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Interpretable ML Interview with Serg Masis (Episode 4)

An awesome guided tour in the world of interpretable machine learning with Serg Masis. Serg Masis is data scientist at Syngenta, a leading science-based agtech company. Serg wrote an amazing book on interpretable machine learning [link]. All the code used for the examples illustrated in the book is freely available [link].

Serg drives us through the concept of interpretability and why it is better than explainability. Why black-box can be interpretable and a white box not? Have you ever heard about glass box models? We went through a lot of topics and modeling approaches.

Resources:

Interpretable Machine Learning with Python – Second Ed

Interpretable Machine Learning with Python – Second Edition [link]

Explainable Boosting Machine [link]

How Interpretable and Trustworthy are GAMs? [link]SHAP (SHapley Additive exPlanations) [link]