伯克利大学机器学习讲义
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2018-03-07
21:19:12
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伯克利大学机器学习(Practical Machine Learning).zip （14个子文件） 
伯克利大学机器学习(Practical Machine Learning) 
2[Sep 3]Regression [Fabian Wauthier].pdf 1.95MB 8[Oct 15]Collaborative Filtering [Lester Mackey].pdf 3MB 4[Sep 17] Clustering [Sriram Sankararaman].pdf 27.04MB 5[Sep 24]Dimensionality reduction [Percy Liang].pdf 5.8MB 10[Oct 29]Reinforcement learning [Peter Bodik].pdf 594KB 1[Aug 27]Tutorial [Ariel Kleiner].pdf 154KB 13[Nov 19]Bayesian nonparametric methods (Dirichlet processes) [Kurt Miller].pdf 3.25MB 12[Nov 12]Time series&sequential hypothesis testing&anomaly detection[Alex Shyr].pdf 1.13MB 7[Oct 8]Hidden Markov models& graphical models [Alex Simma].pdf 3.73MB 3[Sep 10]Classification [Michael Jordan].pdf 2.02MB 6[Oct 1]Feature selection [Alex Bouchard].pdf 4.04MB 9[Oct 22]Active learning, experimental design [Daniel Ting].pdf 577KB 14[Dec 3]Optimization methods for learning [John Duchi] .pdf 1.25MB 11[Nov 5]Bootstrap&cross-validation&ROC plots [Michael Jordan].pdf 485KB资源评论
