Mitigating Bias in Models with SHAP and Fairlearn

Mitigating Bias in Models with SHAP and Fairlearn

Explore techniques for addressing bias in machine learning models through a comprehensive conference talk by Sean Owen from Databricks. Dive into the application of SHAP (SHapley Additive exPlanations) and Fairlearn, two powerful tools for identifying and mitigating bias in AI systems. Learn how these methods can enhance model interpretability, promote fairness, and improve overall model performance. Gain valuable insights into ethical AI practices and discover practical strategies for building more equitable and transparent machine learning solutions.