Deploying and Managing Models in Microsoft Azure Flashcards Preview

DP-100 - PS > Deploying and Managing Models in Microsoft Azure > Flashcards

Flashcards in Deploying and Managing Models in Microsoft Azure Deck (10)
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1

What is the top level resource for Azure Machine Learning?

Plan

Project

Workspace

Solution

Workspace

2

What are training runs you use to build your models?

Solutions

Sessions

Thoughts

Experiments

Experiments

3

What is the last step in an Azure Machine Learning cycle?

Repeat

Deploy

Monitor

Retrain

Repeat

4

What is the term for the change in model input data that leads to model performance degradation?

Function collapse

Data drift

Gradient merge

Model devolution

Data drift

5

What tool is used to track data drift?

Azure Functions

Azure Application Insights

Azure Container Instances

Azure Security Center

Azure Application Insights

6

Which tool can be used to integrate Azure Machine Learning with CI/CD?

Azure DevOps

Azure Container Instances

Azure App Service

Azure IoT Edge

Azure DevOps

7

What can trigger an Azure Machine Learning automated deployment?

Tensorflow Checkpoint

Git Checkin

Azure Function

Database Update

Git Checkin

8

What is the type of message used to monitor for data drift?

data_drift

model_data_collection

drift_detection

accuracy_monitor

model_data_collection

9

What is the statistical distance defined for one-dimensional numerical distribution?

energy_distance

wasserstein_distance

datadrift_contribution

datadrift_coefficient

wasserstein_distance / energy_distance

10

What is the statistical distance defined for one-dimensional numerical distribution?

datadrift_coefficient

datadrift_contribution

energy_distance

wasserstein_distance

wasserstein_distance / energy_distance