Hi community tech, You mentioned MXNet has not wrapper in Perl, but I see it in CPAN and am trying to build it right now. Is it just not working for you?
Thanks, Jovan On Mon, Feb 13, 2017 at 3:43 AM, community tech <commun...@dnsbed.com> wrote: > I tried to search "random forest" on CPAN but got no good luck. > https://en.wikipedia.org/wiki/Random_forest > > For framework we currently use MXNet, which has API for Python/C++/R, but > no Perl. > http://mxnet.io/ > > Thanks. > > 2017-02-12 2:54 GMT+08:00 James Alton <jamesalton...@gmail.com>: > >> If you want to learn about machine learning and the first thing you think >> is: "What Perl libraries are there for this?", you might be going about it >> all wrong. >> >> *The best machine learning libraries are all written for Python*. This >> isn't a "religious" argument, it's just the way it is. I always think: >> Right tool for the job. In this case, it's Python. >> >> TensorFlow - C++ front end, Python front end >> >> Torch - Lua, Python wrapper >> Theano - Python >> Caffe - C++, Python wrapper >> >> (I put TensorFlow by itself because it's probably the one you want >> anyway. Probably the best library out there right now for the vast majority >> of ML.) >> >> Another thing that follows this same theme with machine learning is: AMD >> or Nvidia? Normally I'd say use what you've got, but in this case, it would >> be the wrong decision. You need to go Nvidia otherwise you'll be a "second >> class citizen" in the machine learning world. (OpenCL support often seems >> like an after thought, CUDA is first.) And it has to be a fairly recent >> Nvidia, otherwise stuff won't even load. (A year or two old is ok, point is >> - research the limitation here carefully.) >> >> Your best bet from a Perl standpoint is: Do the heavy lifting in Python, >> pass your results to Perl using JSON or something, and be done with it. >> >> *And btw, if you want the fast track on ML, try Keras.* (It's also for >> Python.) It's an even higher level than Tensorflow and it's almost "fun" to >> program ML in. (Hides a lot of the ugly bits. And with ML, there really are >> a lot of ugly bits. The interface in Keras is like: train this model with >> these layers, give me results with that trained model.) >> >> YMMV and I hope my experiences above saves you lots of potential wasted >> time and money, >> James >> >> >> >> >> On Sat, Feb 11, 2017 at 11:28 AM, chace <chacewe...@gmail.com> wrote: >> >>> Hi there. >>> >>> I don't know much about machine learning myself, much less doing it in >>> Perl. But I have dabbled and have been meaning to do a bit more with it in >>> the Perl-based scientific computing framework PDL. >>> >>> A quick Google search revealed a short blurb on PerlMonks about ML >>> analysis of stock data using PDL. The very last comment also points to a >>> couple of AI modules on CPAN. Links here: >>> >>> http://www.perlmonks.org/?node_id=638391 >>> >>> http://search.cpan.org/search?mode=module&query=AI%3A%3ACategorizer >>> >>> http://search.cpan.org/search?mode=module&query=AI%3A%3ADecisionTree >>> >>> >>> Perl-land is a bit less frameworky and more library-ish than >>> Python-land. There's plenty of algorithms on the CPAN, so I suggest >>> figuring out what you need and importing as you figure that out. >>> >>> >>> On 02/07/2017 05:47 PM, community tech wrote: >>> >>>> Is there a popular perl library/framework for machine learning? >>>> >>>> Thanks. >>>> >>> >>> -- >>> To unsubscribe, e-mail: beginners-unsubscr...@perl.org >>> For additional commands, e-mail: beginners-h...@perl.org >>> http://learn.perl.org/ >>> >>> >>> >> >
