Interpretable Machine Learning Insights
Keith discusses insights from Molnar's book on interpretable machine learning, highlighting the importance of expressive power in generating explanations for models. The book's clear taxonomy and emphasis on limitations provide a valuable survey of current trends in the field.In this clip
From this podcast
Machine Learning Street Talk (MLST)
Explainability, Reasoning, Priors and GPT-3
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