There’s a concept in R of an analysis as a package, in which everything you need for your data analysis is contained within a custom package. When you install the package and build the vignettes, the data analysis is performed and results saved as a pretty HTML or PDF file, generated with R Markdown. I wanted to extend this concept to a machine learning model as a package.
If you listen to university advertisements for data science masters degrees, you’d believe that data scientists are so in-demand that they can walk into any company, state their salary, and start work straight away.
Whenever I take an interest in something I think to myself, “How can I combine this with R?”
When I found myself using R in a corporate environment, my workflow went like this:
That’s it for #useR2018. After 6 keynotes, 132 parallel sessions, many more lightning talks and posters, and an all-important conference dinner, we’ve reached the end of the week.