A machine learning model developed to predict credit risk and assign credit scores, supporting data-driven lending decisions for Bati Bank's Buy-Now-Pay-Later (BNPL) service in collaboration with an eCommerce platform.
The repository is organized into the following directories:
.github/workflows/: Contains configurations for GitHub Actions, enabling continuous integration and automated testing.
.vscode/: Configuration files for the Visual Studio Code editor, optimizing the development environment.
api: Contains the implementation of the machine learning model API, allowing interaction with the model through RESTful endpoints.
notebooks/: Jupyter notebooks used for tasks such as data exploration, feature engineering, and preliminary modeling.
scripts/: Python scripts for data preprocessing, feature extraction, and the implementation of the credit scoring model.
tests/: Unit tests to ensure the correctness and robustness of the implemented model and data processing logic.
To run the project locally, follow these steps:
- Clone the Repository:
git clone https://github.com/epythonlab/bati-bank-credit-scoring.git`
cd bati-bank-credit-scoring
- Set up the Virtual Environment:
Create a virtual environment to manage the project's dependencies:
For Linux/MacOS
python3 -m venv .venv
source .venv/bin/activate
For Windows:
python -m venv .venv
.venv\Scripts\activate
- Install Dependencies:
Install the required Python packages by running:
pip install -r requirements.txt
We welcome contributions to improve the project. Please follow the steps below to contribute:
- Fork the repository.
- Create a new branch for your feature or bugfix.
- Submit a pull request with a detailed explanation of your changes.