We build software with a community of users and developers, and educate scientists about transparent research practices.
Use our packages to acquire your data from both your own and from various data sources, analyze it, add your narrative and generate a final document in any of widely used formats such as Word, Markdown, PDF or LaTeX. Combine our tools with the rich ecosystem of R packages.
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|Reproducible workflows at scale with drake||2019/09/24||Community call (teleconference) 🌐||All are welcome||Ambitious workflows in R, such as machine learning analyses, can be difficult to manage. A single round of computation can take several hours to complete, and routine updates to the code and data tend to invalidate hard-earned results. You can enhance the maintainability, hygiene, speed, scale, and reproducibility of such projects with the drake R package. drake resolves the dependency structure of your analysis pipeline, skips tasks that are already up to date, executes the rest with optional distributed computing, and organizes the output so you rarely have to think about data files. This talk demonstrates how to create and maintain a realistic machine learning project using drake-powered automation.|
|LatinR 2019||2019/09/25 - 2019/09/27||Santiago, CL 🇨🇱||Maëlle Salmon||Maëlle Salmon will give a remote presentation (in Spanish!) on our open software peer review system.|
|rOpenSci Ozunconf19||2019/12/11 - 2019/12/13||Sydney, AU 🇦🇺||Steph Stammel , Karthik Ram||4th annual rOpenSci Ozunconf|