PyCon X


2nd - 5th May 2019

R you ready for python?

As statisticians with a mac (aka data scientists :-) ) more and more often we turn around the central question: how to balance and mix the best of R and python? We slightly and slowly moved all of our data management towards python (etl and data movement) while being tied to R for statistical learning. We found to be more productive managing machine learning algorithms like random forest on scikit-learn, but for time series forecast or statistical matching (propensity or MIB methods) we rely on R and its libraries. One thing that we do now permanently in python is deploy to production (web serving/service). Anyway first thing, approaching each new project, is the selection of the whole stack: “when and why” use R or python. Analyzing [] threads we understood that we are in good company.

Do you have some questions on this talk?

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