Episode Details
Back to EpisodesFeature stores: the missing infrastructure layer in your ML data supply chain
Episode 35
Published 3 months ago
Description
Most ML failures are not model failures. They are data supply chain failures, and feature stores are the architectural response that serious ML organizations have adopted to fix them.
Go deeper, free lessons
- MLOps: monitoring, retraining & drift
- Models in production: drift, monitoring & MLOps
- Data lineage & metadata management: knowing where your data was born
- The lakehouse: unifying analytics & ML
- AI risk & the EU AI Act
Full transcript: https://www.mba-training.com/en/podcast/data/feature-stores-ml-data-supply-chain
The article: https://www.mba-training.com/en/blog/feature-stores-ml-data-supply-chain
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