This repository contains my project on predicting credit risk using machine learning.
In this project, I developed a machine learning model to predict the likelihood of loan default. The primary goal was to assist lending institutions in making informed decisions when evaluating loan applications. The project included the following steps:
- Data Preprocessing
- Feature Engineering
- Model Development
- Model Evaluation
The dataset used for this project is the LendingClub dataset, which contains historical data on loan applications, approved loans, and loan statuses.
- Python
- Jupyter Notebook
- Scikit-Learn
- Pandas
- Matplotlib
- Seaborn
The results of the machine learning classification, including model performance metrics and insights, are available in the .ppt file. These insights provide an overview of the model's recall and ROC-AUC curve.