Is Julia the new language of choice for machine learning?

Julia is one of the fastest growing programming languages of 2018. Flux a machine learning library written in Julia stack already makes it easier to write ML code.

Today, Python and R dominate machine learning and are continuing to grow too. How does Julia eco-system feel like to you? Is it going to be the new language of choice for ML?

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Comments (1)

Mark's photo

Well, it's hard to overcome the kind of inertia that Python and R have. So I think it can go either way.

(Imho that inertia is the whole reason it's still Python and R, rather than just Python).

But I think that if some language disrupts the status quo in the field, it'll be probably be Julia. I think it has many of the important qualities

  • Quick prototyping, with some scalability (e.g. optional types)
  • Good performance (compared to py/R), and C interop
  • Easy for people for whom programming is a tool, not their main career
  • Focused on numerical applications

except the most important one

  • A massive ML ecosystem

Honestly, I don't think the difference is big enough for the switch to be fast, but I think new users who haven't already invested a lot in py/R may prefer it and cause it to grow.

Jason Knight posted a question earlier this year, perhaps he can say smarter things about it than me.