Course on machine learning (Feb. 2020)
A three-day introductory course on Machine Learning was held by Sebastian Lerch and Eva-Maria Walz from 19th - 21st February 2020 at KIT within the framework of a graduate school of the KIT Center "Mathematics in Sciences, Engineering and Economics" (MathSEE). Around 25 early career scientists (of which four W2W PhD students) from a wide range of disciplines including mathematics, meteorology, economics, mechanical engineering, computer science, computational chemistry and architecture learned about the basics of machine learning modeling and the state of the art techniques such as random forests, gradient boosting machines and neural networks.
Lectures on the theoretical background of machine learning were accompanied by hands-on programming exercises in Python that covered practical aspects of implementing machine learning methods for analyzing scientific and real-world datasets.
A podcast about this workshop has been produced by KIT. You can listen to it (in German) here.