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美国康奈尔大学数据分析教材，适合有一定统计学基础的同志学习。
Contents
1 Introduction 9
2 High-Dimensional Space 12
3 Best-Fit Subspaces and Singular Value Decomposition (SVD) 40
4 Random Walks and Markov Chains 76
5 Machine Learning 129
6 Algorithms for Massive Data Problems: Streaming, Sketching, and
Sampling 181
7 Clustering 208
8 Random Graphs 245
9 Topic Models, Nonnegative Matrix Factorization, Hidden Markov Models,
and Graphical Models 310
10 Other Topics 360
11 Wavelets 385
12 Appendix 406
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