Tutorial on how to deploy Deep Learning models on GPU enabled Kubernetes cluster

deep-learning flask gpu kubernetes python tensorflow

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Fidan Boylu Uz 5beb3818d8 changes to nb 00-03, added test_utilities		2018-04-02 17:55:51 +00:00
.gitignore	Initial commit	2018-03-20 03:47:11 -07:00
00_DevelopModel.ipynb	changes to nb 00-03, added test_utilities	2018-04-02 17:55:51 +00:00
01_DevelopModelDriver.ipynb	changes to nb 00-03, added test_utilities	2018-04-02 17:55:51 +00:00
02_BuildImage.ipynb	changes to nb 00-03, added test_utilities	2018-04-02 17:55:51 +00:00
03_TestLocally.ipynb	changes to nb 00-03, added test_utilities	2018-04-02 17:55:51 +00:00
04_DeployOnAKS.ipynb	new notebooks	2018-03-29 22:07:49 +00:00
05_TestWebApp.ipynb	new notebooks	2018-03-29 22:07:49 +00:00
LICENSE	Initial commit	2018-03-20 03:47:14 -07:00
README.md	Initial commit	2018-03-20 03:47:15 -07:00
resnet152.py	changes to nb 00-03, added test_utilities	2018-04-02 17:55:51 +00:00
testing_utilities.py	changes to nb 00-03, added test_utilities	2018-04-02 17:55:51 +00:00

README.md

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.

When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.