This streamlit app demonstrate how a company may evaluate a person credit score, you can see the app live here.
If you want to run the app locally you can clone the project
git clone https://github.com/devmedeiros/credit-score-classification-app
Install the requirements
pip install -r requirements.txt
Enter the project directory
cd credit-score-classification-app
Run the Streamlit App
streamlit run app/streamlit_app.py
├── LICENSE
├── README.md <- The top-level README for developers using this project.
├── data
│ ├── external <- Data from third party sources.
│ ├── interim <- Intermediate data that has been transformed.
│ └── processed <- The final, canonical data sets for modeling.
│
├── app <- Streamlit App.
│
├── models <- Trained and serialized models.
│
├── notebooks <- Jupyter notebooks. Naming convention is a number (for ordering)
│ and a short `-` delimited description, e.g.
│ `1.0-initial-data-exploration`.
│
├── references <- Data dictionary.
│
├── reports <- Generated analysis as HTML, PDF, LaTeX, etc.
│ └── figures <- Generated graphics and figures to be used in reporting
│
└── requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
generated with `pip freeze > requirements.txt`
- improve machine learning model
Project based on the cookiecutter data science project template.