Azure Data Scientists Associate Practice Exam

Which method is NOT suitable for training a model in Azure Machine Learning?

1. Experiment.submit()

2. Run.get.register()

3. Model.register()

4. Model.download()

The correct answer is: Run.get.register()

The method that is not suitable for training a model in Azure Machine Learning is the ability to register a model. Registration is a post-training step that allows you to save (register) your trained model to the Azure Machine Learning workspace, but it does not involve the training process itself. The other options are directly related to the workflows involved in training models. The method used to submit an experiment to run a training job is essential for starting the training process, while getting a run's properties or results is critical for assessing how the training went. Downloading a model may also occur after training for deployment or inference purposes. In contrast, registering a model is simply an organizational step, ensuring that a trained model version is properly cataloged and available for future use in predictions, retraining, or sharing. Understanding these distinctions is important, as effective model management in Azure Machine Learning requires knowing which functions are tied to training processes and which are related to the management of models after they have already been trained.