These are chat archives for FreeCodeCamp/DataScience
discussion on how we can use statistical methods to measure and improve the efficacy of http://freeCodeCamp.com
Language has never been a barrier
@AbhimanyuAryan If you’re referring to D3, I agree. D3 is awesome, though the learning curve is steep and it's incredibly verbose compared to other exploratory visualization libaries in R (and even python). D3 has been more so used to showcase final results after all the work has been done. It typically hasn’t served well for the day to day grind of doing data science work, at least in my experience. I know Mike B. has created a notebook product to try to make it more interactive.
JS is fast, but is it faster than other compiled languages like C/C++? These languages are called by R and python to perform all the heavy lifting, so the intense operations are not interpreted. If JS is not faster than C/C++, then maybe Google’s play with TensorflowJS is somewhere elsewhere. Maybe JS will have some unforseen innovation in DS/AI given it’s the canonical web language.
The label put on this kind of work is another discussion (I’m not sure it’s entirely important what we call it) and highly subjective.
As for tools, I don’t doubt there are libraries available in JS to do the work (cool link you sent). The question is it easier or harder to do the job? By how much? Any friction has a cost on daily work, and could dramatically slow down or cause a project to fail. Some times the friction is mild enough that it does not matter though. I think JS is cool! I just think there are better tools to do DS work at the moment. Maybe that will change in the future.