MAI4CAREU - Machine Learning: Trees and Forests Created byLaia Güell Paule|Updated27 July 2024The University of Cyprus's MSc Artificial Intelligence is part of the Master programmes in Artificial Intelligence 4 Careers in Europe (MAI4CAREU). One of Master's programme's courses, MAI612 - Machine Learning is split up into several lectures. Taught by Vassilis Vassiliades, PhD, the sixth lecture of the MAI612 - Machine Learning course focuses on Trees and Forests.Learning outcomesHow decision tree models workHow to train decision trees using the concepts of entropy and information gainHow to use continuous variables in decision treesClassification and regression treesWhy ensembles of models can achieve lower generalization errorsEnsemble methods such as bagging, random forests, boosting, XGBoost and stackingLearning contentWebsite link MAI4CAREU - Lecture 6 - Trees and ForestsTarget audienceDigital skills for ICT professionals and other digital experts.Digital skill levelIntermediateAdvancedDigital ExpertGeographic scope - CountryAustriaBelgiumBulgariaCyprusRomaniaSloveniaCroatiaCzech republicDenmarkEstoniaFinlandFranceGermanyGreeceHungaryItalyIrelandMaltaLatviaLithuaniaLuxembourgNetherlandsPortugalPolandSwedenSpainSlovakiaShow moreShow less Share this page Log in to comment