Machine Learning

  1. Features
  2. Target
  3. Training Example
  4. Training Set
  5. Hypothesis
  6. Regression
  7. Classification
  8. Supervised Learning
  9. Parameters / Weights
  10. Intercept / Bias
  11. Cost Function
  12. Gradient Descent
  13. Learning Rate
  14. LMS (least mean squares) update rule / Widrow-Hoff learning rule
  15. Batch Gradient Descent
  16. Stochastic/Incremental Gradient Descent
  17. Unsupervised Learning