Idea Lists (Upon Request)

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Understand their implications for thought. Their implications for the nature of information itself. The nature of knowledge, and the limitations of knowledge.

  1. Bias-Variance Tradeoff
    1. Overfitting
    2. Controlling complexity
      1. Model simplicity (restriction methods)
      2. Selection methods (over features)
      3. Regularization
  2. Curse of dimensionality
  3. Ensemble Modeling
  4. Occam’s Razor (Formalized)
  5. Training vs. Generalization Error
  6. Interpolation vs. Extrapolation
  7. Smoothness
  8. VC Dimension
  9. Solomonoff Induction
  10. Variance Maximization
  11. Optimizing for Volatility vs Expected Value
  12. Bayes Rule
  13. Bayes Error
  14. Exploration-Exploitation
  15. Manifolds as Data Representation

I would like to make this stuff runnable.


Source: Original Google Doc

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