HOTSPOT
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You manage an Azure Machine Learning workspace. You submit a training job with the Azure Machine Learning Python SDK v2. You must use MLflow to log metrics, model parameters, and model artifacts automatically when training a model.
You start by writing the following code segment:
import mlflow
mlflow.autolog(log_models=False, exclusive=True)
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
https://mlflow.org/docs/latest/python_api/mlflow.html#mlflow.autolog No, No, No
Correct! No, No, No From your link https://mlflow.org/docs/latest/python_api/mlflow.html#mlflow.autolog --> log_models – If True, trained models are logged as MLflow model artifacts. If False, trained models are not logged. Input examples and model signatures, which are attributes of MLflow models, are also omitted when log_models is False. --> exclusive – If True, autologged content is not logged to user-created fluent runs. If False, autologged content is logged to the active fluent run, which may be user-created.
Y,N,Y https://learn.microsoft.com/en-us/azure/machine-learning/how-to-log-view-metrics?view=azureml-api-2&tabs=interactive#logging-images When you use the mlflow.autolog function, it enables automatic logging of metrics, parameters, and artifacts to a user-created run in MLflow. This means that the autologged content will be logged to a run that was created by the user, rather than being logged to a system-generated run. SaM
No No Yes, Based n below 2 link
log_models – If True, trained models are logged as MLflow model artifacts. If False, trained models are not logged. Input examples and model signatures, which are attributes of MLflow models, are also omitted when log_models is False. exclusive – If True, autologged content is not logged to user-created fluent runs. If False, autologged content is logged to the active fluent run, which may be user-created https://mlflow.org/docs/latest/python_api/mlflow.html#mlflow.autolog
So N N N
The exclusive=True parameter ensures that only MLflow logging will be used, preventing conflicts with other loggers that might be active. this means that the first one should be YES