Join us to learn how performance at any scale is impacted by high availability infrastructures, and how those capabilities impact the value that is generated from the use of machine learning.

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Join us to learn how a feature store, with its multiple data sources and diversity of connectors, streaming data, and online data sets, allows teams to work together, share information, and complement each other's work.

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The modern data team consists of Data Engineers, Data Scientists, Machine Learning Engineers, and Business Analysts, but effective collaboration is challenging. In this talk we will show how a centralized data platform helps solve these issues.

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Learn how to install and configure Hopsworks on your local machines, and how to connect to the Hopsworks Feature Store.

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Learn how to build and operate search and recommendation systems on Hopsworks, with support for the most important pieces of infrastructure.

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Learn how to develop and deploy online models at ease for the open-source KServe and Hopsworks platforms without extensive MLOPs experience.

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A live walk through on how to work with features, both offline and online. We will have a live coding demo on how to get started with Hopsworks, create features and push them to the Hopsworks Feature Store.

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