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I’m no ML expert so take what I say with a grain of salt.

Two resources that might be useful are AWS’ SageMaker documentation and the Machine Learning Engineering book by Andriy Burkov. This book doesn’t really go into detail on logging though. One way to evaluate a model is to run a SageMaker processing job that saves the performance metrics in a json file in S3 somewhere. More info on processing jobs: https://docs.aws.amazon.com/sagemaker/latest/dg/processing-j... . AWS has various services for logging which you can look into. This will mostly apply to orgs using AWS, but it might give a sense of how things can be done more generally.