Best practices of orchestrating Python and R code in ML projects

Best practices of orchestrating #Python and #rstats code in #MachineLearning projects

  • Instead of arguing about Python vs R I will examine the best practices of integrating both languages in one data science project.
  • Today, data scientists are generally divided among two languages — some prefer R, some prefer Python.
  • Usually algorithms used for classification or regression are implemented in both languages and some scientist are using R while some of them preferring Python.
  • Instead of using logistic regression in R we will write Python jobs in which we will try to use random forest as training model.
  • py is presented below: – – Also here we are adding code for download necessary R and Python codes from above (clone the Githubrepository): – – Our dependency graph of this data science project look like this: – – Now lets see how it is possible to speed up and simplify…


Instead of arguing about Python vs R I will examine the best practices of integrating both languages in one data science project.

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