Supervised Learning

• You give the model both input data and desired outputs.
  • Examples:
    • Predicting house prices from size. (Simple Linear Regression, Multiple Linear Regression)
    • Classifying emails as spam or not spam. (Classification)
  • Relies heavily on the availability of labelled data.