Language-agnostic data analysis work?ows and reproducible research, Inter-experimental Machine Learning (IML) Working Group Meeting, April 2017
This was a talk about language-agnostic (or polyglot) analysis work?ows. I show how it is possible to work in multiple languages and switch between them without leaving the work?ow you started. Additionally, I demonstrate how an entire work?ow can be encapsulated in a markdown ?le that is rendered to a publishable paper with cross-references and a bibliography (and with raw LaTeX ?le produced as a by-product) in a simple process, making the whole analysis work?ow reproducible. Example output is shown here. For experimental particle physics, ROOT is the ubiquitous data analysis tool, and has been for the last 20 years old, so I also talk about how to exchange data to and from ROOT.
This was a talk that I gave at CERN at the Inter-experimental Machine Learning (IML) Working Group Meeting in April 2017.
The slides for this talk can be found here.
Data Scientist ? Consultant ? PhD in Particle Physics ? Ex-CERN ? Part of team to discover Higgs boson ? Trans ally ?????????
6 年https://blog.rstudio.com/2018/03/26/reticulate-r-interface-to-python/
Data Scientist ? Consultant ? PhD in Particle Physics ? Ex-CERN ? Part of team to discover Higgs boson ? Trans ally ?????????
6 年I don't believe it: on the very same day that I published this old talk, RStudio announce the "reticulate" package, a comprehensive set of tools for interoperability between Python and R! There is much in my talk that isn't covered by this package, but if you have workflows that require both Python and R you should use that instead!