9781482249071-1482249073-Handbook of Big Data (Chapman & Hall/CRC Handbooks of Modern Statistical Methods)

Handbook of Big Data (Chapman & Hall/CRC Handbooks of Modern Statistical Methods)

ISBN-13: 9781482249071
ISBN-10: 1482249073
Edition: 1
Author: Michael Kane, Peter Bühlmann, Petros Drineas, Mark van der Laan
Publication date: 2016
Publisher: Chapman and Hall/CRC
Format: Hardcover 464 pages
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Book details

ISBN-13: 9781482249071
ISBN-10: 1482249073
Edition: 1
Author: Michael Kane, Peter Bühlmann, Petros Drineas, Mark van der Laan
Publication date: 2016
Publisher: Chapman and Hall/CRC
Format: Hardcover 464 pages

Summary

Handbook of Big Data (Chapman & Hall/CRC Handbooks of Modern Statistical Methods) (ISBN-13: 9781482249071 and ISBN-10: 1482249073), written by authors Michael Kane, Peter Bühlmann, Petros Drineas, Mark van der Laan, was published by Chapman and Hall/CRC in 2016. With an overall rating of 4.0 stars, it's a notable title among other Statistics (Education & Reference) books. You can easily purchase or rent Handbook of Big Data (Chapman & Hall/CRC Handbooks of Modern Statistical Methods) (Hardcover) from BooksRun, along with many other new and used Statistics books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

Handbook of Big Data provides a state-of-the-art overview of the analysis of large-scale datasets. Featuring contributions from well-known experts in statistics and computer science,this handbookpresents a carefully curated collection of techniques from both industry and academia. Thus, the text instills a working understanding of key statistical and computing ideas that can be readily applied in research and practice.

Offering balanced coverage of methodology, theory, and applications, this handbook:

  • Describes modern, scalable approaches for analyzing increasingly large datasets
  • Defines the underlying concepts of the available analytical tools and techniques
  • Details intercommunity advances in computational statistics and machine learning

Handbook of Big Data also identifies areas in need of further development, encouraging greater communication and collaboration between researchers in big data sub-specialties such as genomics, computational biology, and finance.

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