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NEW QUESTION: 1
You create a multi-class image classification deep learning model that uses the PyTorch deep learning framework.
You must configure Azure Machine Learning Hyperdrive to optimize the hyperparameters for the classification model.
You need to define a primary metric to determine the hyperparameter values that result in the model with the best accuracy score.
Which three actions must you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A. Add code to the bird_classifier_train.py script to calculate the validation loss of the model and log it as a float value with the key loss.
B. Set the primary_metric_name of the estimator used to run the bird_classifier_train.py script to loss.
C. Add code to the bird_classifier_train.py script to calculate the validation accuracy of the model and log it as a float value with the key accuracy.
D. Set the primary_metric_goal of the estimator used to run the bird_classifier_train.py script to minimize.
E. Set the primary_metric_goal of the estimator used to run the bird_classifier_train.py script to maximize.
F. Set the primary_metric_name of the estimator used to run the bird_classifier_train.py script to accuracy.
Answer: C,E,F
Explanation:
AD:
primary_metric_name="accuracy",
primary_metric_goal=PrimaryMetricGoal.MAXIMIZE
Optimize the runs to maximize "accuracy". Make sure to log this value in your training script.
Note:
primary_metric_name: The name of the primary metric to optimize. The name of the primary metric needs to exactly match the name of the metric logged by the training script.
primary_metric_goal: It can be either PrimaryMetricGoal.MAXIMIZE or PrimaryMetricGoal.MINIMIZE and determines whether the primary metric will be maximized or minimized when evaluating the runs.
F: The training script calculates the val_accuracy and logs it as "accuracy", which is used as the primary metric.

NEW QUESTION: 2
You have a data pipeline with a Cloud Dataflow job that aggregates and writes time series metrics to Cloud Bigtable. This data feeds a dashboard used by thousands of users across the organization. You need to support additional concurrent users and reduce the amount of time required to write the data.
Which two actions should you take? (Choose two.)
A. Modify your Cloud Dataflow pipeline to use the CoGroupByKey transform before writing to Cloud Bigtable
B. Increase the maximum number of Cloud Dataflow workers by setting maxNumWorkers in PipelineOptions
C. Increase the number of nodes in the Cloud Bigtable cluster
D. Configure your Cloud Dataflow pipeline to use local execution
E. Modify your Cloud Dataflow pipeline to use the Flatten transform before writing to Cloud Bigtable
Answer: A,E
Explanation:
A - Local execution is useful for testing and debugging purposes, especially if your pipeline can use smaller in-memory datasets.
B- https://cloud.google.com/dataflow/docs/guides/specifying-exec-params C- increases both read and write performance D- Flatten merges multiple PCollection objects into a single logical PCollection.
E- Consider using CoGroupByKey if you have multiple data sets that provide information about related things .

NEW QUESTION: 3
Sie konfigurieren eine Richtlinie für den bedingten Zugriff. Die Einstellungen für Standorte werden wie in der Ausstellung Standorte gezeigt konfiguriert. (Klicken Sie auf die Registerkarte Standorte.)

Die Benutzer- und Gruppeneinstellungen werden wie in der Ausstellung Benutzer und Gruppen gezeigt konfiguriert. (Klicken Sie auf die Registerkarte Benutzer und Gruppen.)

Mitglieder der Sicherheitslesergruppe melden an, dass sie sich auf ihrem Gerät nicht bei Microsoft Active Directory (Azure AD) anmelden können, während sie sich im Büro befinden.
Sie müssen sicherstellen, dass sich die Mitglieder der Sicherheitslesergruppe auf ihrem Gerät bei Azure AD anmelden können, während sie sich im Büro befinden. Die Lösung muss das Prinzip des geringsten Privilegs anwenden.
Was tun?
A. Erstellen Sie im Azure Active Directory-Verwaltungscenter ein benutzerdefiniertes Steuerelement.
B. Erstellen Sie im Azure Active Directory-Verwaltungscenter einen benannten Speicherort.
C. Konfigurieren Sie in der Richtlinie für den bedingten Zugriff den Gerätestatus.
D. Erstellen Sie im Intune Admin Center eine Richtlinie zur Gerätekompatibilität.
Answer: B
Explanation:
Explanation
References:
https://docs.microsoft.com/en-us/azure/active-directory/conditional-access/location-condition

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