Project organization

The project is organized as follows:

├── README.md
├── data
│ ├── interim <- Intermediate data that has been transformed.
│ ├── processed <- The final, canonical data sets for modeling.
│ └── raw <- The original, immutable data dump.
│
├── docs <- The Sphinx Documentation.
│
├── models <- Contains saved model as .pkl
│
├── mlruns <- Contains mlflow runs (Our experiment and runs are on the “1” folder)
│
├── notebooks <- Jupyter notebooks
│
├── predictions <- Contains the predictions of the three models as csv files
│
├── conda.yml <- The conda environnement properties
│
├── 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
│
├── features <- Scripts to turn raw data into features for modeling
│ │
│ └── build_features.py
│
└── models <- Scripts to train models and then use trained models to make predictions

│
├── predict_model.py
├── train_model.py
└── train_mlflow.py