Interdisciplinary Center for Applied Machine Learning - ICAML

The ICAML (Interdisciplinary Center for Applied Machine Learning) aims to make machine learning interdisciplinary accessible by developing and applying three fundamental components of teaching.

The first component is the provision of courses and events with a focus on modules that can be accessed via the Internet. These modules are supplemented by lectures and lectures, the spectrum of which ranges from basic tutorials to methods of machine learning and the handling of specific data types.

The second component consists of the provision of information and knowledge. On the one hand, the existing knowledge of the persons and institutes involved is collected and prepared for use on the platform. On the other hand, external sources are collected, commented on and evaluated with regard to content. These knowledge packages support the offered courses significantly, but at the same time serve as an entry point for potentially interested parties. The collection of knowledge units is not static but is updated and expanded with the collected experiences and results.

The third component is the administration and maintenance of a computing cluster. Through this cluster, the participants have access to the computing power needed for machine learning and thus have the opportunity to gain practical experience. On the one hand, project and final papers in the field of machine learning are made possible, on the other hand, the cluster plays a central role in the execution of practical exercises which accompany the offered courses.

If you are interested in machine learning or would like to use our offer for a project or your thesis visit www.icaml.org. In collaboration with the  Institute of Photogrammetry and GeoInformation (IPI), German Aerospace Center (DLR).