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Artificial intelligence - Data quality for analytics and machine learning (ML) - Part 4: Data quality process framework
This document establishes general common organizational approaches, regardless of the type, size or nature of the applying organization, to ensure data quality for training and evaluation in analytics and machine learning (ML).
It includes guidance on the data quality process for:
This document is applicable to training and evaluation data that come from different sources, including data acquisition and data composition, data preparation, data labelling, evaluation and data use.
This document does not define specific services, platforms or tools.
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