This project involves fitting four machine learning models to predict credit risk using a dataset from Germany, which contains 1,000 observations and 10 features. The final results are based on the model with the highest Area Under the Curve (AUC) of the ROC curve.

Story Board

Beautifull ggridges plot using the Singer dataset