Features are essential to ML models. Therefore, a good feature infrastructure is important to any organization that wants to use ML properly in production. Feast is a great tool for building up your feature infrastructure. However, using Feast in production may need customization of your tech stack, extension for advanced use cases, and improvement of reliability and observability. In this talk, we will share the lessons learned from how Robinhood built a feature store from Feast.
Yuyang (Rand) Xie
Senior Machine Learning Engineer
Robinhood
Rand is a Senior Machine Learning Engineer at Robinhood, focusing on ML serving stack including model serving and feature store. Before Robinhood, Rand worked at Google and was one of the founding engineers of Vertex AI's Feature Store product.
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.