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If Python was a barrier on data/ML, then certainly the the data/ML community would have circled around a different programming language... but it didn't. All ev
by DwnVoteHoneyPot 5y ago
If Python was a barrier on data/ML, then certainly the the data/ML community would have circled around a different programming language... but it didn't. All evidence says Python has some quality about it that that makes it good for data/ML but you think it's a drag? You even point out that Swift couldn't replace it despite efforts.
The author has the same weird logic that Python wouldn't be as popular without Numpy... but it does have Numpy... Usain Bolt wouldn't be as fast if he didn't have legs too.
- alfor 5y agoIt’s better than the rest at the moment. Let’s say you have small amount of data, 1Go than can easily fit in the memory of a laptop. You try to load or do analysis of that with python. The only way to make it work is to use a library that is build in C. Forget doing for loop over that thing. So each library has to build a language of parameters to allow you to use the speed and memory efficiency of C. Effectively in ML python act as a config language for C. So all the actual work has to happen in C, but all your experiment are in python. That create a barrier to innovation as you hit limit of performance on python and you have to switch language. But yeah, all the library are in Python and most of the work is still done there so it’s very hard for people to move to something else because they would have to rebuild a huge part of the stack, there is a strong network effect here. But the core language is still very bad for performance computing.