/credit-risk-resampling-with-ML

Credit Risk Resampling

Primary LanguageJupyter Notebook

#Credit Risk Resampling

Create a basic machine learning model to address the classification problem inherent to credit portfolios.

Sequential pproach to model fitting:

  • Split the Data into Training and Testing Sets
  • Create a Logistic Regression Model with the Original Data
  • Predict a Logistic Regression Model with Resampled Training Data

Technologies:

  • Python IDE (JupyterLab)
  • Libraries: pandas, numpy, sklearn, matplotlib, pathlib, imblearn

Contributors: Lee Copeland

Columbia Engineering