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	* Weeks 1-2: A. {{:ml1-intro.pdf\|Machine Learning (basic concepts)}}; B. {{:ml2-math.pdf\|Math foundation}}: probabilities and statistics, Bayes theorem, Entropy, mutual information, decision tree, optimization, matrix factorization (Weekly Reading: [[http://www.cse.yorku.ca/course_archive/2011-12/W/6328/Duda_AppMath.pdf\|W2]]) (A useful online manual on [[http://www.ee.ic.ac.uk/hp/staff/dmb/matrix/calculus.html\|Matrix Calculus]])		* Weeks 1-2: A. {{:ml1-intro.pdf\|Machine Learning (basic concepts)}}; B. {{:ml2-math.pdf\|Math foundation}}: probabilities and statistics, Bayes theorem, Entropy, mutual information, decision tree, optimization, matrix factorization (Weekly Reading: [[http://www.cse.yorku.ca/course_archive/2011-12/W/6328/Duda_AppMath.pdf\|W2]]) (A useful online manual on [[http://www.ee.ic.ac.uk/hp/staff/dmb/matrix/calculus.html\|Matrix Calculus]])