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ML Stanford Online Class 2011

7.05MB. 0 audio & 130 images. Updated 2012-08-25.
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Description

Collaborative flashcards for the Machine Learning online Stanford class of fall 2011 Up-to-date, miss only week10 (to come) and week6 part1 (learning curves, soon) For more informations, see http://github.com/lrq3000/online-stanford-flashcards-2011

Sample (from 193 notes)

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Front If the angle between the two vectors v and u is greater than 90°, what does p (the projection of u onto v or v onto u) looks like?
Back p will be negative:
Tags support-vector-machine week7
Front Give the optimization algorithm (gradient descent) for Content Based recommender system:[...]
Back Content Based Recommender System - Gradient Descent Additional informations: Note: this is essentially a variation linear regression.
Tags content-based recommender-systems week9
Front Numerical gradient checking is simply put [...]
Back Numerical gradient checking is simply put an approximation of the gradient by taking 2 points and calculating the line's coefficient, and then compare to the real derivation found by back propagation.Alternative answer: a verification if one's implementation of back propagation is bug-free
Tags neural-network week5

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