- Notes of Lesson 5 and 6

  • classification • ai • prediction • course • lesson • linear regression • perceptron • maximum likelihood • six • laplacian smoothing • peter norvig • 5 • online • 6 • sebastian thrun • five • class • stanford • notes • smooth • machine learning • linear separator • occam's razor
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If the “mood” of the previous lessons was about Inference, I can only say that the current are about “smoothing”, “occam’s razor” and “perceptron”. 3 concepts that will remain with you even after having forgotten about all this (check it out below :-P).

Enjoy the notes and, again, do Lesson 5, than complete the Homework, than study Lesson 6.

UPDATE Sat 05 Nov 2011: I just finished putting down the notes of Lesson 6, and you can find the link above.

I must say that Lesson 6, if we exclude Expectation Maximisation, is way less “mathematical” than the other lessons. Prof. Thrun, at a certain point, seems like givings us just an “overview” of some of the Unsupervised Learning concepts. It really makes you mouth-watering!