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Bias detection and explainability in ML

March 22, 2022

Machine learning is increasingly used to assist decision making in financial services, education, transportation and healthcare. As decision support systems become more automated, there is a prevailing need to increase fairness-awareness and provide explanations for decisions made by machine learning models. In this session, we share how you can use Amazon SageMaker Clarify to identify different types of data and model bias, and understand how a prediction was generated through model explainability.
Speaker: Pauline Kelly, Solutions Architect, AWS

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