Feature Stores: Core Concepts, Practices and Workshop (with Feast and Kubeflow)

Feature stores have emerged as critical technologies in a modern ML stack. They aim to solve the full set of data management problems encountered when building and operationalizing data for ML applications.
In this webinar we will dive into the design and concepts of feature stores, where feature stores fit in the ML stack, and the problems they solve. We will then provide a hands on walk through in deploying an end-to-end ML system that leverages a Feast as its feature store, and Kubeflow as the ML platform.
Speaker: Willem Pienaar (Tecton)
website: www.aicamp.ai/...
Resources: tinyurl.com/feast-aicamp

[@arindamadak6832]

can I get a demo installation of feast on my personal machine or it must be on AZURE??

[@nguyenhuycuong.freddie]

Hi all, I have a question: "Could feature store be used for unstructured data such as images and audios ?".

[@miguelalba2106]

I think in those cases you save the file name or path to the image/audio as one of the features