MLOps: The rise of machine learning operations

AI

As hard as it is for data scientists to tag data and develop accurate machine learning models, managing models in production can be even more daunting. Recognising model drift, retraining models with updating data sets, improving performance, and maintaining the underlying technology platforms are all important data science practices. Without these disciplines, models can produce erroneous [&hellip

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August 15, 2020
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