Running and Monitoring Distributed ML with Ray and whylogs

Ray is an open-source project that allows users to parallelize Python processes and integrates with whylogs, a monitoring solution for machine learning models in production. Ray makes it easy to divide large datasets into smaller chunks and process them in parallel, generating whylogs profiles along the way. This enables users to monitor their ML models' performance and behavior in real-time. By using Ray pipelines and whylogs, users can easily integrate these tools into their workflows for data analysis and model monitoring.

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