5. 機器學習基石-Why can Machine Learn?
Why can Machine Learn? Why can Machine Learn? 1. Preview of Last Chapter 2. VC Bound (Vapnik-Chervonenkis Bound) - A Upper Bound Limitation of Hoeffding Inequity 1) Introduction 2) Growth function 3)
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- 1. 6. 機器學習基石-Why can Machine Learn? - Noice and Error
- 2. 機器學習基石---Why Can Machines Learn(Part1)
- 3. 4. 機器學習基石-When can Machine Learn? - Feasible of Learning
- 4. 7. 機器學習基石-How can Machine Learn? - Linear Regression
- 5. 9. 機器學習基石-How can Machine Learn? - Linear Model for Classification
- 6. 8. 機器學習基石-How can Machine Learn? - Logistic Regression
- 7. 12. 機器學習基石-How can Machine Learn Better? - Regularization
- 8. 10. 機器學習基石-How can Machine Learn? - Nonlinear Transformation
- 9. 1. 機器學習基石-When can Machine Learn? - The Learning Problem
- 10. 13. 機器學習基石-How can Machine Learn Better? - Validation
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相關文章
- 1. 6. 機器學習基石-Why can Machine Learn? - Noice and Error
- 2. 機器學習基石---Why Can Machines Learn(Part1)
- 3. 4. 機器學習基石-When can Machine Learn? - Feasible of Learning
- 4. 7. 機器學習基石-How can Machine Learn? - Linear Regression
- 5. 9. 機器學習基石-How can Machine Learn? - Linear Model for Classification
- 6. 8. 機器學習基石-How can Machine Learn? - Logistic Regression
- 7. 12. 機器學習基石-How can Machine Learn Better? - Regularization
- 8. 10. 機器學習基石-How can Machine Learn? - Nonlinear Transformation
- 9. 1. 機器學習基石-When can Machine Learn? - The Learning Problem
- 10. 13. 機器學習基石-How can Machine Learn Better? - Validation