资源｜(无深度学习的)机器学习概要(2017课程讲义草稿PPT)

原标题：资源｜(无深度学习的)机器学习概要(2017课程讲义草稿PPT)

Individual Chapters:

1. Front Matter

   http://ciml.info/dl/v0_99/ciml-v0_99-ch00.pdf

2. Decision Trees

   http://ciml.info/dl/v0_99/ciml-v0_99-ch01.pdf

3. Limits of Learning

   http://ciml.info/dl/v0_99/ciml-v0_99-ch02.pdf

4. Geometry and Nearest Neighbors

   http://ciml.info/dl/v0_99/ciml-v0_99-ch03.pdf

5. The Perceptron

   http://ciml.info/dl/v0_99/ciml-v0_99-ch04.pdf

6. Practical Issues

   http://ciml.info/dl/v0_99/ciml-v0_99-ch05.pdf

7. Beyond Binary Classification

   http://ciml.info/dl/v0_99/ciml-v0_99-ch06.pdf

8. Linear Models

   http://ciml.info/dl/v0_99/ciml-v0_99-ch07.pdf

9. Bias and Fairness

   http://ciml.info/dl/v0_99/ciml-v0_99-ch08.pdf

10. Probabilistic Modeling

    http://ciml.info/dl/v0_99/ciml-v0_99-ch09.pdf

11. Neural Networks

    http://ciml.info/dl/v0_99/ciml-v0_99-ch10.pdf

12. Kernel Methods

    http://ciml.info/dl/v0_99/ciml-v0_99-ch11.pdf

13. Learning Theory

    http://ciml.info/dl/v0_99/ciml-v0_99-ch12.pdf

14. Ensemble Methods

    http://ciml.info/dl/v0_99/ciml-v0_99-ch13.pdf

15. Efficient Learning

    http://ciml.info/dl/v0_99/ciml-v0_99-ch14.pdf

16. Unsupervised Learning

    http://ciml.info/dl/v0_99/ciml-v0_99-ch15.pdf

17. Expectation Maximization

    http://ciml.info/dl/v0_99/ciml-v0_99-ch16.pdf

18. Structured Prediction

    http://ciml.info/dl/v0_99/ciml-v0_99-ch17.pdf

19. Imitation Learning

    http://ciml.info/dl/v0_99/ciml-v0_99-ch18.pdf

20. Back Matter

    http://ciml.info/dl/v0_99/ciml-v0_99-ch19.pdf返回搜狐，查看更多

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