Which property should you set?

You use the Azure Machine Learning service to create a tabular dataset named training.data. You plan to use this dataset in a training script.

You create a variable that references the dataset using the following code:

training_ds = workspace.datasets.get("training_data")

You define an estimator to run the script.

You need to set the correct property of the estimator to ensure that your script can access the training.data dataset

Which property should you set?
A . inputs = [training_ds.as_named_input(‘training_ds’)]
B . script_params = {"–training_ds":training_ds}
C . environment_definition = {"training_data":training_ds}
D . source_directory = training_ds

View Answer

Answer: A

Explanation:

Example:

# Get the training dataset

diabetes_ds = ws.datasets.get("Diabetes Dataset")

# Create an estimator that uses the remote compute

hyper_estimator = SKLearn(source_directory=experiment_folder,

inputs=[diabetes_ds.as_named_input(‘diabetes’)], # Pass the dataset as an input

compute_target = cpu_cluster,

conda_packages=[‘pandas’,’ipykernel’,’matplotlib’],

pip_packages=[‘azureml-sdk’,’argparse’,’pyarrow’],

entry_script=’diabetes_training.py’)

Explanation:

Reference: https://notebooks.azure.com/GraemeMalcolm/projects/azureml-primers/html/04%20-%20Optimizing%20Model%20Training.ipynb