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https://github.com/icoxfog417/datascience-template
Data science project template
https://github.com/icoxfog417/datascience-template
amazon-sagemaker-lab datascience jupyter-notebook machine-learning
Last synced: 4 months ago
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Data science project template
- Host: GitHub
- URL: https://github.com/icoxfog417/datascience-template
- Owner: icoxfog417
- License: mit
- Created: 2022-08-11T01:42:26.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2022-12-08T00:56:38.000Z (about 2 years ago)
- Last Synced: 2024-04-15T12:50:35.549Z (10 months ago)
- Topics: amazon-sagemaker-lab, datascience, jupyter-notebook, machine-learning
- Language: Jupyter Notebook
- Homepage:
- Size: 20.5 KB
- Stars: 19
- Watchers: 3
- Forks: 4
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# datascience-template
[](https://github.com/icoxfog417/datascience-template/actions/workflows/ci.yml)
[](https://github.com/pre-commit/pre-commit)
[](https://github.com/psf/black)
[](https://github.com/PyCQA/flake8)
[](https://pycqa.github.io/isort/)
[](https://github.com/python/mypy)Well structured and tested data science project template. You can use this [template](https://docs.github.com/ja/repositories/creating-and-managing-repositories/creating-a-repository-from-a-template) when creating the data sicence repository.
📁 **Organized**: The project structure is refereed to [Cookiecutter Data Science](https://github.com/drivendata/cookiecutter-data-science)
🚀 **Prepared**: Major libraries are prepared in `environment.yml`. If you are familiar with [Colaboratory](https://colab.research.google.com/?utm_source=scs-index) environment, please use `environment-colab.yml` .
✅ **Tested**: `scripts` are checked by common linter when [pre-commit](https://pre-commit.com/).
Here is the notebook link to provide the quick access to your analysis. You can create the conda environment by Right click `Build Conda Environment` or `conda create -f environment.yml` in Studio Lab.
[](https://studiolab.sagemaker.aws/import/github/icoxfog417/datascience-template/blob/main/notebooks/example.ipynb)
## Project Structure
```bash
.
├── data
│ ├── external # data from third party sources.
│ ├── processed # data after processing
│ ├── interim # data that transformed
│ └── raw # raw data
├── models # store models
├── notebooks # store notebooks
├── docs # documentation for your project
├── .gitignore # ignore files that cannot commit to Git
├── .pre-commit-config.yaml # configurations for pre-commit
├── pyproject.toml # dependencies for poetry
├── README.md # describe your project
├── scripts # store source code used in notebook
│ └── __init__.py # make src a Python module
└── tests # store tests
└── __init__.py # make tests a Python module
```## Customization
* `environment.yml`: Please specify the packages and versions. As a default, no version is specified.
* `.pre-commit-config.yaml`: Please check the `rev` to check the code.
* Change the Notebook url for `Open in Studio Lab`.