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Herausgeber: 
  • Richard S. Segall
  • Gao Niu
  • Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 14-24 Tagen versandfertig
    Veröffentlichung:  Februar 2020  
    Genre:  EDV / Informatik 
     
    COMPUTERS / Software Development & Engineering / General
    ISBN:  9781799827689 
    EAN-Code: 
    9781799827689 
    Verlag:  Engineering Science Reference 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 260 mm / B 183 mm / D 18 mm 
    Gewicht:  685 gr 
    Seiten:  256 
    Zus. Info:  HC gerader Rücken kaschiert 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    With the development of computing technologies in today's modernized world, software packages have become easily accessible. Open source software, specifically, is a popular method for solving certain issues in the field of computer science. One key challenge is analyzing big data due to the high amounts that organizations are processing. Researchers and professionals need research on the foundations of open source software programs and how they can successfully analyze statistical data. Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities provides emerging research exploring the theoretical and practical aspects of cost-free software possibilities for applications within data analysis and statistics with a specific focus on R and Python. Featuring coverage on a broad range of topics such as cluster analysis, time series forecasting, and machine learning, this book is ideally designed for researchers, developers, practitioners, engineers, academicians, scholars, and students who want to more fully understand in a brief and concise format the realm and technologies of open source software for big data and how it has been used to solve large-scale research problems in a multitude of disciplines.

      



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