Course curriculum

  • 1

    Intro to Machine Learning (Supervised Learning with Linear Models)

    • Intro to ML

    • Linear Regression

    • Logistic Regression

    • Support Vector Machines
  • 2

    Supervised Learning with Non-Linear Models

    • Decision Trees

    • K-Nearest Neighbours

    • Random Forest

    • Gradient Boosted Machines
  • 3

    Unsupervised Learning

    • K-Means

    • Principal Component Analysis