Removing or De-biasing Sensitive Attributes

One mitigation approach involves excluding or transforming sensitive features (e.g., race, gender) from the input data to prevent direct discrimination. Alternatively, implement techniques like adversarial debiasing to train models that are invariant to these sensitive attributes while maintaining predictive accuracy.

One mitigation approach involves excluding or transforming sensitive features (e.g., race, gender) from the input data to prevent direct discrimination. Alternatively, implement techniques like adversarial debiasing to train models that are invariant to these sensitive attributes while maintaining predictive accuracy.

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Retention Forecasting Models for Diverse Tech Talent

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