Future of Interpretability
Christoph and Tim discuss the evolving landscape of machine learning interpretability, emphasizing the need for critical thinking alongside automated reporting. They explore the potential for standardization and simplification in the interpretability process to make it more accessible and engaging for all users.In this clip
From this podcast
Machine Learning Street Talk (MLST)
047 Interpretable Machine Learning - Christoph Molnar
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