Machine Learning

Course I took during Q1 of my second year while at UTwente. I took this course to refresh my basics of Machine Learning, hoping to prepare me for the Mater’s Thesis.

Topics Covered

• Preliminaries (Linear Algebra & Probabilities)
  • Inner Product
  • Probability Density Function, Gaussian distribution
  • A practical on ML basics
• Machine Learning Paradigms
• Data Mining — seems like they reused a lot of info from Data Science in this lecture.
• Linear Discriminants
• Decision Trees (CART)
  • Decision Tree Practical
  • Bagging
  • Random Forest
• Linear Regression with Gradient Descent
• Multi Layer Perceptron (MLP)
• Support Vector Machine (SVM)