Awesome!
Thank you David -- backproppy looks nice + simple -- exactly what i
needed to experiment/learn with.
On Mon, Nov 28, 2011 at 1:22 PM, David Warde-Farley
wrote:
> On Mon, Nov 28, 2011 at 06:42:03PM +0100, Andreas Müller wrote:
>
>> I think it should be pretty straightforward, replacing
On Mon, Nov 28, 2011 at 06:42:03PM +0100, Andreas Müller wrote:
> I think it should be pretty straightforward, replacing cp.prod()
> with np.dot() and similar.
> The implementation has lots of features, so I am not sure
> how easy it is to understand. You can definitely have a look.
>
> If you al
On 11/28/2011 05:23 PM, Timmy Wilson wrote:
> Thanks Guys!
>
>> This is neither a Deep Belief Network nor a stack
>> of RBMs, just a regular feed forward neural network
>> that has a particularly well chosen set of initial weights.
> Agreed. This is what i'm imagining.
>
> Assuming good results, i
Thanks Guys!
> This is neither a Deep Belief Network nor a stack
> of RBMs, just a regular feed forward neural network
> that has a particularly well chosen set of initial weights.
Agreed. This is what i'm imagining.
Assuming good results, i'm sure i'll want to move to a GPU implementation.
In
Setting up the coverage reports was actually easy:
Here is the progress plot (along with the pep8 progress plot) on the
project over time:
https://jenkins.shiningpanda.com/scikit-learn/job/scikit-learn-py27-numpy1.5.1-scipy-0.10.0/
Here is the HTML report of the last successful build:
htt
2011/11/28 Vlad Niculae :
> Hi Olivier,
>
> This is very cool. Could we plot average test coverage as well, similar to
> pep8?
> Is there a way to subscribe to the build reports, like with the
> buildbot? I signed up but still couldn't find one.
Ideally I would like to send the notifications to t
2011/11/28 Andreas Müller :
> On 11/28/2011 03:11 AM, Olivier Grisel wrote:
>> I could not resist:
>>
>> I have configured the pep8 report:
>>
>>
>> https://jenkins.shiningpanda.com/scikit-learn/job/scikit-learn-py27-numpy1.5.1-scipy-0.10.0/ws/pep8.txt
>>
> This is pretty cool :) Thanks!
>> Th
I'd like to add something to David's addition to Olivier's answer:
There are also some alternatives to Theano ;)
Theano is great, in particular with all the docs and tutorials, but I
think it feels
like learning a new language.
My lab has a CUDA library called CUV that aims to be a numpy replace
On 11/28/2011 03:11 AM, Olivier Grisel wrote:
> I could not resist:
>
> I have configured the pep8 report:
>
>
> https://jenkins.shiningpanda.com/scikit-learn/job/scikit-learn-py27-numpy1.5.1-scipy-0.10.0/ws/pep8.txt
>
This is pretty cool :) Thanks!
> There is currently 511 errors. Please feel
Hi Olivier,
This is very cool. Could we plot average test coverage as well, similar to pep8?
Is there a way to subscribe to the build reports, like with the
buildbot? I signed up but still couldn't find one.
Vlad
On Mon, Nov 28, 2011 at 4:26 AM, Olivier Grisel
wrote:
> 2011/11/28 Olivier Grisel
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