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    Mastering Spark with R. The Complete Guide to Large-Scale Analysis and Modeling

    (ebook) (audiobook) (audiobook) Język publikacji: angielski
    Mastering Spark with R. The Complete Guide to Large-Scale Analysis and Modeling Javier Luraschi, Kevin Kuo, Edgar Ruiz - okładka ebooka

    Mastering Spark with R. The Complete Guide to Large-Scale Analysis and Modeling Javier Luraschi, Kevin Kuo, Edgar Ruiz - okładka ebooka

    Mastering Spark with R. The Complete Guide to Large-Scale Analysis and Modeling Javier Luraschi, Kevin Kuo, Edgar Ruiz - okładka audiobooka MP3

    Mastering Spark with R. The Complete Guide to Large-Scale Analysis and Modeling Javier Luraschi, Kevin Kuo, Edgar Ruiz - okładka audiobooks CD

    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Stron:
    296
    Dostępne formaty:
    ePub
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    If you’re like most R users, you have deep knowledge and love for statistics. But as your organization continues to collect huge amounts of data, adding tools such as Apache Spark makes a lot of sense. With this practical book, data scientists and professionals working with large-scale data applications will learn how to use Spark from R to tackle big data and big compute problems.

    Authors Javier Luraschi, Kevin Kuo, and Edgar Ruiz show you how to use R with Spark to solve different data analysis problems. This book covers relevant data science topics, cluster computing, and issues that should interest even the most advanced users.

    • Analyze, explore, transform, and visualize data in Apache Spark with R
    • Create statistical models to extract information and predict outcomes; automate the process in production-ready workflows
    • Perform analysis and modeling across many machines using distributed computing techniques
    • Use large-scale data from multiple sources and different formats with ease from within Spark
    • Learn about alternative modeling frameworks for graph processing, geospatial analysis, and genomics at scale
    • Dive into advanced topics including custom transformations, real-time data processing, and creating custom Spark extensions

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