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    Episode 22: Episode 22: Diving in to drake with Will Landau

    Episode 22: Episode 22: Diving in to drake with Will Landau

    FromThe R-Podcast

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    Episode 22: Episode 22: Diving in to drake with Will Landau

    FromThe R-Podcast

    ratings:
    Length:
    78 minutes
    Released:
    Mar 26, 2017
    Format:
    Podcast episode

    Description

    In this episode of the R-Podcast I have a conversation with my colleague Will Landau about his new R package drake (https://cran.rstudio.com/web/packages/drake/) that provides a powerful build system for analysis pipelines. In addition we have a fun R community roundup, listener feedback, and a couple of package picks to give you a gentle nod and a fun way to explore interpolation. If you have ideas for topics, questions, or other types of feedback, get in touch with me by heading over to the R-Podcast site at www.r-podcast.org (https://www.r-podcast.org), sending a note to thercast[at]gmail.com, or contacting me at @thercast on Twitter. As always thanks for tuning in and I hope you enjoy episode 22 of the R-Podcast!
    Released:
    Mar 26, 2017
    Format:
    Podcast episode

    Titles in the series (35)

    R is a free and open-source statistical computing environment. It has quickly become the leading choice of software used to develop cutting-edge statistical algorithms, innovative visualizations, and data processing, among other key features. R has seen tremendous growth in popularity and functionality over the last decade, largely due to the vibrant and devoted R community of users. Whether you have experience with commercial statistical software such as SAS or SPSS and want to learn R, or getting into statistical computing for the first time, the R-Podcast will provide you with valuable information and advice that will help you to tap into the power of R. Our intent is to start with the basic concepts that can be a struggle for those new to R and statistical computing. We will give practical advice on how to take advantage of R’s capabilities to accomplish innovative and robust data analyses. Along the way we will highlight the additional tools and packages that greatly enhance the experience of using R, and highlight resources that can help people become experts with R. While this podcast is not meant to be a series of lectures on statistics, we will use freely and publicly available data sets to illustrate both basic statistical analyses as well as state-of-the-art algorithms to show how powerful and robust R can be for analyzing today’s explosion of data. In addition to the audio podcast, we will also produce screencasts for hands-on demonstrations for those topics that are best explained via video.