Good news on the facilitating the hangout. Also, yes, a downpour (aka asynchronous stochastic gradient descent is what I meant) for deep learning.
Sent from my iPhone On Oct 6, 2013, at 12:58, Suneel Marthi <[email protected]> wrote: > Grant would be available the week of Oct 14 for a hangout (tentatively). > We could go ahead and schedule one next week if there's (and seems very much > like it) enough response. I can go ahead and facilitate one. > > I will be 100% focused on Mahout from next week once I start at my new job > from Monday. > > Regarding building something for Deep Learning, Yexi's patch for MLP (see > M-1265) may be a good place to refactor/start thinking about the foundations. > I guess Ted is alluring to build something like what's been described in the > Google paper (see > http://www.cs.toronto.edu/~ranzato/publications/DistBeliefNIPS2012_withAppendix.pdf). > Correct? > > > Suneel > > > > > ________________________________ > From: Ted Dunning <[email protected]> > To: "[email protected]" <[email protected]> > Cc: "[email protected]" <[email protected]> > Sent: Sunday, October 6, 2013 2:10 AM > Subject: Re: Mahout's future > > > Saikat > > These are all good suggestions. I would have a hard time suggesting a > prioritization of them. > > Does anybody remember what grant said about having another hangout? > > Sent from my iPhone > > On Oct 6, 2013, at 7:15, Saikat Kanjilal <[email protected]> wrote: > >> I wanted to mention a few other things:1)It might be useful to take and >> embed a few already productionalized use cases into the integration tests in >> mahout, this will help additional users get on board faster2) Deep learning >> is really interesting, however I'd like to help research some common use >> cases first before tying this into mahout3) It'd be good to put some thought >> into documenting when you would choose what type of algorithm given a >> production machine learning recommendation system to build, this would give >> more visibility for users into choosing the right mixture of algorithms to >> build a production ready recommender, often what I've found is that a bulk >> of the time in building productionalized recommenders is spent cleaning and >> filtering noisy data4) I'd like to also explore how to tie in machine >> learning algorithms into real time systems built using twitter storm >> (http://storm-project.net/), it seems that industry more and more is wanting > to do real time analytics on the fly, I'm curious what type of algorithms > we'd need for this and back propagate these into mahout >> >> It'd be good to meet like minded devs together locally (Seattle) or over >> gtalk/conference to talk through possibilities. >> Regards >>> From: [email protected] >>> Date: Sat, 5 Oct 2013 18:13:40 -0700 >>> Subject: Re: Mahout's future >>> To: [email protected] >>> >>> On Sat, Oct 5, 2013 at 5:08 PM, Saikat Kanjilal <[email protected]> wrote: >>> >>>> Does it make sense to have a quick meeting of interested developers over >>>> google chat/conference rather than email to discuss and assign folks to >>>> specifics? >>>> >>>> Thoughts? >>> >>> Great idea. >>> >>> I think that Grant may have been organizing a hangout. >>
