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【机器学习】白板手推系列笔记

本人学习了此系列课程,讲解的很好,提高了对于模型的理解。特此做了学习笔记。

目前已更新到系列35,更多可到up主的主页观看。主页链接

B站播放链接1-23章

目录如下:

  1. 绪论
  2. 数学基础
  3. 线性回归
  4. 线性分类
  5. 降维
  6. 支持向量机
  7. 核方法
  8. 指数族分布
  9. 概率图模型
  10. EM
  11. 高斯混合模型
  12. 变分推断
  13. MCMC
  14. HMM
  15. 线性动态系统
  16. 粒子滤波
  17. 条件随机场
  18. 高斯网络
  19. 贝叶斯线性回归
  20. 高斯过程回归
  21. 受限玻尔兹曼机
  22. 谱聚类
  23. 前馈神经网络

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