[Haskell-cafe] AI - machine learning

[C Gosch]

Hi all,

I have implemented max-sum/sum-product in c++ before and a while ago,
did the same in Haskell.
I don't think my implementation is as idiomatic Haskellish as I would
like, and I have so far not
published it and also not looked at it for a little while (since I
have some more projects :) ).
However, if you are interested, I will publish it (maybe on github?),
and I think we should join forces.
I am also very interested in machine learning techniques, but I can
unfortunately use neither those nor Haskell at
my day job at present.

Let me know what you think.

Best regards,
Christian


Message: 3
Date: Thu, 17 May 2012 15:36:08 +0400
From: Paul Graphov <graphov at gmail.com>
Subject: Re: [Haskell-cafe] AI - machine learning
To: miro <miroslav.karpis at gmail.com>
Cc: haskell-cafe at haskell.org
Message-ID:
       <CAKHAQn+yFGCdLPoKR0sEhvJobwPPykvqTYieqZeBbzhyVodizg at mail.gmail.com>
Content-Type: text/plain; charset=UTF-8

Hi Miro!

I have no useful information for you. Few weeks ago I also checked for
any AI (machine learning first of all) related packages exist and
found nothing satisfactory except for some quite small packages
implementing a single algorithm (like NN-back-propagation). So there
is a lot to do :)

If you are going to do something in this area please let me know, I'll
be glad to collaborate!

p.s. Now I'm taking Machine Learning course at Coursera.org and
looking forward to apply this knowledge with Haskell.

On Tue, May 15, 2012 at 3:02 AM, miro <miroslav.karpis at gmail.com> wrote:
> Hi All, recently I started to take a look at haskell, especially at AI. I
> can see some email addresses of interested people there but not so much of
> other activity behind. Does it exist some mailing group especially for AI?
>
> Basically I'm interested in trying some machine learning algorithms. Start
> with reinforcement learning and value-based), and go towards AGI (Artificial
> General Intelligence). Does anybody know about some already existing haskell
> approaches, or is there anybody working on this?
>
> Cheers,
> m.