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Interpretable Machine Learning using Counterfactuals

Explainable AI through counterfactual examples for model transparency.

Alibi provides counterfactual explanations for machine learning models, helping organizations understand and justify AI decisions. Used by data scientists and compliance teams to interpret model behavior and identify potential biases. Generates human-readable 'what-if' scenarios explaining why models make specific predictions.