On Monday, May 28, 2018, kirby urner <kirby.ur...@gmail.com> wrote: > > Wes or someone may have linked to this already. Just tuned it in myself: > > https://colab.research.google.com/notebooks/basic_features_overview.ipynb >
CoLab is pretty cool. They have GPU instances. Kaggle also has GPU instances now with Kernels and Learn. https://www.kaggle.com/kernels https://www.kaggle.com/learn/overview We worked on a Kaggle data science competition as a team of individuals teaching each other through our local Python Users Group. It was a house prices prediction competition; similar to the well-known Boston house prices dataset included with scikit-learn. There are a bunch of hosted Jupyter Notebook services now: https://github.com/markusschanta/awesome-jupyter/blob/master/README.md#hosted-notebook-solutions To host local instances of Jupyter for a group of size n, there are JupyterHub 'spawners' and 'authenticators'. https://zero-to-jupyterhub.readthedocs.io/en/latest/ https://github.com/jupyterhub/jupyterhub/wiki/Spawners https://github.com/jupyterhub/jupyterhub/wiki/Authenticators Gvisor is strongly recommended for sandboxing hosted containers with Docker: https://github.com/google/gvisor Binder builds upon JupyterHub but doesn't have auth yet: https://github.com/jupyterhub/binderhub/issues/323 > > That's Google's way of letting us use Jupyter Notebooks in the cloud and > to share them on Google Drive. > Storage: https://github.com/jupyter/jupyter-drive Storage + Real-time collaboration: https://github.com/jupyterlab/jupyterlab-google-drive > > I see where students would benefit, not that this is the first or only > cloud-based environment. Another great tool. > > Kirby > >
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