tample
Please read install.md for details on how to set up this project.
├── LICENSE
├── tasks.py <- Invoke with commands like `notebook`.
├── README.md <- The top-level README for developers using this project.
├── install.md <- Detailed instructions to set up this project.
├── data
│ ├── external <- Data from third party sources.
│ ├── interim <- Intermediate data that has been transformed.
│ ├── 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),
│ the creator's initials, and a short `-` delimited description, e.g.
│ `1.0-jqp-initial-data-exploration`.
│
├── references <- Data dictionaries, manuals, and all other explanatory materials.
│
├── reports <- Generated analysis as HTML, PDF, LaTeX, etc.
│ └── figures <- Generated graphics and figures to be used in reporting.
│
├── environment.yml <- The requirements file for reproducing the analysis environment.
│
├── .here <- File that will stop the search if none of the other criteria
│ apply when searching head of project.
│
├── setup.py <- Makes project pip installable (pip install -e .)
│ so final_project can be imported.
│
└── final_project <- Source code for use in this project.
├── __init__.py <- Makes final_project 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
│
├── utils <- Scripts to help with common tasks.
└── paths.py <- Helper functions to relative file referencing across project.
│
└── visualization <- Scripts to create exploratory and results oriented visualizations.
└── visualize.py
Project based on the cookiecutter conda data science project template.