project_description
├── LICENSE
├── README.md <- The top-level README for developers using this project.
│
├── data
│ ├── raw <- The original, immutable data dump.
│ ├── external <- Data from third party sources.
│ ├── interim <- Intermediate data that has been transformed.
│ └── processed <- The final, canonical data sets for modeling.
│
├── models <- Trained and serialized models, model predictions, or model summaries
│
├── notebooks
│ ├── src <- Jupyter Notebooks. Naming convention is
│ │ (where # and initials are optional):
│ │ [#]_[2-4 word description]_[initials].ipynb
│ │ e.g. 1_exploratory_analysis_ag.ipynb
│ │
│ ├── py <- Script version of notebooks.
│ ├── html <- HTML version of notebooks.
│ └── archive <- Datestamped archive notebooks. Naming convention is:
│ [#]_[2-4 word description]_[DS-initials]_[ISO 8601 date].ipynb
│
├── references <- Data dictionaries, manuals, and all other explanatory materials.
│
├── reports <- Deliverable reports 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`
│
├── setup.py <- makes project pip installable (pip install -e .) so src can be imported
└── src <- Source code for use in this project.
├── features <- Scripts to turn raw data into features for modeling
│ └── build_features.py
├── __init__.py <- Makes src a Python module
│
├── data <- Scripts to download or generate data
│ └── make_dataset.py
│
├── 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
│
└── visualization <- Scripts to create exploratory and results oriented visualizations
└── visualize.py