Feature Stores for ML

Data scientists are duplicating work because they don’t have a centralized feature store. Everybody I talk to really wants to build or even buy a feature store……if an organization had a feature store, the ramp-up period [for Data Scientists] can be much faster. Harish Dodi, O’Reilly Podcast Hopsworks The first fully open-source Feature Store, based around Dataframes (Spark/Pandas), Hive (offline), and MySQL Cluster (online) databases. Zipline AirBnB use Zipline for Feature management as par

4 mentions: @keigohtr@chezou@AxSaucedo@EthicalML
Date: 2020/01/28 08:21

Referring Tweets

@keigohtr feature storeについてまとめたサイト。ボリュームがすごすぎてキャッチアップが捗る。 #mlopsslack t.co/5I8JvIxSuA
@EthicalML Feature Stores for ML: Duplicated work in data science scales fast. Feature stores have potential for re-usability. This site contains an excellent list of resources including videos, articles and beyond. t.co/VGLffNqqa2 t.co/skaADFjEDF
@AxSaucedo Feature Stores for ML: Duplicated work in data science scales fast. Feature stores have potential for re-usability. This site contains an excellent list of resources including videos, articles and beyond. t.co/21qDanvCMb t.co/s3HZeVt98t
@chezou feature storeのOSS/closed sourceのまとめ。発表動画とfeature comparisonもあるのは良い。あれ、でもこれ違う基盤も混ざってない?/Feature Stores for ML t.co/u9sS1ORgGw

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