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MLOps with MLflow and Kubernetes

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A practical MLOps book covering experiment tracking, model registries, feature pipelines, CI/CD for ML, Kubernetes serving, monitoring, drift, governance, and safe model rollout.

Level: intermediateLanguage: EN EnglishRating: 0Reviews: 0

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Book contents

01Chapter 1: Why Machine Learning Needs Operations 02Chapter 2: Datasets, Features, Models, and Artifacts 03Chapter 3: Experiment Tracking with MLflow 04Chapter 4: Model Registries and Approval Workflows

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