ML Lineage

The required information in MLOps pipelines often needs to be better connected and address more diverse concerns, even though the emerging MLOps practices streamline the development and operations of ML-based artifacts and systems. The concept of ML lineage is a framework to holistically capture and connect the required information about ML model development and operations, thus supporting and implementing, e.g., regulatory compliance and governance.

ML lineage is an information model that fundamentally distinguishes between the model and prediction levels, conceptually encompassing separate yet interconnected core domains for the project, experiment, model, and prediction. ML lineage easily integrates with existing MLOps pipelines, workflows, and tools, often requiring minimal additional effort, such as generating model cards or integrating with existing pipelines.

ML lineage is widely applicable, and as a framework, it can be customized to a use case.

ML engineers, especially regulated or high-risk use cases.

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