This repository provides a short introduction into the most popular model-agnostic IML (interpretable machine learning) methods. The theoretical background and examples are demonstrated via a slide set. Users can apply this knowledge on various excercises on real-world data, which are also provided with detailed solutions.
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This repository provides a short introduction into the most popular model-agnostic IML (interpretable machine learning) methods. A presentation containing the theoretical background and examples as well as excercises on real-world data are included.
License: Apache License 2.0