Feast and Arize Supercharge Feature Management and Model Monitoring for MLOps

Feast and Arize AI have partnered to enhance the ML model lifecycle by empowering online/offline feature transformation and serving through Feast's feature store and detecting and resolving data inconsistencies through Arize's ML observability platform. The integration of a feature store and evaluation store can help improve productionization of features, mitigate data inconsistencies, and facilitate troubleshooting to resolve performance degradations in an end-to-end ML model lifecycle.

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