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If you're a #dataScientist working in #rstats, you've probably heard of #docker, but might not know why you'd care or how to get started...
Here's a thread summarizing my talk from #useR2022 from a few weeks ago, and a link to my free online book📕!
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Here's a thread summarizing my talk from #useR2022 from a few weeks ago, and a link to my free online book📕!
🧵
Docker is a general tool for packaging code with its dependencies.
So in the data science world, Docker is a tool for reproducibility + portability. Docker can make it easy to share your work with others, or to keep it safe for later.
So in the data science world, Docker is a tool for reproducibility + portability. Docker can make it easy to share your work with others, or to keep it safe for later.
When you think about reproducing an R project, there are layers of reproducibility, as you make things more reproducible, it also takes more work. 
