Understanding Data Lineage in H2O | Tracking Data for AI Models

Описание: Learn how data lineage in the H2O platform ensures transparency, traceability, and efficiency in AI model development. Feature Store and Driverless AI provide seamless tracking of data from feature creation to model deployment.

Key insights:
✅ Collaborate on feature sets with version control
✅ Track changes and dependencies in derived feature sets
✅ Automatically document model data for full transparency
✅ Trace training data back to experiments and model versions

By maintaining a clear data lineage, organizations can optimize their AI workflows, ensure reproducibility, and build more reliable models.

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