Simba Khadder
@simba_khadder
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CEO @FeatureformML, The 'Virtual' Feature Store.
San Francisco, CA
Joined March 2017
I've seen so much success with organizations adoption feature stores. I've also seen lots of confusion. The problem is that the feature store category is broad and ill-defined. In reality, there are three types of feature stores: literal, physical, and virtual.
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Unpacking 3 Types of Feature Stores // @simba_khadder // MLOps Podcast #265:
home.mlops.community
Simba dives into how feature stores have evolved and how they now intersect with vector stores, especially in the world of machine learning and LLMs. He breaks down what embeddings are, how they...
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I've had like 100 companies selling AI SDRs reaching out to me, presumably using their own product. They are the most awkward pseudo-personalized cold email/LI requests. The reach-out doubles as a demo, and it's real bad. IMO, LLMs excel at augmentation, not automation.
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Getting model features into production is hard, but it doesn't have to be! 🌟
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Excited to announce @FeatureformML 's $5.5m seed round, bringing our total to over $8 million! 🚀 Our virtual feature store fundamentally changes how ML teams define, manage, and deploy model features. https://t.co/xy8vhdH2w3
siliconangle.com
Featureform raises $5.5M to bring order to feature management 'chaos' - SiliconANGLE
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Excited for our webinar TOMORROW. Now that Feast is unmaintained, many people I talk to are pondering their next steps. Whether you're actively using Feast, considering Featureform, or curious about the evolving landscape of open-source feature stores, this webinar is for you.
📅 Join us this Thursday, December 7th at 12 PM PT for "OSS Feature Store Comparison: #Featureform & #Feast", hosted by our CEO, @simba_khadder! 🎉 🔗Sign up here:
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🚨 Happening tomorrow, Nov 14th at 8 AM PT! Join us for "Building a #FeatureStore with Featureform & @databricks hosted by @simba_khadder 🎉 Learn how to define & run feature pipelines with Featureform's Python API on Databricks! Q&A to follow. 🎟 https://t.co/3XxNuRie9N
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Had a ton of fun chatting with @CShorten30 on the @weaviate_io podcast! You can listen in to learn more about feature stores and their place in LLM-powered systems.
Hey everyone! I am SUPER excited to publish our 74th Weaviate Podcast featuring Simba Khadder (@simba_khadder), the CEO and Co-Founder of Featureform (@FeatureformML)!! 🎉 Simba is one of the world's experts on building distributed recommendation systems at massive scale! Simba
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.@CMUDB ML⇄DB Seminar Series Video #5 — @simba_khadder (CEO) @FeatureformML: Feature Store Architectures & Technical Challenges https://t.co/pyqinzBxAL
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💢😧: "I don't understand, what do you mean the features in our data warehouse aren't available for model serving & inference in prod?" #datascience #mlops #dataengineering #mlengineer #ml #dataops #featurestores
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🚀 New Blog Alert! "Feature Versioning: A Key Ingredient To Keeping Your Data Science Projects From Going Off The Rails!" 🚂💥 We're diving deep into the world of feature versioning in #MachineLearning. Check it out here: https://t.co/JMBoV4vAOn Time for a 🧵! 1/7
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🤩 We'll also tackle how to manage features & embeddings for practical LLM use cases! 🔖 A must-attend for the following folks: - #DataScientists - #mlengineers - Anyone interested in enhancing their LLM workflows! 🔗 Be sure to RSVP Here: https://t.co/Qzg3TEqKuw
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I have a few invites left for our Executive Cocktail Party at Databricks #DataAISummit tomorrow at 7p. DM me for an invite!
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🔥 EPISODE DROP: 💬 LLMs In Your SQL 🧰 , Declarative ML vs AutoML 🤖, Crabs as nature’s answer to the question “What creature represents the pinnacle of evolution?” 🦀🔪.... This episode has it all. @w4nderlus7 (@predibase) & @simba_khadder talk about: 🧵 1/n
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Really cool to see our feature platform customers be able to use vectors directly This has been a shortcoming of the feature serving world now addressed by @FeatureformML
🥳 Excited to announce v0.9 of @FeatureformML , one of our biggest releases yet! With @Redisinc Vector Store, Embedding Support, API improvements, Expanded Compatibility, and Increased Stability, we're set to make your ML life easier! 🚀 #ml #mlops #datascience 🧵 1/n
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🥳 Excited to announce v0.9 of @FeatureformML , one of our biggest releases yet! With @Redisinc Vector Store, Embedding Support, API improvements, Expanded Compatibility, and Increased Stability, we're set to make your ML life easier! 🚀 #ml #mlops #datascience 🧵 1/n
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Last month, @simba_khadder spoke at the MLOps Community meetup in San Francisco to a packed room. It was a memorable night and for those who missed it or live on the other side of the world, here is Simba’s talk from the evening.
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🚨 ATTENTION: The Eagle Has Landed! 🎉 The eagerly anticipated Feature Engineering Guide Part 1 is now live on the site! 🔗 Access it here for free: https://t.co/C4h1hMZIUO
#featureengineering #datascience #machinelearning #mlops #dataops #featurestores #feature #bestpractices
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Had such an awesome conversation with the one and only @josh_wills ! We talked about everything from data infra at the early Slack days up to the LLM revolution!
🔥 EPISODE DROP: You might know this illustrious gentlemen by his glorious hat. 🤠 🛠 You might know him from his work on data science, data engineering, data infrastructure for companies like @SlackHQ , @cloudera , @Google. 🐦 You might even know him from tweets here 🤭
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🧙♂️ In a world where #LLMs & #PromptEngineering cast doubt on Data Scientist careers, a beacon of hope emerges: Traditional #FeatureEngineering.
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