Discover the fastest path to get machine learning models to production. The Big Book of MLOps will show you how data engineers, data scientists, and machine learning engineers can build and collaborate on a common platform, using powerful and open frameworks such as Delta Lake for data pipelines, MLflow for model management and Databricks Workflows for automation.
In this eBook, you’ll learn:
The essential components of an MLOps reference architecture
The key stakeholders to involve as you build and deploy machine learning applications
How to leverage the same platform for data and models and get to production faster
How to monitor data and models through the complete ML lifecycle with end-to-end lineage
Best practices to guide your MLOps planning and decision-making
A new data-centric approach to building robust MLOps practices
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