MLOps notes

• 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