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While machine learning and deep learning models often produce good classifications and predictions, they are almost never perfect. Models almost always have some percentage of false positive and false negative predictions. That’s sometimes acceptable, but matters a lot when the stakes are high. For example, a drone weapons system that falsely identifies a school as […]

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Matt Turek ,Christoph Molnar ,Google ,Microsoft Research ,Defense Advanced Research Projects Agency ,Data Labeling Service ,Wells Fargo ,Microsoft ,Machine Learning ,Azure Machine ,Interpretable Machine Learning ,Google Cloud Platform ,What If Tool ,Feature Fit ,Feature Effects ,

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