You could deploy a rocker image, possibly with an API (built with plumber). But I think it is misleading to refer to that as an executable.
On May 6, 2020 11:39:09 PM PDT, Paul Bernal <paulberna...@gmail.com> wrote: >Dear Jeff, an executable in terms of deploying a machine learning >model, >whether it a classifocation, regression, time series or deep learning >model. > >Best regards, > >Paul > >El jue., 7 de mayo de 2020 1:22 a. m., Jeff Newmiller < >jdnew...@dcn.davis.ca.us> escribió: > >> There is no executable that can run on any OS. As for python... it is >> hardly the only game in town for building executables, but it and >those >> other options are off topic here. >> >> On May 6, 2020 10:53:00 PM PDT, Paul Bernal <paulberna...@gmail.com> >> wrote: >> >Dear Jeff, >> > >> >Thank you for the feedback. So, after reading your comments, it >seems >> >that, >> >in order to develop an executable model that could be run in any OS, >> >python >> >might be the way to go then? >> > >> >I appreciate all of your valuable responses. >> > >> >Best regards, >> > >> >Paul >> > >> >El mié., 6 de mayo de 2020 6:22 p. m., Jeff Newmiller < >> >jdnew...@dcn.davis.ca.us> escribió: >> > >> >> Large data... yes, though how this can be done may vary. I have >used >> >> machines with 128G of RAM before with no special big data >packages. >> >> >> >> Making an executable... theoretically, yes, though there are some >> >> significant technical (and possibly legal) challenges that will >most >> >likely >> >> make you question whether it was worth it if you try, particularly >if >> >your >> >> intent is to obscure your code from the recipient. I (as a random >> >user and >> >> programmer on the Internet) would strongly discourage such >efforts... >> >it >> >> will almost certainly be more practical to deliver code in >> >script/package >> >> form. >> >> >> >> On May 6, 2020 2:20:47 PM PDT, Paul Bernal ><paulberna...@gmail.com> >> >wrote: >> >> >Dear R friends, >> >> > >> >> >Hope you are doing well. I have two questions, the first one is, >can >> >I >> >> >work >> >> >with very large datasets in R? That is, say I need to test >several >> >> >machine >> >> >learning algorithms, like (random forest, multiple linear >> >regression, >> >> >etc.) >> >> >on datasets having between 50 to 100 columns and 20 million >> >> >observations, >> >> >is there any way that R can handle data that large? >> >> > >> >> >The second question is, is there a way I can develop an R model >and >> >> >turn it >> >> >into an executable program that can work on any OS? >> >> > >> >> >Any help and/or guidance will be greatly appreciated, >> >> > >> >> >Best regards, >> >> > >> >> >Paul >> >> > >> >> > [[alternative HTML version deleted]] >> >> > >> >> >______________________________________________ >> >> >R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see >> >> >https://stat.ethz.ch/mailman/listinfo/r-help >> >> >PLEASE do read the posting guide >> >> >http://www.R-project.org/posting-guide.html >> >> >and provide commented, minimal, self-contained, reproducible >code. >> >> >> >> -- >> >> Sent from my phone. Please excuse my brevity. >> >> >> >> -- >> Sent from my phone. Please excuse my brevity. >> -- Sent from my phone. Please excuse my brevity. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
