Supervised Machine Learning

Lending services companies allow individual investors to partially fund personal loans as well as buy and sell notes backing the loans on a secondary market.

This project uses lending data to create machine learning models to classify the risk level of given loans. Specifically, the Logistic Regression model and Random Forest Classifier will be created and compared.

Stages

1. Retrieve the Data - lending_data.csv located in Resources folder
2. Predict model performance for Logistic Regression and Random Forests Classifier - recorded in markdown cells of Credit Risk Evaluator.ipynb
3. Split the Data into Training and Testing Sets
4. Create, Fit and Compare Models

References

Loan Approval Dataset (2022). Data for this dataset was generated by edX Boot Camps LLC, and is intended for educational purposes only.