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简介
Foundations of Data Science 豆 0.0分
资源最后更新于 2020-09-05 22:03:23
作者：Avrim Blum
出版社：Cambridge University Press
出版日期：2020-01
ISBN：9781108485067
文件格式： pdf
标签： 机器学习 数据科学 统计学 数学 Data_Science Data_Mining Machine_Learning Clustering
简介· · · · · ·
Description Contents Resources Courses About the Authors
This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value deco...
目录
1. Introduction
2. High-dimensional space
3. Best-fit subspaces and Singular Value Decomposition (SVD)
4. Random walks and Markov chains
5. Machine learning
6. Algorithms for massive data problems: streaming, sketching, and sampling
7. Clustering
8. Random graphs
9. Topic models, non-negative matrix factorization, hidden Markov models, and graphical models
10. Other topics
11. Wavelets
12. Appendix.
2. High-dimensional space
3. Best-fit subspaces and Singular Value Decomposition (SVD)
4. Random walks and Markov chains
5. Machine learning
6. Algorithms for massive data problems: streaming, sketching, and sampling
7. Clustering
8. Random graphs
9. Topic models, non-negative matrix factorization, hidden Markov models, and graphical models
10. Other topics
11. Wavelets
12. Appendix.
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