- 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.
Continue reading “Best practices of orchestrating Python and R code in ML projects”