MLOps notes

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• logging
• metrics
• data-pipelines

• Data is changing (new type of data, the same data but a newser dataset)
• Model

• Monitor the quality of the model over time
• The standard tools measuring precision and recall in classification, accuracy, F-measure (F1)

• data quality
• model decay (due to changes in the data that are not used to re-train the model)
• locality (using the same model on a different set of data, eg. a different cluster of customers)

• Distributed learning