Tutorial part of the sacred workshop on simple iris dataset
├── Makefile <- Makefile with commands like `make data` or `make train`
│
├── README.md <- The top-level README for developers using this project.
│
├── data <- Data directory (not on GitHub)
│
├── models <- Trained and serialized models, model predictions, or model summaries
│
├── 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
│
├── data <- Scripts to download or generate data
│ └── make_dataset.py
│
└── models <- Scripts to train models and then use trained models to make
│ predictions
├── predict_model.py
└── train_model.py
Project based on the cookiecutter data science project template. #cookiecutterdatascience