Data Labeling & Annotation Pipelines

Data Labeling & Annotation Pipelines#

Most ML failures aren't caused by the wrong model architecture. They're caused by bad labels. A 2022 analysis of production ML incidents at large tech companies found that data quality issues, including label noise and inconsistency, were responsible for more model degradation events than any algorithmic choice. Your interviewer at Google or Meta almost certainly knows this. The question is whether you do...