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ML Feature Store Basics

Serve consistent ML features

A feature store standardizes feature definitions, computes them in batch/stream, and serves them consistently for training and online inference with lineage and quality monitoring.

Define Once

Centralize feature definitions with owners and metadata.

Materialize

Compute in batch/stream; serve online with low latency.

Validate

Monitor freshness, quality, and training/serving skew.

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