In this course, you will :
- Explain the concept of credit risk and how it is calculated.
- Discuss the logistic regression model, which is a risk modelling standard.
- comprehend the model's components as well as how to evaluate its performance
- Investigate the financial implications of using this model.
- Another common credit risk model is decision trees. We will go beyond decision trees by creating gradient boosted trees with Python's trendy XGBoost package.
- Exploring and Preparing Loan Data
- Logistic Regression for Defaults
- Gradient Boosted Trees Using XGBoost
- Model Evaluation and Implementation