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updates docs to reflect new directory structure; adds more general name to visualization directory
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docs/docs/index.md

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@@ -70,7 +70,7 @@ Starting a new project is as easy as running this command at the command line. N
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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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├── 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.
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│   ├── features <- Scripts to turn raw data into features for modeling
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│   │   └── 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
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│   └── train_model.py
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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
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│   │   └── train_model.py
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│ │
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│   └── visualization <- Scripts to create exploratory and results oriented visualizations
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│   └── visualize.py
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└── tox.ini <- tox file with settings for running tox; see tox.testrun.org
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└── tox.ini <- tox file with settings for running tox; see tox.testrun.org
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```
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## Opinions

{{ cookiecutter.repo_name }}/README.md

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@@ -17,7 +17,7 @@ Project Organization
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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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├── 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.
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│   ├── features <- Scripts to turn raw data into features for modeling
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│   │   └── 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
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│   └── train_model.py
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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
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│   │   └── train_model.py
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│ │
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│   └── visualization <- Scripts to create exploratory and results oriented visualizations
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│   └── visualize.py
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└── tox.ini <- tox file with settings for running tox; see tox.testrun.org
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└── tox.ini <- tox file with settings for running tox; see tox.testrun.org

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