Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.
A demonstration of the explainerdashboard package that that displays model quality, permutation importances, SHAP values and interactions, and individual trees for sklearn RandomForestClassifiers, etc
A Python Package that computes Target Permutation Importances (Null Importances) of a machine learning model.
#计算机科学#Grouped version of permutation importance
#计算机科学#Hitting vs Pitching vs Fielding vs Baserunning (Feature Importance)
#计算机科学#Why do employees leave? This project first compares the predictive performance of three different models, then uses the best model to help reveal the top contributing factors.
Tech Challenge of the Postgraduate in Data Analytics, from FIAP, developing a Data Warehouse with data from PNAD-COVID-19, from IBGE, using Pyspark and Google BigQuery for ETL, as well as an analysis ...