Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
Type of Medium
Language
Region
Library
Years
Person/Organisation
Subjects(RVK)
  • 1
    Book
    Book
    Oakland, Calif. : University of California Press
    UID:
    gbv_799813265
    Format: XI, 252 S. , graph. Darst.
    Edition: 1. ed.
    ISBN: 0520280989 , 0520280970 , 9780520280984 , 9780520280977
    Content: "We live, today, in world of big data. The amount of information collected on human behavior every day is staggering, and exponentially greater than at any time in the past. At the same time, we are inundated by stories of powerful algorithms capable of churning through this sea of data and uncovering patterns. These techniques go by many names - data mining, predictive analytics, machine learning - and they are being used by governments as they spy on citizens and by huge corporations are they fine-tune their advertising strategies. And yet social scientists continue mainly to employ a set of analytical tools developed in an earlier era when data was sparse and difficult to come by. In this timely book, Paul Attewell and David Monaghan provide a simple and accessible introduction to Data Mining geared towards social scientists. They discuss how the data mining approach differs substantially, and in some ways radically, from that of conventional statistical modeling familiar to most social scientists. They demystify data mining, describing the diverse set of techniques that the term covers and discussing the strengths and weaknesses of the various approaches. Finally they give practical demonstrations of how to carry out analyses using data mining tools in a number of statistical software packages. It is the hope of the authors that this book will empower social scientists to consider incorporating data mining methodologies in their analytical toolkits"--Provided by publisher
    Content: "We live, today, in world of big data. The amount of information collected on human behavior every day is staggering, and exponentially greater than at any time in the past. At the same time, we are inundated by stories of powerful algorithms capable of churning through this sea of data and uncovering patterns. These techniques go by many names - data mining, predictive analytics, machine learning - and they are being used by governments as they spy on citizens and by huge corporations are they fine-tune their advertising strategies. And yet social scientists continue mainly to employ a set of analytical tools developed in an earlier era when data was sparse and difficult to come by. In this timely book, Paul Attewell and David Monaghan provide a simple and accessible introduction to Data Mining geared towards social scientists. They discuss how the data mining approach differs substantially, and in some ways radically, from that of conventional statistical modeling familiar to most social scientists. They demystify data mining, describing the diverse set of techniques that the term covers and discussing the strengths and weaknesses of the various approaches. Finally they give practical demonstrations of how to carry out analyses using data mining tools in a number of statistical software packages. It is the hope of the authors that this book will empower social scientists to consider incorporating data mining methodologies in their analytical toolkits"--Provided by publisher
    Note: Literaturverz. S. 239-244 , Erscheinungsjahr in Vorlageform:[2015]
    Additional Edition: ISBN 9780520960596
    Additional Edition: ISBN 0520960599
    Language: English
    Subjects: Computer Science , Sociology
    RVK:
    RVK:
    RVK:
    Keywords: Sozialwissenschaften ; Data Mining ; Sozialwissenschaften ; Data Mining
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
Did you mean 0520280849?
Did you mean 0520209893?
Did you mean 0520230949?
Close ⊗
This website uses cookies and the analysis tool Matomo. Further information can be found on the KOBV privacy pages