FYI, in April a project called scikit-neuralnetwork came into
existence. It's a library wrapping Pylearn2 and providing a scikit-learn
compatible interface. https://github.com/aigamedev/scikit-neuralnetwork
As others have stated, there are already some nice Python neural network
libraries
2015, at 19:08, Boyuan Deng bryanhsud...@gmail.com wrote:
Hi Andreas:
when I think there is a closed form solution
Yes, I remember that in some paper they first give the analytical solution
to the optimization problem, and then prove that it's the same result that
iterative version
into that, too?
If you have other related ideas, feel free to include them as well.
Best,
Andy
On 03/22/2015 05:47 PM, Boyuan Deng wrote:
Hi all:
This is the link to my proposal for the Cross-validation and
Meta-estimators for Semi-supervised Learning topic:
https://docs.google.com/document
, too bad it’s not 3 months ago, I could have met you in Saarbruecken,
I was just next door!
Hope my comments can help strengthen your proposal,
Yours,
Vlad
On 24 Mar 2015, at 19:08, Boyuan Deng bryanhsud...@gmail.com wrote:
Hi Andreas:
when I think there is a closed form solution
Yes
Hi Vinayak:
scipy.stats implemented pearsonr() like that because it's a statistics
routine. It treats 0 in the input data as indeed value 0.
But in the context of recommender systems, unrated is different from
score 0 (though we usually use 0 to represent unrated when score must
be
Hi Vinayak:
I remember there is an off-the-shelf function in scipy.stats called
pearsonr. You don't have to implement it on your own.
Boyuan
On 03/22/2015 01:21 PM, Vinayak Mehta wrote:
Hello everyone!
I was recently working on a simple movie recommender system in which I
calculated the
to show your practical abilities to contribute to
the project so that core developers become familiar with your work. I
see you have started to do so at #4409; something that involves
testing and/or documentation would be ideal.
- Joel
On 19 March 2015 at 09:30, Boyuan Deng bryanhsud
