As an intermediate R programmer looking to dive into machine learning, should I choose Python or stick with R?

[alireza5969]

I am an intermediate R programmer with some experience in machine learning concepts and simple modeling in R. I have an opportunity to collaborate with a professional machine learning team that is okay with me using R, but I believe I will eventually need to switch to Python.

I have two tasks:

1. Learn Python (which can be postponed if I continue with R, but I know I will eventually need to switch).
2. Master a machine learning tool (Tidymodels, mlr3, or scikit-learn) to impress the team during the interview.

As I said, task 1 can be done later. But, task 2 should be done in a few weeks. Therefore, if you think that I should go for Python, please consider that I have an interview in very near future, so I have to master both Python and ML.

I understand that Python is more memory-efficient and has better GPU access, but I’ve also heard good things about R’s ML packages like Tidymodels and mlr3.

Given that R has a promising future in ML but Python is currently more widely used, what should I do? What is the roadmap? If I should stick with R, which packages should I use and what resources should I learn?

Thank you!

[joesho112358]

Just my opinion, but learning a library, that is common to both, in the language you know seems like a good stepping stone into the language you want to know.

So maybe you’ll have time to learn some Python after the library which is probably a smaller undertaking anyway