ML Model Updates
Adrià explains that the need for updating an ML model depends on the domain it's being used for. By collecting and labeling new data from users, the model can be retrained to improve accuracy and solve real cases effectively. Demetrios emphasizes the importance of understanding the KPIs and the overall objective of the model. Looking ahead, they discuss the rapid evolution of ML and the need for constant updates and adjustments in the coming years.In this clip
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ProductizeML: Assisting Your Team to Better Build ML Products // Adrià Romero // MLOps Meetup #47
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