Machine Learning Course

Machine Learning Course

Yaser Abu-Mostafa via YouTube Direct link

Lecture 09 - The Linear Model II

9 of 18

9 of 18

Lecture 09 - The Linear Model II

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Classroom Contents

Machine Learning Course

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  1. 1 Lecture 01 - The Learning Problem
  2. 2 Lecture 02 - Is Learning Feasible?
  3. 3 Lecture 03 -The Linear Model I
  4. 4 Lecture 04 - Error and Noise
  5. 5 Lecture 05 - Training Versus Testing
  6. 6 Lecture 06 - Theory of Generalization
  7. 7 Lecture 07 - The VC Dimension
  8. 8 Lecture 08 - Bias-Variance Tradeoff
  9. 9 Lecture 09 - The Linear Model II
  10. 10 Lecture 10 - Neural Networks
  11. 11 Lecture 11 - Overfitting
  12. 12 Lecture 12 - Regularization
  13. 13 Lecture 13 - Validation
  14. 14 Lecture 14 - Support Vector Machines
  15. 15 Lecture 15 - Kernel Methods
  16. 16 Lecture 16 - Radial Basis Functions
  17. 17 Lecture 17 - Three Learning Principles
  18. 18 Lecture 18 - Epilogue

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