Friday, March 8, 2013

Basics of Machine Learning (Video)

This is a basic video course on machine learning (ML) that covers the basic theory, algorithms, and applications.
  • Lecture 1: The Learning Problem
  • Lecture 2: Is Learning Feasible?
  • Lecture 3: The Linear Model I
  • Lecture 4: Error and Noise
  • Lecture 5: Training versus Testing
  • Lecture 6: Theory of Generalization
  • Lecture 7: The VC Dimension
  • Lecture 8: Bias-Variance Tradeoff
  • Lecture 9: The Linear Model II
  • Lecture 10: Neural Networks
  • Lecture 11: Overfitting
  • Lecture 12: Regularization
  • Lecture 13: Validation
  • Lecture 14: Support Vector Machines
  • Lecture 15: Kernel Methods
  • Lecture 16: Radial Basis Functions
  • Lecture 17: Three Learning Principles
  • Lecture 18: Epilogue
theory - mathematical
technique - practical
analysis - conceptual

 

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