I’ve always wanted to explore julia, I’ve used it for a few things but never had the time to make something decently sized. Anyone here have any experience with it?

I’ve always wanted to explore julia, I’ve used it for a few things but never had the time to make something decently sized. Anyone here have any experience with it?

Tangentially, how does Julia compare to R and Python? (Not asking to you specifically, but extending your question; hope that's okay.) Especially for statistics.

Tangentially, how does Julia compare to R and Python? (Not asking to you specifically, but extending your question; hope that's okay.) Especially for statistics.

Much faster if you use the type system, not as many packages (yet) as R in statistics. But more labs and researchers are adopting it so it may change in the future. The documentation for the...

Much faster if you use the type system, not as many packages (yet) as R in statistics. But more labs and researchers are adopting it so it may change in the future. The documentation for the packages is not as great as in R though. I think it's a great sub for numpy, scipy, maybe even simpy soon. In terms of ML/DL I'm not sure, but there are people who prefer Julia's flux to tensorflow or pytorch. In terms of stats, I'll use it instead of R but only because I like to develop packages and play with the low level implementation. But I think if you just want out-of-the-box statistical analysis, R is going to be better (not to speak of the incredible tidyverse).

I’ve always wanted to explore julia, I’ve used it for a few things but never had the time to make something decently sized. Anyone here have any experience with it?

Tangentially, how does Julia compare to R and Python? (Not asking to you specifically, but extending your question; hope that's okay.) Especially for statistics.

Much faster if you use the type system, not as many packages (yet) as R in statistics. But more labs and researchers are adopting it so it may change in the future. The documentation for the packages is not as great as in R though. I think it's a great sub for numpy, scipy, maybe even simpy soon. In terms of ML/DL I'm not sure, but there are people who prefer Julia's flux to tensorflow or pytorch. In terms of stats, I'll use it instead of R but only because I like to develop packages and play with the low level implementation. But I think if you just want out-of-the-box statistical analysis, R is going to be better (not to speak of the incredible tidyverse).

There's some discussion here, but no real answers.

Thanks!