counterfactual-explanations

1 free lesson tagged counterfactual-explanations across AI. Each one is a short sequence of focused steps with narration and a five-question quiz at the end — take them in any order, no signup required.

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Gradients, Counterfactuals, and Whether to Trust an Explanation

When a model is differentiable you can attribute a prediction with calculus instead of sampling. This lesson covers plain saliency, Integrated Gradients and its axioms, Grad-CAM, then counterfactual explanations, which answer what would have to change rather than what mattered. It closes with the evidence that explanations can fail or be deliberately faked, and a protocol for checking yours.

12 steps·~18 min

Gradients, Counterfactuals, and Whether to Trust an Explanation

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