Machine and Deep Learning

Machine Learning, and the most successful extension of it, Deep Learning, deals with the analysis of data and the development of models. To be able to apply these algorithms, the computer scientist needs to have a good understanding of the foundations of Machine Learning. This course provides a recapitulation of (un)supervised learning, classification, decision theory and overfitting. It introduces some classical statistical learning classifiers and discusses their complexity, and ways to adapt their complexity (regularisation). The course focusses further on Deep Learning, including backpropagation, Convolutional Neural Networks, Recurrent Neural Networks, self-attention and Transformers.