Tuesday, September 25, 2012
Back to school!
Couldn't let September end without learning something new, so I enrolled in a Coursera course that I had postponed for a while -- Probabilistic Graphical Models, with Daphne Koller.
Even though this was already running, albeit in a previous incarnation, by the time I was attending Andrew Ng's Machine Learning course, I had put it off because of the limited spare time I have for such courses. This was not a bad decision, since I was able to focus more on the ML course, and now my background is more solid for PGM.
I've only seen a couple of the videos, but I like Prof. Koller's way of explaining things. The "Distributions" introductory video in particular struck me as an extremely clear way of describing joint distributions and operations on them.
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hey! This is a wrong place to post this. I found your post on Stackoverflow regarding scipy optimize for cost function in Linear Regression. I was hoping you could help me out in implementing that for Neural Networks. Even I'm taking Machine Learning this time on Coursera which is very fun.
ReplyDeleteHi! I'm not sure what you are really asking :-)
ReplyDeleteI gather you want to implement neural networks, but I don't understand what the scipy optimize function has got to do with your question.