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人工智能+机器人+大数据+算法（140本+）
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深度学习
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伯克利大学机器学习(Practical Machine Learning)（14本）
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10[Oct 29]Reinforcement learning [Peter Bodik].pdf
11[Nov 5]Bootstrap&cross-validation&ROC plots [Michael Jordan].pdf
12[Nov 12]Time series&sequential hypothesis testing&anomaly detection[Alex Shyr].pdf
13[Nov 19]Bayesian nonparametric methods (Dirichlet processes) [Kurt Miller].pdf
14[Dec 3]Optimization methods for learning [John Duchi] .pdf
1[Aug 27]Tutorial [Ariel Kleiner].pdf
2[Sep 3]Regression [Fabian Wauthier].pdf
3[Sep 10]Classification [Michael Jordan].pdf
4[Sep 17] Clustering [Sriram Sankararaman].pdf
5[Sep 24]Dimensionality reduction [Percy Liang].pdf
6[Oct 1]Feature selection [Alex Bouchard].pdf
7[Oct 8]Hidden Markov models& graphical models [Alex Simma].pdf
8[Oct 15]Collaborative Filtering [Lester Mackey].pdf
9[Oct 22]Active learning, experimental design [Daniel Ting].pdf
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