This project aims to assess credit risk using machine learning techniques. It involves building a predictive model that can classify loan applicants into different risk categories (e.g., low risk, high risk) based on their attributes.
- Predictive modeling using machine learning algorithms
- Preprocessing techniques such as data scaling and one-hot encoding
- Evaluation metrics including accuracy, precision, recall, and F1-score
- Hyperparameter tuning for model optimization
- Visualization of results using plots and charts
To use this project, you need Python and several libraries installed. You can install the required libraries using pip: