Transcription of Machine Learning and Data Mining Lecture Notes
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Machine Learning and Data MiningLecture NotesCSC 411/D11 Computer Science DepartmentUniversity of TorontoVersion: February 6, 2012 Copyrightc 2010 Aaron Hertzmann and David FleetCSC 411 / CSC D11 CONTENTSC ontentsConventions and Notationiv1 Introduction to Machine of Machine Learning .. simple problem ..22 Linear 1D case .. inputs .. outputs ..83 Nonlinear function regression .. and Regularization .. Neural Networks .. Neighbors .. a quadratic .. 185 Basic Probability logic .. definitions and rules .. random variables .. and Multinomial distributions .. expectation .. 266 Probability Density Functions (PDFs) expectation, mean, and variance.
CSC 411 / CSC D11 Acknowledgements Conventions and Notation Scalars are written with lower-case italics, e.g.,x. Column-vectors are written in bold, lower-case: x, and matrices are written in bold uppercase: B. The set of real numbers is represented by R; N-dimensional Euclidean space is writtenRN. Aside:
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