cookiecutter-data-science/{{ cookiecutter.repo_name }}/README.md

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{{cookiecutter.project_name}}
==============================
{{cookiecutter.description}}
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Project Organization
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------------
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├── LICENSE
├── Makefile <- Makefile with commands like `make data` or `make train`
├── README.md <- The top-level README for developers using this project.
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├── data
│   ├── external <- Data from third party sources.
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│   ├── interim <- Intermediate data that has been transformed.
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│   ├── processed <- The final, canonical data sets for modeling.
│   └── raw <- The original, immutable data dump.
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├── docs <- A default Sphinx project; see sphinx-doc.org for details
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├── models <- trained and serialized models, model predictions, or model summaries
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├── notebooks <- Jupyter notebooks. Naming convention is a number (for ordering),
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│ the creator's initials, and a short `-` delimited description, e.g.
`1.0-jqp-initial-data-exploration`.
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├── references <- Data dictionaries, manuals, and all other explanatory materials.
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├── reports <- Generated analysis as HTML, PDF, LaTeX, etc.
│   └── figures <- Generated graphics and figures to be used in reporting
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├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
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│ generated with `pip freeze > requirements.txt`
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├── src <- Source code for use in this project.
│   ├── __init__.py <- Makes src a Python module
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│ │
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│   ├── data <- Scripts to download or generate data
│   │   └── make_dataset.py
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│ │
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│   ├── features <- Scripts to turn raw data into features for modeling
│   │   └── build_features.py
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│ │
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│   └── models <- scripts to train models and then use trained models to make
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│ │ predictions
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│   ├── predict_model.py
│   └── train_model.py
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└── tox.ini <- tox file with settings for running tox; see tox.testrun.org