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 <[email protected]> wrote: > 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 already have a working RBM implementation, it might >> be easier to code the back propagation step yourself. >> >> Maybe you should rather look at some backpropagation >> code and the paper the others suggested. >> Implementing backpropagation should be fairly straight-forward. > > http://github.com/dwf/backproppy contains some code with a working (albeit > quite slow) feed forward neural network implementation. It is extensible > enough that multiple layers should be easy to hack in. It uses in-place > operations to minimize the creation of temporary buffers; the example network > object I have in there has a grad method that can compute the gradients wqith > respect to an entire network (the layer objects are initialized to throw > their gradients in slices of a larger object), and so it can be used with > stochastic gradient descent or any other gradient-based optimizer. > > It should be straightforward to create another network object with the > desired autoencoder architecture and then just assign the weights from the > RBMs into the right places. > > David > > ------------------------------------------------------------------------------ > 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 > ------------------------------------------------------------------------------ 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
