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Practitioners Guide To MLOps

Whitepaper

Published January 2022
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This whitepaper provides an overview of the MLOps life cycle, MLOps processes, and capabilities and why they’re important for successful adoption of ML-based systems. It also deep dives into concrete details of running a continuous training pipeline, deploying a model, and monitoring predictive performance of ML models

In this report, you will learn:

  • The MLOps life cycle and important processes and capabilities for successful ML-based systems
  • Orchestrating and automating the execution of continuous training pipelines
  • Model deployment and prediction serving
  • Dataset and feature management
  • Model management and governance