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