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8 changes: 6 additions & 2 deletions .github/workflows/tests.yml
Original file line number Diff line number Diff line change
Expand Up @@ -4,10 +4,14 @@ name: tests
on:
push:
branches: [master]
paths-ignore: "docs/**"
paths-ignore:
- "docs/**"
- "README.md"
pull_request:
branches: [master]
paths-ignore: "docs/**"
paths-ignore:
- "docs/**"
- "README.md"
schedule:
# Run every Sunday
- cron: "0 0 * * 0"
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29 changes: 14 additions & 15 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -43,16 +43,16 @@ The directory structure of your new project will look something like this (depen
│ ├── processed <- The final, canonical data sets for modeling.
│ └── raw <- The original, immutable data dump.
├── docs <- A default mkdocs project; see mkdocs.org for details
├── docs <- A default mkdocs project; see www.mkdocs.org for details
├── 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`.
├── pyproject.toml <- Project configuration file with package metadata for {{ cookiecutter.module_name }}
│ and configuration for tools like black
├── pyproject.toml <- Project configuration file with package metadata for
{{ cookiecutter.module_name }} and configuration for tools like black
├── references <- Data dictionaries, manuals, and all other explanatory materials.
Expand All @@ -64,23 +64,22 @@ The directory structure of your new project will look something like this (depen
├── setup.cfg <- Configuration file for flake8
└── {{ cookiecutter.module_name }} <- Source code for use in this project.
└── {{ cookiecutter.module_name }} <- Source code for use in this project.
├── __init__.py <- Makes {{ cookiecutter.module_name }} a Python module
├── __init__.py <- Makes {{ cookiecutter.module_name }} a Python module
├── data <- Scripts to download or generate data
│ └── make_dataset.py
├── config.py <- Store useful variables and configuration
├── features <- Scripts to turn raw data into features for modeling
│ └── build_features.py
├── dataset.py <- Scripts to download or generate data
├── models <- Scripts to train models and then use trained models to make
│ │ predictions
│ ├── predict_model.py
│ └── train_model.py
├── features.py <- Code to create features for modeling
└── visualization <- Scripts to create exploratory and results oriented visualizations
└── visualize.py
├── modeling
│ ├── __init__.py
│ ├── predict.py <- Code to run model inference with trained models
│ └── train.py <- Code to train models
└── plots.py <- Code to create visualizations
```

## Using v1
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