pip install -r requirements.txt

├── README.md          <- The top-level README for developers using this project.
├── data
│   ├── 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),
│
├── 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
│
├── 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
│   │
│   ├── data           <- Scripts to download or generate data
│   │   └── get_openml_data.py
│   │
│   ├── features       <- Scripts to turn raw data into features for modeling
│   │   ├── calcers    <- Calcers realization for features
│   │   │   ├── base_calcer.py
│   │   │   ├── mapper_features.py
│   │   │   ├── stats_features.py
│   │   │   ├── target_features.py
│   │   │   └── tda_features.py
│   │   ├── tda_feature_engineering.py
│   │   └── build_features.py
│   │
│   ├── models         <- Scripts to train models
│   │   ├── feature_importances.py
│   │   └── train_model.py
│   │
│   ├── mlflow_utils.py
│   └── utils.py
├── tests              <- unit tests
│   ├── conftest.py
│   └── tests.py
└── test_environment.py

mlflow server --backend-store-uri sqlite:///mlruns.db --default-artifact-root artifacts

src/data/get_openml_data.py --config config/params.yaml

src/features/build_features.py --config config/params.yaml

src/models/train_model.py --config config/params.yaml