This is a guest blog from software engineers Amog Kamsetty and Archit Kulkarni of Anyscale and contributors to Ray.io In this blog post, we’re announcing two new integrations with Ray and MLflow: Ray Tune+MLflow Tracking and Ray Serve+MLflow Models, which together make it much easier to build machine learning (ML) models and take them to…

The post Ray & MLflow: Taking Distributed Machine Learning Applications to Production appeared first on Databricks.

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