Guru CHAS.owens will reply. On 16 Mar 2017 7:08 am, "community tech" <commun...@dnsbed.com> wrote:
> Today python has so many excellent libraries for ML, the ones we are > checking with, > > 1. sklearn: http://scikit-learn.org/stable/ > 2. Keras 2: https://blog.keras.io/introducing-keras-2.html?t=1 > 3. Theano: http://deeplearning.net/software/theano/ > 4. Pytorch: https://github.com/pytorch/pytorch > > I do wish perl community has got involved ML world too. :) > > > 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/ >>> >>> >>> >> >
