Erklärbares Maschinelles Lernen

Students understand the interpretability and explainability of machine learning systems. They master methods of interpretability and can optimise systems for interpretability. They are able to implement interpretability and explainability mechanisms for machine learning systems.

• Successful completion of exercises and presentation of results in course
• Written examination, 120 min.

• Script and presentations are available for download in Moodle at the beginning of the semester and on an ongoing basis. Problems for exercises and instructions for lab experiments can be downloaded.
• Serg Masis, Interpretable Machine Learning with Python: Learn to build interpretable high-performance models with hands-on real-world examples, Packt 2021
• Ajay Thampi, Interpretable Ai: Building Explainable Machine Learning Systems, Manning 2022
• Christoph Molnar, Interpretable Machine Learning: A Guide For Making Black Box Models Explainable, 2022
• Uday Kamath; John Liu, Explainable Artificial Intelligence: An Introductionto Interpretable Machine Learning, Springer 2021

Bewertungen von Studierenden

Was Studierende über dieses Modul sagen. Die BTU hat damit nichts zu tun — hier schreiben nur Studierende, und jede Bewertung ist die Meinung einer einzelnen Person.