Outcomes from machine learning models suffer from physical and human interpretability in such a way that data scientists are unable to transfer their knowledge to non-technical people. Join our Data Scientist, Andrea Giussani, to explore the results of an xbooster classifier with Shap values.
During this session we will learn about:
– Xgboost library: including fit and predict methods
– Shap values
Don’t miss this webinar on November 4th at 9 a.m. PT | 12 p.m. ET | 6 p.m. CET.
– All registrants will receive the recording of the webinar via email