#67 Operationalizing Machine Learning with MLOps
DataFramed
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Intro
This chapter delves into the significance of operationalizing machine learning models in light of challenges posed by the COVID-19 pandemic. It highlights data drift, its effects on model performance, and introduces MLOps methodologies to help organizations enhance their data operations.
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Transcript
