MLOps and Machine Learning in Production
MLOps from theory to practice: training pipelines, model registry, feature store, A/B testing, model drift monitoring, CI/CD for ML, and infrastructure on Kubernetes and cloud.
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MLOpsML pipelinemodel registryfeature storeKubernetes
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