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Nvidia GPU enabled machine learning and linear algebra in R
- jey 15y agoIMO, just use python unless you absolutely have to use R for some other reason. You can still call R functions using rpy2. EDIT: My suggestion is to use Python if you're starting a new project, since it has a wider ecosystem you can tap into, including PyCUDA and Theano. A lot of the other new development and nifty packages for scentific computing are Python centric.
- minimax 15y agoI find myself using Python for application development and dropping into R for interactive data analysis. ggplot2 is really pleasant to use while matplotlib just sort of feels like a better gnuplot.
- disgruntledphd2 15y agoI use R for most of my statistical analysis, but have also used Python. Its an awful lot easier to get started with analysis in R, as its specialised for importing data, running analyses and plotting. It also has methods for everything else one can imagine. That being said, Python is friendly, intuitive and fun so I really like it as a language, but I don't want to have to re implement all of my R workflow (mostly psychometrics which isn't available in python). Python is so much better for data manipulation tasks is not even funny. Sure, you can use readlines and reshape in R, but Python really excels at this sort of stuff. If you have more of your stack in Python, then it probably looks like a better choice, and the ecosystem for general programming is much larger, but around statistical analysis R is where its at. Most of the problems people are having with R (slow, single threaded) are not going to be greatly improved by moving to Python, while the advantages of R is that one can get people who know some statistical analysis to use this as a foundation to learn programming. I started with R, and now have completely gotten the programming bug. So maybe that's another advantage for R.
- pavelkaroukin 15y agoAnyone know something similar, but for more universal OpenCL platform?
- zeratul 15y agoI can only guess that jey's comment was downvoted because R is more prevalent language for statistics and data mining when compared to Python: http://www.kdnuggets.com/polls/2011/languages-for-data-mining-analytics.html http://www.kdnuggets.com/polls/2011/languages-for-data-minin... Thus, there is a much larger ecosystem as it comes to STATISTICS and data mining in R. Cluster analysis packages are especially advanced in R. BTW, there is an effort to have OpenMP support in core R, e.g. the "dist" function: http://r.789695.n4.nabble.com/How-to-safely-use-OpenMP-pragma-inside-a-C-function-td3777036.html http://r.789695.n4.nabble.com/How-to-safely-use-OpenMP-pragm... EDIT: I was able to compile and run some of the functions under MacOSX 10.6 and R 2.13.1. I couldn't get it to compile with CULA (free version) and my GPU hardware is 1.1 so I can't run SVM :-(
- ketralnis 15y ago> I can only guess that jey's comment was downvoted because R is more prevalent language for statistics and data mining when compared to Python I'd imagine he was downvoted for coming into a "Here's how to do this thing in language X" thread and spouting about why everyone is using their own favourite toy instead of his own favourite toy.