Feature Stores: The Data Side of ML Pipelines | by Sarah Wooders | riselab | Apr, 2021 | Medium
We need a principled way of managing state in real-time ML pipelines.
6 mentions:
Date: 2021/04/07 22:25
Referring Tweets
@sarahwooders Check out this blog post I wrote with @pschafhalter @mejoeyg about managing features in real-time ML pipelines! t.co/YafetLi2kH
@mejoeyg Anyone using feature stores? I am pretty excited about where the technology is headed and we wrote a short blog post about it t.co/dhssjZbiWj.
@pschafhalter Curious about Feature Stores? Check out our blog post which discusses the problems they address and exciting opportunities for future work (w/ @sarahwooders @mejoeyg)
t.co/vlwA7uiuhv
@ucbrise We need a principled way of managing state in real-time ML pipelines - a blog post by Sarah Wooders
t.co/lRPypVh5ls
@kuromt_ RiseLab（Sparkの開発元のAmpLabの生まれ変わり）から使いやすくスケールするFeature Storeがそのうち公開される予感を感じさせる記事
t.co/7caugaQVv4
@joe_hellerstein Interested in ML featurization and online model serving? Check out @sarahwooders post on Feature Stores. t.co/uwW9KeAj2j @ucbrise #RISELab @Berkeley_EECS
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