Filename
Size
Date
课件\cs229-notes1 Supervised Learning
 Discriminative Algorithms .pdf
 235162
 2007-12-11
课件\cs229-notes10 Principal Components Analysis .pdf
 77205
 2007-12-11
课件\cs229-notes11 Independent Components Analysis .pdf
 75963
 2007-12-11
课件\cs229-notes12 Reinforcement Learning and Control .pdf
 75738
 2007-12-11
课件\cs229-notes2 Generative Algorithms .pdf
 878764
 2007-12-11
课件\cs229-notes3 Support Vector Machines .pdf
 179785
 2007-12-11
课件\cs229-notes4 Learning Theory .pdf
 111349
 2007-12-11
课件\cs229-notes5 Regularization and Model Selection .pdf
 88707
 2007-12-11
课件\cs229-notes6 Online Learning and the Perceptron Algorithm. (optional reading).pdf
 52070
 2007-12-11
课件\cs229-notes7a Unsupervised Learning
 k-means clustering. .pdf
 271020
 2007-12-11
课件\cs229-notes7b Mixture of Gaussians .pdf
 55179
 2007-12-11
课件\cs229-notes8 The EM Algorithm .pdf
 83133
 2007-12-11
课件\cs229-notes9 Factor Analysis .pdf
 83106
 2007-12-11
课件\cs229-prob Probability Theory Review .pdf
 151039
 2007-12-11
课件\ML-advice.pdf
 320993
 2007-12-11
课件\Section notes 1-Linear Algebra Review and Reference .pdf
 168545
 2007-12-11
课件\Section notes 4-Convex Optimization Overview
 Part I.pdf
 152436
 2007-12-11
课件\Section notes 5-Convex Optimization Overview
 Part II .pdf
 201528
 2007-12-11
课件\Section notes 6-Hidden Markov Models .pdf
 202549
 2007-12-11
课件\Section notes 7-The Multivariate Gaussian Distribution.pdf
 343164
 2014-05-15
课件\Section notes 8-More on Gaussian Distribution.pdf
 119533
 2014-05-15
课件\Section notes 9-Gaussian Processes.pdf
 163887
 2014-05-15
课件