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-机器学习公开课课件

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Stanford Machine Learning Open Courseware
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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
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