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Detecting Drift in Deep Learning: A Methodology Primer

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2 Published in 2022 at "IT Professional"

DOI: 10.1109/mitp.2022.3191318

Abstract: Supervised machine learning models are trained on historical data to learn a static mapping between their input and output variables. However, when they are deployed on continuously streamed data, whose nature is likely to change… read more here.

Keywords: methodology; drift deep; learning methodology; detecting drift ... See more keywords