jupyter-tutorial
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Training materials for setting up and using a research infrastructure based on Jupyter notebooks: https://cusy.io/en/seminars
* [ipython-sql](https://github.com/catherinedevlin/ipython-sql)
* [Home](https://cml.dev/) * [github.com/iterative/cml](https://github.com/iterative/cml) * [CML basic use case](https://github.com/iterative/cml_base_case) * [Example Continuous Machine Learning project](https://github.com/iterative/example_cml)
* [Connected papers in a visual graph](https://www.connectedpapers.com/)
* [github.com/ijl/orjson](https://github.com/ijl/orjson)
* [Atom IDE](https://ide.atom.io/) * [jupyter-notebook](https://atom.io/packages/jupyter-notebook) * [GitKraken](https://atom.io/packages/gitkraken)
* [GitHub](https://github.com/facebook/prophet) * [Docs](https://cran.r-project.org/web/packages/prophet/prophet.pdf) * [example notebooks](https://github.com/facebook/prophet/tree/master/notebooks) * [Example for Dask and Prophet](https://examples.dask.org/applications/forecasting-with-prophet.html)
See [Patterns for Managing Source Code Branches](https://martinfowler.com/articles/branching-patterns.html#mainline).
see [Microsoft Threat Intelligence Security Tools](https://github.com/microsoft/msticpy)
see also * [Home](https://pangeo.io/packages.html) * [GitHUb](https://github.com/pangeo-data/pangeo/)