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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!
ck run program:lnferreira-time_series_clustering_via_community_detection-github-artifact --cmd_key=default
Support for host OS: any
Support for target OS: any
Tags: imported-artifact,raw-artifact,black-box,github,lnferreira-time_series_clustering_via_community_detection,community detection,time series,time series analysis,time series clustering,vmaster,branch-master