A lot of those topics are very interesting, and they pick off very well from where the Stanford ML course finishes. I'd love to see the slides if you end up uploading them.
If (very selfishly) I may suggest an extra topic - could you cover the different kinds of losses & norms, and discuss which is appropriate and when? I haven't found a good basic overview of the topic yet. On Mon, Oct 1, 2012 at 12:03 PM, Alexandre Gramfort <[email protected]> wrote: > Hi Gilles, > > great initiative ! Let me know you're not the only one. I'll be teaching > machine learning at Telecom ParisTech using Python + scikit-learn > starting next month. > > 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. > > Best, > Alex > > > > On Mon, Oct 1, 2012 at 10:19 AM, Gilles Louppe <[email protected]> wrote: >> Hi Team, >> >> Given the increasing maturity of the project, we have decided (or, >> more precisely, I convinced my advisor :-)) to use Scikit-Learn in the >> machine learning course given at my university. Our objective is to >> make our students use Scikit-Learn for three assignments. We were >> previously using Matlab with some home-made modules. >> >> Has any of you already tried that? >> >> As the teaching assistant for this course, I plan to give my students >> a tutorial to Python+Scikit-Learn. I was wondering if besides the >> tutorials in our user guide, any of you had made (or knew) teaching >> materials targeted for students? I am aware of Olivier and Jake >> tutorials. >> >> Also, if you have anything that comes to mind regarding elements I >> should include in such a tutorial, please feel free to suggest! >> >> 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 > > ------------------------------------------------------------------------------ > 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 ------------------------------------------------------------------------------ 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
