model-credit's Introduction

Credit Project

==============================

Credit Default Prediction Project

To see the data dictionary, you could visit: https://www.kaggle.com/datasets/uciml/default-of-credit-card-clients-dataset

Project Organization

├── LICENSE
├── README.md          <- The top-level README for developers using this project.
├── data
│   ├── scores         <- Results from scoring model.
│   ├── processed      <- The final, canonical data sets for modeling.
│   └── raw            <- The original, immutable data dump.
│
├── models             <- Trained and serialized models, model predictions, or model summaries
│
├── notebooks          <- Jupyter notebooks. Naming convention is a number (for ordering)
│
├── requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.
│                         generated with `pip freeze > requirements.txt`
│
├── setup.py           <- makes project pip installable (pip install -e .) so src can be imported
├── src                <- Source code for use in this project.
│   ├── __init__.py    <- Makes src a Python module
│   │
│   ├── make_dataset.py<- Script to prepare data
│   │
│   ├── train.py       <- Script to train models
│   │                    
│   ├── evaluate.py    <- Script to evaluate models using kpi's
│   │
│   └── predict.py     <- Script to use trained models to make predictions
│
└── LICENSE            <- License

Project based on the cookiecutter data science project template. #cookiecutterdatascience

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