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Machine Learning and Data Mining Lecture Notes

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Machine Learning and Data MiningLecture NotesCSC 411/D11Computer Science DepartmentUniversity of TorontoVersion: February 6, 2012Copyrightc 2010 Aaron Hertzmann and David FleetCSC 411 / CSC D11CONTENTSContentsConventions and Notationiv1Introduction to Machine of Machine Learning . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . simple problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..22Linear 1D case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . inputs.

Lecture Notes CSC 411/D11 Computer Science Department University of Toronto Version: February 6, 2012 ... 5 Basic Probability Theory 21 ... when fitting a curve to noisy data, it is common to measure the q uality of the fit in terms of

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