Machine Learning Introductory Project


Recently, I started doing projects from the Udacity Machine Learning Nanodegree. This is the first project of the whole course. Since it is an introductory course, the project covers central topics of machine learning:

  • Training and testing data
  • Goodness of fit: Coefficient of determination (R^2)
  • Over- and underfitting
  • Bias-variance tradeoff
  • Grid search
  • Cross-validation