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Navigating ML Explainability: From Theory to Implementation | Orsalia Andreou | DSC DACH 24
Description
In her tech tutorial, Orsalia demonstrated the growing importance of transparent machine learning models, emphasizing the need for explainability and interpretability for regulators, developers, and business leaders. She guided participants through both theoretical concepts and practical applications, ensuring a comprehensive understanding of these essential aspects. Orsalia highlighted how explainability in ML fosters trust and accountability in decision-making processes.
This tutorial by Orsalia was held on September 11th as part of Tech Tutorials at the DSC DACH 24
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