ExamTopics Logo
Mail Us[email protected]
Menu
Microsoft Discussions
exam questions

Exam DP-100 All Questions

View all questions & answers for the DP-100 exam
Go to Exam

Exam DP-100 topic 3 question 102 discussion

Actual exam question from Microsoft's DP-100
Question #: 102
Topic #: 3
[All DP-100 Questions]

HOTSPOT -
You create an Azure Databricks workspace and a linked Azure Machine Learning workspace.
You have the following Python code segment in the Azure Machine Learning workspace: import mlflow import mlflow.azureml import azureml.mlflow import azureml.core from azureml.core import Workspace subscription_id = 'subscription_id' resourse_group = 'resource_group_name' workspace_name = 'workspace_name' ws = Workspace.get(name=workspace_name, subscription_id=subscription_id, resource_group=resource_group) experimentName = "/Users/{user_name}/{experiment_folder}/{experiment_name}" mlflow.set_experiment(experimentName) uri = ws.get_mlflow_tracking_uri() mlflow.set_tracking_uri(uri)
Instructions: For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Hot Area:

Show Suggested Answer Hide Answer
Suggested Answer:
by TEO96B at Dec. 29, 2021, 11:09 a.m.

Comments

Chosen Answer:
This is a voting comment (?). It is better to Upvote an existing comment if you don't have anything to add.
Switch to a voting comment New
Submit Cancel
TEO96B
Highly Voted 2 years, 10 months ago
It should be NYN, shouldn't it?
upvoted 27 times
Lion007
10 months ago
I agree, it should be NYN Box 1: No - This method does not create a new resource group or Azure Machine Learning workspace; it simply accesses an existing one​​. Box 2: Yes - The get_mlflow_tracking_uri() method retrieves the tracking URI of the Azure Machine Learning workspace, and set_tracking_uri() directs MLflow to send its tracking data to this URI​​. Box 3: No - The Python code provided does not include any code that specifically sets up tracking for the "epoch loss" metric. While MLflow is capable of tracking such a metric, it would require explicit calls to mlflow.log_metric() within the training loop, which are not present in the provided code segment​​.
upvoted 2 times
...
[Removed]
2 years, 10 months ago
I agree
upvoted 3 times
...
...
vish9
Highly Voted 1 year, 5 months ago
https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-mlflow-azure-databricks?view=azureml-api-2&tabs=cli%2Cmlflow The above link states: Azure Databricks can be configured to track experiments using MLflow in two ways: Track in both Azure Databricks workspace and Azure Machine Learning workspace (dual-tracking) Track exclusively on Azure Machine Learning By default, dual-tracking is configured for you when you linked your Azure Databricks workspace. Hence It should be NNN
upvoted 6 times
Matt2000
9 months ago
I followed your link. The code specified in this question occurs in the section 'Tracking exclusively on Azure Machine Learning workspace'. I suppose that the second question should be 'Yes'.
upvoted 1 times
...
...
Secure_Defense
Most Recent 2 months, 3 weeks ago
Should be NNN. For second box: NO "You can configure Azure Databricks to track experiments using MLflow in two ways: - Track in both Azure Databricks workspace and Azure Machine Learning workspace (dual-tracking) - Track exclusively on Azure Machine Learning By default, when you link your Azure Databricks workspace, dual-tracking is configured for you. Linking your Azure Databricks workspace to your Azure Machine Learning workspace enables you to track your experiment data in the Azure Machine Learning workspace and Azure Databricks workspace at the same time. This configuration is called Dual-tracking. https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-mlflow-azure-databricks?view=azureml-api-2&tabs=cli%2Cmlflow#track-azure-databricks-runs-with-mlflow For third box: NO The code doesn't provide any segment to track metrics.
upvoted 1 times
...
SunilB
1 year, 7 months ago
Should be NNN After you link your Azure Databricks workspace with your Azure Machine Learning workspace, MLflow Tracking is automatically set to be tracked in all of the following places: The linked Azure Machine Learning workspace. Your original ADB workspace.
upvoted 5 times
...
vishal_aiml164
1 year, 9 months ago
It should be N,N,N as i see that 1) we will not create ws 2) in latest Azure ML and Azure DB we can monitor the logs 3) there is no code for logging in mlflow
upvoted 6 times
vishal_aiml164
1 year, 9 months ago
FYR : https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-mlflow-azure-databricks?tabs=cli%2Cmlflow
upvoted 1 times
...
...
ning
2 years, 4 months ago
I do not fully understand this question, in the statements, there are no statement for logging, in order mlflow to log, one the following needs to be called: mlflow.log_param("alpha", alpha) mlflow.log_metric('mse', 1.23) mlflow.log_artifact("actuals_vs_predictions.png") mlflow.log_model(lr, "linear Model") if no statement to log, how would anything to be traced or logged???
upvoted 1 times
...
AjoseO
2 years, 7 months ago
On 03 March 2022 The 3rd question was different
upvoted 4 times
...
Community vote distribution
A (35%)
C (25%)
B (20%)
Other
Most Voted
A voting comment increases the vote count for the chosen answer by one.

Upvoting a comment with a selected answer will also increase the vote count towards that answer by one. So if you see a comment that you already agree with, you can upvote it instead of posting a new comment.

SaveCancel
exam
Someone Bought Contributor Access for:
SY0-701
London, 1 minute ago