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.
