High Performance Feature Serving with Feast on AWS
apply(meetup) - Aug '21 - 10 minutes
In this lightning talk we will showcase how teams can deploy and productionize a feature store on AWS with Feast. We will demonstrate how users can train a machine learning model using historical features from Redshift, deploy the model into production on AWS, then serve fresh feature values to the model using a serverless feature serving stack with DynamoDB.
Willem Pienaar
Feast Committer and Tech Lead
Tecton
Willem Pienaar is a tech lead at Tecton, where he leads the Feast open source feature store. Willem created Feast while leading the Data Science Platform team at Gojek. His main focus areas are building data and ML platforms, allowing organizations to scale machine learning and drive decision making. In a previous life, Willem founded and sold a networking startup.
Request a Demo
Unfortunately, Tecton does not currently support these clouds. We’ll make sure to let you know when this changes!
However, we are currently looking to interview members of the machine learning community to learn more about current trends.
If you’d like to participate, please book a 30-min slot with us here and we’ll send you a $50 amazon gift card in appreciation for your time after the interview.
Interested in trying Tecton? Leave us your information below and we’ll be in touch.
Unfortunately, Tecton does not currently support these clouds. We’ll make sure to let you know when this changes!
However, we are currently looking to interview members of the machine learning community to learn more about current trends.
If you’d like to participate, please book a 30-min slot with us here and we’ll send you a $50 amazon gift card in appreciation for your time after the interview.
Interested in trying Tecton? Leave us your information below and we’ll be in touch.
Unfortunately, Tecton does not currently support these clouds. We’ll make sure to let you know when this changes!
However, we are currently looking to interview members of the machine learning community to learn more about current trends.
If you’d like to participate, please book a 30-min slot with us here and we’ll send you a $50 amazon gift card in appreciation for your time after the interview.
