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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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