2011/11/21 Jacob VanderPlas <[email protected]>: > I would recommend these: I'm currently taking the Machine Learning > course, taught by Andrew Ng, which will be offered again in January. > It's been a great intro to things like logistic regression, neural > networks, SVM, etc. for someone like me with no formal ML training. > I've found 2-3 hours/week sufficient to complete the lectures, quizzes > and programming assignments, though someone less familiar with Octave > may spend more time on the assignments.
I'm taking the ML course too and I can assure you that some NumPy knowledge is enough to get into Octave pretty quickly. I also finally understand parts of the NumPy interface design that puzzled me before ;) I understood from my newspaper (!) that Stanford would be offering an online course in probabilistic graphical models as well, somewhere beginning of 2012. Does anyone know if Stanford has an overview website of these courses? My google-fu failed me so far. -- Lars Buitinck Scientific programmer, ILPS University of Amsterdam ------------------------------------------------------------------------------ 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
