文件名称：伯克利大学机器学习讲义
文件大小：39.45MB
文件格式：ZIP
更新时间：2021-03-27 15:05:52
machine learning
一共14个课程的大学讲义，包括聚类、回归、分类、降维、强化学习……
【文件预览】：
伯克利大学机器学习(Practical Machine Learning)
----2[Sep 3]Regression [F* 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)