Top Tweets for #FeatureStore
More sessions like this are lined up for QCon London 2027, April 13-16.
Find out more about QCon London 2027 here: https://t.co/ZsNGcZPHdj
#QConLondon #FeatureStore #DataEngineering
More sessions like this are lined up for QCon London 2027, April 13-16.
Find out more about QCon London 2027 here: https://t.co/Q1E8qKwjPE
#QConLondon #FeatureStore #MLInfrastructure
More sessions like this are lined up for QCon London 2027, April 13-16.
Find out more about QCon London 2027 here: https://t.co/3bVbPlHL7x
#QConLondon #FeatureStore #MLInfrastructure
More sessions like this are lined up for QCon London 2027, April 13-16.
Find out more about QCon London 2027 here: https://t.co/ZY4xexbsAL
#QConLondon #FeatureStore
Build a high-performance feature store with Feast! 🚀 Our new guide shows you how to use @duckdb for seamless historical feature retrieval and Dragonfly for low-latency online feature serving. Code examples inside! #FeatureStore #ML #MLOps
https://t.co/YDlNjPtn1F
🚀 Feast + Kubeflow? The Feast maintainers are proposing to donate Feast to Kubeflow!
Join the discussion & share your thoughts! 👇 https://t.co/FMfW4wcwgK
Link to original post: https://t.co/l5Hzdr2aUv
#Kubeflow #Feast #MLOps #AI #MachineLearning #GenerativeAI #FeatureStore
Which is the best managed feature store provider available to serve high traffic and real time traffic prediction. Please comment below.
#FeatureStore #SaaS #MachineLearning #AI
We described two Feature Store data model alternatives.
https://t.co/cnAurL2KuQ
@Medium use a third one :)
#scylladb #ml #FeatureStore
🌟 Want to know how to build feature stores with RisingWave? 🌊
Xinhao Xu will take you through all the deployment steps of this simple demo!
📘For more: https://t.co/lUUoFTGvid
#ml #machinelearning #ai #featurestore
Scaling an ML Feature Store From 1M to 1B Features per Second https://t.co/Z9HcdbKJeT @c_a_dunlop @scylladb #Sponsored #MachineLearning #FeatureStore
This coming thursday, I will be participating in the #belgian #mlops #meetup and talking about how the @hopsworks #featurestore can be used as #ai / #ml system infrastructure. Join us if you can!
https://t.co/DOXYzDfIqF
Happy to say that today marks my 6-month anniversary at @hopsworks . To celebrate, I wanted to share this short clip that our team created a while ago, but that was hidden too deep in our treasure trove of #ai, #ml, #mlops and #featurestore content: https://t.co/6LK6PCNBlI
@hopsworks @neo4j That's why I wrote this article, and built a spreadsheet ffs :) - to help people make better #ValueCases for their #featurestore #ml #ai platform implementations. Read it over here: https://t.co/hE5bcfsHWT .
Join us for the #live session on Accelerating Price Elasticity #AI Use Cases to Production in 3–4 Weeks with Predictability and Scale: https://t.co/PkJXYBbSC9
#AIChallenges #MachineLearning #UnifyAI #featureengineering #featurestore #aiandml #ai #machinelearning #mlops #data
@simonsinek @hopsworks 1. WHY should I consider a #featurestore.
2. WHY should I BUY, and not BUILD a #featurestore for my #MLOps infrastructure.
3. WHY should I, if I decide to BUY instead of building that piece of infrastructure, choose @hopsworks and nothing else.
Tonight, me and @SirOibaf are enjoying some quality time briefing the lovely folks at @VectrConsulting about the advantage of using a @hopsworks #featurestore for #machinelearning. Thanks @_TomMichiels_, @Jweiren and @ignazw for inviting us!
@hopsworks * and then finally articulating that you should compare the #online+#offline #featurestore in #ai/#ml to the #database+#datawarehouse combo in #applications/#analytics: https://t.co/wIS5lrVWuQ
Here's how I would summarize my own thoughts wrt the differences between (#online and #offline) #featurestores in the #ai and #ml space (left/green - eg. @hopsworks ) and the #databases and #datawarehouses in the #applications and #analytics space (right/red).
One thing that I have had people ask me over the past few months at @hopsworks, is how a #featurestore actually compares to a more traditional #database or #datawarehouse. There are similarities, and there are differences. I plan to get into some more details of this in the next few days - but high-level this looks like this.
¿Qué es el #FeatureStore? ¿Cuándo debemos usar esta solución? ¿Y en qué casos no? Te contamos más sobre esta herramienta tan útil en proyectos de #MLOps en el blog 👇
STHLM data folks: join us for a fantastic @hopsworks and #duckdb meetup at our offices! @SirOibaf and @Maxxen_ sharing their amazing work - highlighting how you can make #MLOps and #featurestore fly!
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