Resend. I keep using the wrong sender. sorry guys.

On Thu, Mar 27, 2014 at 1:10 PM, Julie Pitt <[email protected]> wrote:

> Thanks for the pointers, Matt! I watched your tutorial video and follower
> your steps myself. One weird thing was that when I did the swarm over the
> sine data set, no model_params.py was generated. I checked out the exact
> example code you posted on your personal GitHub, so we will see if that
> happens with your exact code. Also of note is that the description.py did
> not seem to work with Cerebro.
>
> Thank you for pointing to the skeleton doc about model params. That is a
> good start, and in line with what I was looking for. I wasn't able to find
> that on my own, so hopefully the reorg will help.
>
> The other doc I feel is missing is one that says "here are the major
> pieces of py code and how they fit together." Not necessarily of interest
> to the casual user, but could be immensely helpful to prospective
> contributors.
>
>
> On Wednesday, March 26, 2014, Matthew Taylor <[email protected]> wrote:
>
>> Most of the Numenta team is off at an AWS event today, so I'll try to
>> help as I can. We are lacking documentation on model parameters, which
>> is bad because they are quite important.
>>
>> The swarm process seems magical, but all it does is run a PSO [1]
>> algorithm. Hopefully, you've seen Ron's video on Swarming [2]. So it
>> just takes your input data and creates a bunch of models over and
>> over, throwing out the ones that don't perform well and replacing them
>> with new models with different params. Eventually finding the set of
>> parameters that perform best on your data. More on our wiki [3] [4].
>>
>> We do have some docs on model params on our wiki as well [5], but it
>> needs to be better exposed and cleaned up. (I'm working on wiki reorg
>> right now [6]).
>>
>> [1] en.wikipedia.org/wiki/Particle_swarm_optimization
>> [2] Swarming in NuPIC <http://www.youtube.com/watch?v=xYPKjKQ4YZ0>
>>
>> [3] https://github.com/numenta/nupic/wiki/Running-Swarms
>> [4] https://github.com/numenta/nupic/wiki/Swarming-Algorithm
>> [5] https://github.com/numenta/nupic/wiki/Models#version-1
>> [6] https://github.com/numenta/nupic/issues/747
>> ---------
>> Matt Taylor
>> OS Community Flag-Bearer
>> Numenta
>>
>>
>> On Wed, Mar 26, 2014 at 2:57 PM, Julie Pitt <[email protected]> wrote:
>> > Yes. I read On Intelligence and the Whitepaper. Now I actually want to
>> take
>> > my understanding to the next level. What I've worked out so far is that
>> > there are a few options, for running a model:
>> >
>> > 1. Use the OPF. You're essentially a (python) client to the OPF which in
>> > turn is a client to the CLA.
>> > 2. Use python (or other) language bindings directly to interface with
>> the
>> > CLA
>> >
>> > I'm currently looking at #1. There are several ways I've seen to get
>> into
>> > using the OPF:
>> >
>> > a. Given a dataset, swarm it to create a model. Somehow swarming
>> *magically*
>> > figures out what translation and encoding is needed, whether you need
>> to use
>> > the SP or TP or both, as well as what parameters to send them.
>> > b. create a model by hand
>> >
>> > I can do the swarm but would really like to understand the various
>> > parameters and config in description.py as well as other elements I
>> might be
>> > missing. Right now I'm blindly fumbling around until it starts to make
>> > sense. I'd love to do better than that if others have advice.
>> >
>> >
>> >
>> > On Wed, Mar 26, 2014 at 2:46 PM, Freeman 77 <[email protected]>
>> wrote:
>> >>
>> >> Did you checked the available documents in the wiki about the CLA and
>> the
>> >> book On Intelligence? I think this must be the first step you need to
>> make,
>> >> at least that's what I'm doing.
>> >>
>> >> Greetings.
>> >>
>> >> El 26-03-2014, a las 17:50, "Julie Pitt" <[email protected]>
>> escribió:
>> >>
>> >> Sorry if this post appears twice. I used the wrong "from" address the
>> >> first time.
>> >>
>> >>> I'm just getting into NuPIC. I have built it on my machine and I'm
>> >>> running Cerebro. I've tried loading up a couple of models (so far only
>> >>> hotgym works) and run using Cerebro. I would like to start tinkering
>> by
>> >>> tweaking or creating my own models. Aside from just reading
>> examples/code
>> >>> and making inferences, is there a good place to go to get a
>> description of
>> >>> the config and what the params are?
>> >>>
>> >>> I have stumbled across ExpGenerator.py which seems to generate
>> >>> experiments from some input file, but so far I haven't been able to
>> >>> determine what should be in that input file.
>> >>>
>> >>> Thanks!
>> >>
>> >>
>> >>
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