Supercharging Open Analytics with Model Diagnostic & Model Explainability

“Is your machine learning model a mystery even to you? Let's decode its decision-making process together and find out why SHAP offers the best of both worlds: global insights and individual explanations.”

We are not afraid to tackle complex models and challenges and explain them. In this session, Boris Pritsker, Applied Data Science Manager, Earnix, explains the critical importance of model explainability in modern analytics and delves deeply into the unique offerings and advantages of Earnix's explainability tools.