> My first teaching material will be an intro to python. I'll use these slides > > http://perso.telecom-paristech.fr/~gramfort/intro-python/ > [code] > https://github.com/agramfort/scientific-python-intro-45mins > > the topics I'll cover are SVMs, trees, RF, QDA/LDA, NMF/PCA/ICA, > K-means, GMM, bagging/boosting, logistic regression, ridge (maybe > others) > > all material is not ready yet but maybe we can share some.
Thanks for the pointer! I may take some inspiration from your slides :-) I plan to work on this during this week. I keep you posted as soon as I have something concrete. Best, Gilles ------------------------------------------------------------------------------ Got visibility? Most devs has no idea what their production app looks like. Find out how fast your code is with AppDynamics Lite. http://ad.doubleclick.net/clk;262219671;13503038;y? http://info.appdynamics.com/FreeJavaPerformanceDownload.html _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
