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Artifact pipeline from https://github.com/Taewook-Ko/Recommender-System-Papers

program:taewook-ko-recommender-system-papers-github-artifact (v1.0.0)
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License: CC BY-SA 4.0
Creation date: 2020-05-01
Source: paperswithcode.com
cID: b0ac08fe1d3c2615:49d70fd2d79f9ab0

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Description  

This portable workflow is our attempt to provide a common CLI with Python JSON API and a JSON meta description to automatically detect or install required components (models, data sets, libraries, frameworks, tools), and then build, run, validate, benchmark and auto-tune the associated method (program) across diverse models, datasets, compilers, platforms and environments. Our on-going project is to make the onboarding process as simple as possible via this platform. Please check this CK white paper and don't hesitate to contact us if you have suggestions or feedback!
  • Automation framework: CK
  • Source: paperswithcode.com
  • Available command lines:
    • ck run program:taewook-ko-recommender-system-papers-github-artifact --cmd_key=default (META)
  • Support for host OS: any
  • Support for target OS: any
  • Tags: imported-artifact,raw-artifact,black-box,github,taewook-ko-recommender-system-papers,click-through rate prediction,feature engineering,recommendation systems,vmaster,branch-master
  • How to get the stable version via the client:
    pip install cbench
    cb download program:taewook-ko-recommender-system-papers-github-artifact --version=1.0.0 --all
    ck run program:taewook-ko-recommender-system-papers-github-artifact
  • How to get the development version:
    pip install ck

    ck run program:taewook-ko-recommender-system-papers-github-artifact
  • CLI and Python API: module:program

    • Dependencies    

    ReadMe  

    Imported from https://github.com/Taewook-Ko/Recommender-System-Papers

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