Also saying "Math is not JS's strength' is somewhat of an invalid statement. We shouldn't establish strengths of a language based on popular opinion. We should consider how the interpreters themselves operate with a language. It's possible to find research that shows node.js being considerably faster than python which by pop culture is good with math. In the end if your task is math heavy you will need to adapt the language to your needs and have a strong understanding about how it works. If you do that it won't matter that much which language you'll use to get your results and bring people on the ML band wagon.
I think the JS ecosystem is so big I'd assume it would have a library for everything. Maybe it's not the ideal language for lots of things but these days it's the universal tool.
(Not sure if I'm replying to the intended comment, I'm somewhat confused by the lack of a reply button on certain comments)
It's possible to find research that shows node.js being considerably faster than python which by pop culture is good with math.
This isn't really a fair comparison. Nodejs is a V8-based javascript runtime that does just-in-time compilation and python is just a language. There are Python runtimes that also do just-in-time compilation, so a fair comparison would involve comparable runtimes.
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Every language has its strengths. Math is not JS's strength so why use it for something that's inherently math-heavy?
if I'm not mistaken, tensorflow utilizes WebGL to operate on hardware (mainly GPU) so the performance hit by js is not aggressive.
Also, it can be a learning platform for people that are more used to JS, it can start here and move to another language later.
Also saying "Math is not JS's strength' is somewhat of an invalid statement. We shouldn't establish strengths of a language based on popular opinion. We should consider how the interpreters themselves operate with a language. It's possible to find research that shows node.js being considerably faster than python which by pop culture is good with math. In the end if your task is math heavy you will need to adapt the language to your needs and have a strong understanding about how it works. If you do that it won't matter that much which language you'll use to get your results and bring people on the ML band wagon.
Couple of sources:
I think the JS ecosystem is so big I'd assume it would have a library for everything. Maybe it's not the ideal language for lots of things but these days it's the universal tool.
(Not sure if I'm replying to the intended comment, I'm somewhat confused by the lack of a reply button on certain comments)
This isn't really a fair comparison. Nodejs is a V8-based javascript runtime that does just-in-time compilation and python is just a language. There are Python runtimes that also do just-in-time compilation, so a fair comparison would involve comparable runtimes.