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Ebay, Electronic Arts, Google, Microsoft, many financial institutions.



Are these production systems? I'm a bit blown away that this can work with R.

http://adv-r.had.co.nz/Performance.html


R is a glue language. The fast bits are always written in C++, FORTRAN, or wrapping a BLAS like LAPACK.

R-vs-Python is almost never the problem in production. Interpreted-vs-compiled is almost always the issue. (I'm aware of Numba and similar efforts. Last time I tried it, it sucked on nuts. And Theano is a rather specialized bit that most people don't actually need.)

JMHO. But I've never seen anyone dealing with truly huge data and inference problems that had the low-level bits in anything other than C++ or FORTRAN. I could imagine that Scala can do a pretty good job now, especially if you use Spark a lot. But R vs Python seems like a really stupid question. Use the one that has the libraries you need.


This. R vs. Python is a very stupid debate. Especially for speed. For example pandas is slower than data.table. There are plenty of ways to have performant models in R. If you are worried about performance in deployment, run H2O, for example, there are plenty others. There is also flashr, if you want to write your own algorithms, which swaps R's basic operators and data management with C++.

Also google is doing to R what they did to javqscript with v8. Expect GA next year.


What is GA?

I think the right answer is both.

And probably Javascript, too.


Yes, those are production systems like I said. Ebay scores their search results. EA scores customer lifetime value, churn, marketing communications.




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