Machine Learning

This course will cover the most fundamental concepts and algorithms in machine learning. The materials will be presented in a practical way such that students will get skills to work with important libraries and frameworks like scikit-learn, Keras and Pytorch. We try to cover the following topics: Linear Algebra overview K-nearest Neighbors Classifier Decision Trees Linear Methods for Regression Linear Classifiers Support Vector Machines Neural Networks Boosting and Bagging Probabilistic Classifiers Clustering Dimensionality Reduction

Lecture Info

  • Instructor: Amir Ali Ghahramani
  • Meeting time: Saturdays and Mondays, 11:00 - 12:30
  • Location:
  • Email: