Examples: query, "exact match", wildcard*, wild?ard, wild*rd
Fuzzy search: cake~ (finds cakes, bake)
Term boost: "red velvet"^4, chocolate^2
Field grouping: tags:(+work -"fun-stuff")
Escaping: Escape characters +-&|!(){}[]^"~*?:\ with \, e.g. \+
Range search: properties.timestamp:[1587729413488 TO *] (inclusive), properties.title:{A TO Z}(excluding A and Z)
Combinations: chocolate AND vanilla, chocolate OR vanilla, (chocolate OR vanilla) NOT "vanilla pudding"
Field search: properties.title:"The Title" AND text
Answered
You Guys, Thank You So Much. I Have Super Positive Things To Say About Clearml And I'M Very Excited To Try It Out At Work (Still Selling It)

You guys, thank you so much. I have super positive things to say about ClearML and I'm very excited to try it out at work (still selling it) https://www.linkedin.com/posts/eric-riddoch_im-still-early-in-clearml-but-im-beginnin[…]392438874112-PqgT?utm_source=share&utm_medium=member_desktop

  
  
Posted one year ago
Votes Newest

Answers


Yes, thank you from me too! Wrapping up a project where we ended up deploying a self hosted version on EKS and leveraging its autoscaling abilities. Ticked a lot boxes for our team from model deployment to running pipelines, tracking experiments, storing artifacts and even allowing the deployment of some R code/models by making the use of custom docker images a breeze 😅

Given once your pipes become sufficiently complex and start to veer more outside the ML domain, you might opt in for some other solution to be run in parallel, e.g., Airflow, Dagster, argoflow, ... out of which the latter acts as a backbone for Kubeflow pipes.

Would be happy to recommend ClearML and even the enterprise versions for large enough orgs : )

  
  
Posted one year ago
1K Views
1 Answer
one year ago
one year ago
Tags