Lecture 13 - Linear Regression via Least Squares#

Objectives#

  • Define supervised learning.

  • Define regression tasks.

  • Define classification tasks.

  • Perform linear regression with a single variable using least squares.

  • Perform polynomial regression with a single variable using least squares.

  • Perform regression with any generalized linear model using least squares.

  • Explain the concepts of overfitting and underfitting.

  • Use the mean square error of a validation dataset to assess the goodness of fit of a regression model.