Instruction: Describe your strategies for scaling ML models efficiently to work with large volumes of data.
Context: This question explores the candidate's experience and strategies for scaling ML models to accommodate big data.
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The way I'd think about it is this: I scale by matching the approach to the bottleneck. Sometimes the issue is training throughput, sometimes feature engineering, sometimes storage and data movement, and sometimes labeling or evaluation. The right scaling strategy...