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Hey, I Hope This Is The Right Place To Ask. We'Re A Small Data Science Team That Wants To Log Everything About Our Ml Models. Looking Around On The Internet, Mostly Mlflow Is Being Recommended, But Occasionally The Name Trains Pop-Ups.
According To You,
Thank you for your impression! I get a bit more of a Airflow feel for running many tasks to train models with different parameters, which is a good thing.
I'm still skimming through the documents, but TRAINS documentation on how models are stored is a bit vague to me. The https://allegro.ai/docs/examples/examples_models/ only quickly mentions that you can set an output location. Which is a bit shallow compared with the https://mlflow.org/docs/latest/model-registry.html . Any good resource that talks about TRAINS models management?
It seems that with https://github.com/mlflow/mlflow/#saving-and-serving-models .
I cannot find anything about serving models in TRAINS?
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4 years ago
one year ago