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Catching up with machine learning class from Stanford

posted Nov 6, 2011 11:23 PM by Asen Kovachev   [ updated Nov 7, 2011 12:42 AM ]
Several weeks ago I signed up at ml-class.org. Machine learning is of big interest to me and I highly recommend taking this course. I wish I knew earlier how fun and educational it is.

I finally managed to get into it this weekend. I am slightly behind the due dates, which results in 20% penalty on your score. Overall it is a well organized and presented class.

Hopefully one day people can get a respectable degree from the comfort of their home using similar technology.

TIP: Instead of entering your email and password every time, just modify the basicPrompt function in submit.m:

function [login password] = basicPrompt()
  login = 'your@email.com'
  password = '<your-web-submission-password>';
end

I'm currently trying to figure out a better way to calculate the logistic regression cost function (vectorization among other things)

Logistic regression cost function

I haven't used Octave before but I am getting the hang of it. It seems easy to prototype mathematical algorithms. You can easily do in a few lines of code what could take 30 or more to do in C++/Java, etc.

Comments

Asen Kovachev - Nov 7, 2011 10:20 PM

This actually wasn't really that hard...
Once you realize that h can easily be vectorized like this:
h = sigmoid(X * theta);
the rest is trivial.