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[D] MLOps resources
What I mean is topics like handling hundreds of models and their updates, reusable CI/CD pipelines, batch and online architectures, integration with feature stores, jobs/queues for model scheduling, data drift, metrics monitoring, and alerts, and so on.
This would be for someone familiar with the major concepts, hands-on experience with MLflow, SageMaker, Azure ML services, Databricks and similar tools.
advanced alerts architectures books courses data design design systems drift feature integration intermediate jobs machinelearning mean metrics mlops monitoring pipelines queues resources scheduling systems topics updates