Title:  Introduction To Machine Learning using Python

By: Professor Laurent HEUTTE

Abstract:

This course will develop an introduction to Machine Learning, by reviewing the fundamental principles (supervised vs unsupervised, algorithms taxonomy, model complexity, model selection…) and methods (LDA, KNN, SVM, LMP, decision trees, random forest). The course will be accompanied by a hands-on practical (in python), during which some datasets will be processed to assess and compare the performance of the various methods studied (running time, stability, sensitivity to noise/outliers, etc).