
Springer Gabler
Mathematical Foundations of Big Data Analytics (English, Vladimir Shikhman)
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Specifications
| Publisher | Springer Gabler |
| Language | English |
| ISBN-13 | 9783662625200 |
| ISBN-10 | 3662625202 |
| Author | Vladimir Shikhman |
Product Description
About the Book
From the Back Cover In this textbook, basic mathematical models used in Big Data Analytics are presented and application-oriented references to relevant practical issues are made. Necessary mathematic 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 i…
ISBN: 9783662625200
Book Insights
What You'll Learn
- ·In-depth exploration of topics covered in Mathematical Foundations of Big Data Analytics
- ·Key concepts explained with clarity and practical examples
- ·Insights valuable for anyone studying or working in Springer Gabler
Who Should Read This
Students at the undergraduate and postgraduate level, as well as educators.
Key Highlights
- ·Brand new physical book delivered across India
- ·15-day hassle-free return policy
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Is Mathematical Foundations of Big Data Analytics available in English?
Mathematical Foundations of Big Data Analytics is available in English on GlowMirror.
Who is the author of Mathematical Foundations of Big Data Analytics?
Mathematical Foundations of Big Data Analytics is authored by Vladimir Shikhman.
Who published Mathematical Foundations of Big Data Analytics?
Mathematical Foundations of Big Data Analytics is published by Springer Gabler.
How many pages does Mathematical Foundations of Big Data Analytics have?
Page count information for Mathematical Foundations of Big Data Analytics is available in the specifications section of this page.
How long does it take to read Mathematical Foundations of Big Data Analytics?
At an average reading speed of 250 words per minute, reading Mathematical Foundations of Big Data Analytics takes a few hours to a few days depending on reading pace.
What is Mathematical Foundations of Big Data Analytics about?
About the Book
From the Back Cover In this textbook, basic mathematical models used in Big Data Analytics are presented and application-oriented references to relevant practical issues are made. Necessary mathematic tools are examined and applied to current problems of data analysis, such as brand...
Is Mathematical Foundations of Big Data Analytics suitable for beginners?
Whether Mathematical Foundations of Big Data Analytics is suitable for beginners depends on your background in Springer Gabler. Review the product description and specifications above for details on the target audience and difficulty level.
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Mathematical Foundations of Big Data Analytics is from the Springer Gabler edition/year. Check the specifications section for full edition details.
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