SHAP opens up the ML black box by providing feature attributions for every prediction of every model. Being a relatively new method (arxiv.org/abs/[masked]) , SHAP is gaining popularity extremely quickly thanks to its user-friendly API and theoretical guarantees. In this talk I will guide your intuition through the exciting theory SHAP is based on, and demonstrate how SHAP values can be aggregated to understand model behavior. Throughout the talk I will present real-life examples for using SHAP in the fraud detection domain at PayPal, and in the medical domain as provided by the SHAP authors’. EVENT:
PyData Tel Aviv 2020 SPEAKER:
Adi Watzman PUBLICATION PERMISSIONS:
PyData provided Coding Tech with the permission to republish PyData talks. CREDITS:
Original video source: https://www.youtube.com/watch?v=0yXtdkIL3Xk https://www.youtube.com/watch?v=1YWDcGTVkyM