On Wed, Feb 05, 2014 at 03:02:24PM +0300, Issam wrote: > I have been working with scikit-learn for three pull requests - namely, > Multi-layer Perceptron (MLP), Sparse Auto-encoders, and Gaussian > Restricted Boltzmann Machines.
Yes, you have been doing good work here! > For the upcoming GSoC, I propose to ensure completing these three pull > requests. I also would develop Greedy layer-wise training algorithm for > deep learning, extending MLP to allow for more than one hidden layer, > where weights are initialized using Sparse Auto-encoders or RBM. > How will this suit for GSoC? The MLP is almost finished. I would hope that it would be finished before the GSoC. Actually, I was hoping that it could be finished before next release. For the rest, I'll let someone who knows neural nets better than me reply, as I don't know the state of the art, and I don't know what is feasible in deep learning without GPUs. Cheers, Gaël ------------------------------------------------------------------------------ Managing the Performance of Cloud-Based Applications Take advantage of what the Cloud has to offer - Avoid Common Pitfalls. Read the Whitepaper. http://pubads.g.doubleclick.net/gampad/clk?id=121051231&iu=/4140/ostg.clktrk _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
