to biology, linguistics, sociology, electrical engineering, computer science and artificial intelligence. For the models, we make use of a wide range of mathematics – from basic disciplines of numerical linear algebra, statistics and optimization to more specialized game, graph and even complexity theories. By doing so, we cover all relevant techniques commonly used in Big Data Analytics. Each chapter starts with a concrete practical problem whose primary aim is to motivate the study of a particular Big Data Analytics technique. Next, mathematical results follow – including important definitions, auxiliary statements and conclusions arising. Case-studies help to deepen the acquired knowledge by applying it in an interdisciplinary context. Exercises serve to improve understanding of the underlying theory. Complete solutions for exercises can be consulted by the interested reader at the end of the textbook; for some which have to be solved numerically, we provide descriptions of algorithms in Python code as supplementary material. This textbook has been recommended and developed for university courses in Germany, Austria and Switzerland. eBook.
In this textbook, basic mathematical models used in Big Data Analytics are presented and application-oriented references to relevant practical issues are made. Necessary mathematical tools are examined and applied to current problems of data analysis, such as brand loyalty, portfolio selection, credit investigation, quality control, product clustering, asset pricing etc. – mainly in an economic context. In addition, we discuss interdisciplinary applications to biology, linguistics, sociology, electrical engineering, computer science and artificial intelligence. For the models, we make use of a wide range of mathematics – from basic disciplines of numerical linear algebra, statistics and optimization to more specialized game, graph and even complexity theories. By doing so, we cover all relevant techniques commonly used in Big Data Analytics. Each chapter starts with a concrete practical problem whose primary aim is to motivate the study of a particular Big Data Analytics technique. Next, mathematical results follow – including important definitions, auxiliary statements and conclusions arising. Case-studies help to deepen the acquired knowledge by applying it in an interdisciplinary context. Exercises serve to improve understanding of the underlying theory. Complete solutions for exercises can be consulted by the interested reader at the end of the textbook; for some which have to be solved numerically, we provide descriptions of algorithms in Python code as supplementary material. This textbook has been recommended and developed for university courses in Germany, Austria and Switzerland. eBook.
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Mathematical Foundations of Big Data Analytics
DE PB NW FEISBN: 9783662625200 bzw. 3662625202, in Deutsch, Springer Gabler, Taschenbuch, neu, Erstausgabe.
Lieferung aus: Deutschland, Dieser Artikel ist noch nicht erschienen. Jetzt vorbestellen vor und wir liefern Ihnen den Artikel sobald er verfügbar ist. Lieferung von Amazon, Versandkostenfrei.
Von Händler/Antiquariat, Amazon.de.
Springer Gabler, Taschenbuch, Ausgabe: 1st ed. 2021, Publiziert: 2021-03-13T00:00:01Z, Produktgruppe: Book.
Von Händler/Antiquariat, Amazon.de.
Springer Gabler, Taschenbuch, Ausgabe: 1st ed. 2021, Publiziert: 2021-03-13T00:00:01Z, Produktgruppe: Book.
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Mathematical Foundations of Big Data Analytics
~EN PB NWISBN: 9783662625200 bzw. 3662625202, vermutlich in Englisch, Springer Shop, Taschenbuch, neu.
Lieferung aus: Deutschland, En Stock, frais de port.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
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Mathematical Foundations of Big Data Analytics Vladimir Shikhman Author
~DE PB NWISBN: 9783662625200 bzw. 3662625202, vermutlich in Deutsch, Springer Berlin Heidelberg, Taschenbuch, neu.
Lieferung aus: Vereinigte Staaten von Amerika, zzgl. Versandkosten.
Mathematical Foundations of Big Data Analytics,Vladimir Shikhman.
Mathematical Foundations of Big Data Analytics,Vladimir Shikhman.
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