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Machine Learning and Data Mining Lecture Notes

book
Language:
Author: Aaron Hertzmann and David Fleet
Url: http://www.dgp.toronto.edu/~hertzman/411notes.pdf
Format: Pdf
Year: 2012
Category: Machine Learning
Pages: 134
Clicks: 772

Description
Contents: Introduction to Machine Learning; Linear Regression; Nonlinear Regression; Quadratics; Basic Probability Theory; Probability Density Functions; Estimation; Classification; Gradient Descent; Cross Validation; Bayesian Methods; Monte Carlo Methods; Principal Components Analysis; Lagrange Multipliers; Clustering; Hidden Markov Models; Support Vector Machines; AdaBoost.

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