The objective of this case study is to fit and compare 4 different binary classification models (classifiers) to predict whether a customer has good credit history or bad using the German Credit dataset. The dataset is sourced from the UCI Machine Learning Repository (https://archive.ics.uci.edu/ml/datasets/statlog+(german+credit+data))
The data can be found in S3779009_Data file, while the implementation is in Predicting Credit Risk of Customers.ipynb file You can see the detailed report of the case in Predicting Credit Risk of Customers.html document.