The Machine Learning Summer School (MLSS) is a 12-day event where participants take intensive courses on a variety of topics in machine learning, ranging from optimization and Bayesian inference to deep learning, reinforcement learning and Gaussian processes (see topics). The objective of the MLSS is to give a broad overview of many relevant topics in machine learning and to help training the next generation of machine learning researchers.

The lectures will be of tutorial style, assuming a solid background knowledge in mathematics and statistics, but then quickly picking up the pace so that after 2-4 hours of teaching we arrive at the state of the art in the subject area.