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Explainability and interpretability aren't used interchangeably.Review LaterTrueFalse

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Explainability and interpretability aren't used interchangeably.Review LaterTrueFalse

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True. Explainability and interpretability are two different concepts in the field of machine learning and are not used interchangeably. Explainability refers to the degree to which a human can understand the decision-making process of a model, while interpretability is the degree to which a human can consistently predict a model's result. The two terms, while related, have distinct meanings.

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