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End to End usecases using Intel System Stacks
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DnPlas and unrahul Adds Handwritten Digit Recognition example (#43)
* Adds handwritten digit recognition example

* Python scripts for training, classifying and model serving
* Docker images for all tasks mentioned above

Signed-off-by: Daniela Plascencia <daniela.plascencia@linux.intel.com>

* kubeflow/pipelines: Adds handwritten recog example

Signed-off-by: Daniela Plascencia <daniela.plascencia@linux.intel.com>

* Adds LICENSE to train script

Signed-off-by: Daniela Plascencia <daniela.plascencia@linux.intel.com>
Latest commit c6647c7 Jan 15, 2020
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handwritten_digit_recog Adds Handwritten Digit Recognition example (#43) Jan 15, 2020
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zeppelin-notebook Update .travis.yml to build zeppelin-notebook Nov 27, 2019
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README.md

Intel System Stacks Usecases

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The Clear Linux* OS based reference stacks allow developers to quickly get up and running with images tailored, optimized, and tested together for specific use cases. This repository offers example use cases to explore the possibilities.

Contributing

Security Issues

Security issues can be reported to Intel's security incident response team via https://intel.com/security.

Coding Style

We love pep8 (except for the line length of 79, we deem a length of 90 is good), and use black to ensure that coding style is consitent, please run black xx.py if you are making any change to python files.

Mailing List

See our public mailing list page for details on how to contact us. You should only subscribe to the Stacks mailing lists using an email address that you don't mind being public.

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