You should definitely have a look at theano that will probably run much faster than pure numpy for this kind of models (esp. if you have access to a GPU with the CUDA runtime).
http://deeplearning.net/software/theano/ The deep learning tutorial [1] have a section on backpropagation [2] and also on RBMs and DBN. You should also have a look at the Efficient Backprop paper by Lecun et al. [5] [1] http://www.deeplearning.net/tutorial/ [2] http://www.deeplearning.net/tutorial/mlp.html#mlp [3] http://www.deeplearning.net/tutorial/rbm.html#rbm [4] http://www.deeplearning.net/tutorial/DBN.html#dbn [5] http://yann.lecun.com/exdb/publis/#lecun-98b Best, -- Olivier ------------------------------------------------------------------------------ All the data continuously generated in your IT infrastructure contains a definitive record of customers, application performance, security threats, fraudulent activity, and more. Splunk takes this data and makes sense of it. IT sense. And common sense. http://p.sf.net/sfu/splunk-novd2d _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
