📘 Free DP-100 Sample Questions
You have an Azure Synapse Analytics job that uses Scala. You need to view the status of the job.
What should you do?
A
From Synapse Studio, select the workspace. From Monitor, select SQL requests.
B
From Azure Monitor, run a Kusto query against the AzureDiagnostics table.
C
From Synapse Studio, select the workspace. From Monitor, select Apache Sparks applications.
D
From Azure Monitor, run a Kusto query against the SparkLoggingEvent_CL table.
Correct Answer:
C. From Synapse Studio, select the workspace. From Monitor, select Apache Sparks applications.
Explanation:
Use Synapse Studio to monitor your Apache Spark applications. To monitor running Apache Spark application Open Monitor, then select Apache Spark applications. To view the details about the Apache Spark applications that are running, select the submitting Apache Spark application and view the details. If the Apache Spark application is still running, you can monitor the progress.
Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/monitoring/apache-spark-applications
HOTSPOT -
Complete the sentence by selecting the correct option in the answer area.
Hot Area:
A
Correct Answer:
A.
Explanation:
Explanation:
A Deep Learning Virtual Machine is a pre-configured environment for deep learning using GPU instances.
You need to implement a Data Science Virtual Machine (DSVM) that supports the Caffe2 deep learning framework. Which of the following DSVM should you create?
A
Windows Server 2012 DSVM
B
Windows Server 2016 DSVM
C
Ubuntu 16.04 DSVM
D
CentOS 7.4 DSVM
Correct Answer:
C. Ubuntu 16.04 DSVM
Explanation:
Explanation:
Caffe2 is supported by Data Science Virtual Machine for Linux.
Microsoft offers Linux editions of the DSVM on Ubuntu 16.04 LTS and CentOS 7.4. However, only the DSVM on Ubuntu is preconfigured for Caffe2.
This question is included in a number of questions that depicts the identical set-up.However, every question has a distinctive result.Establish if the recommendation satisfies the requirements.You have been tasked with employing a machine learning model, which makes use of a PostgreSQL database and needs GPU processing, to forecast prices.You are preparing to create a virtual machine that has the necessary tools built into it.You need to make use of the correct virtual machine type.Recommendation: You make use of a Geo AI Data Science Virtual Machine (Geo-DSVM) Windows edition.Will the requirements be satisfied?
A
Yes
B
No
Correct Answer:
B. No
Explanation:
The Azure Geo AI Data Science VM (Geo-DSVM) delivers geospatial analytics capabilities from Microsoft's Data Science VM. Specifically, this VM extends the AI and data science toolkits in the Data Science VM by adding ESRI's market-leading ArcGIS Pro Geographic Information System.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/overview
This question is included in a number of questions that depicts the identical set-up.However, every question has a distinctive result.Establish if the recommendation satisfies the requirements.You have been tasked with employing a machine learning model, which makes use of a PostgreSQL database and needs GPU processing, to forecast prices.You are preparing to create a virtual machine that has the necessary tools built into it.You need to make use of the correct virtual machine type.Recommendation: You make use of a Deep Learning Virtual Machine (DLVM) Windows edition.Will the requirements be satisfied?
A
Yes
B
No
Correct Answer:
A. Yes
Explanation:
I will also stand with a Yes.A Deep Learning Virtual Machine (DLVM) is a pre-configured virtual machine image on Microsoft Azure that is optimized for training deep learning models and includes popular tools such as TensorFlow, PyTorch, and Caffe2.The DLVM Windows edition includes support for GPU processing, making it suitable for the task of running a machine learning model that requires GPU processing to forecast prices.Additionally, the DLVM can be configured to use PostgreSQL as the database, satisfying the requirement for a PostgreSQL database.Therefore, the recommendation to use a DLVM Windows edition will satisfy the requirements.
This question is included in a number of questions that depicts the identical set-up.However, every question has a distinctive result.Establish if the recommendation satisfies the requirements.You have been tasked with employing a machine learning model, which makes use of a PostgreSQL database and needs GPU processing, to forecast prices.You are preparing to create a virtual machine that has the necessary tools built into it.You need to make use of the correct virtual machine type.Recommendation: You make use of a Data Science Virtual Machine (DSVM) Windows edition.Will the requirements be satisfied?
A
Yes
B
No
Correct Answer:
A. Yes
Explanation:
In the DSVM, your training models can use deep learning algorithms on hardware that's based on graphics processing units (GPUs).PostgreSQL is available for the following operating systems: Linux (all recent distributions), 64-bit installers available for macOS (OS X) version 10.6 and newer.Windows (with installers available for 64-bit version; tested on latest versions and back to Windows 2012 R2.References:https://docs.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/overview
DRAG DROP -You have been tasked with moving data into Azure Blob Storage for the purpose of supporting Azure Machine Learning.Which of the following can be used to complete your task?Answer by dragging the correct options from the list to the answer area.Select and Place:
A
Correct Answer:
A.
Explanation:
You can move data to and from Azure Blob storage using different technologies:? Azure Storage-Explorer? AzCopy? Python? SSISReference:https://docs.microsoft.com/en-us/azure/machine-learning/team-data-science-process/move-azure-blob " target="_blank" style="word-break: break-all;">
HOTSPOT -Complete the sentence by selecting the correct option in the answer area.Hot Area:
A
Correct Answer:
A.
Explanation:
Use the Convert to ARFF module in Azure Machine Learning Studio to convert datasets and results in Azure Machine Learning to the attribute-relation file format used by the Weka toolset. This format is known as ARFF.The ARFF data specification for Weka supports multiple machine learning tasks, including data preprocessing, classification, and feature selection.In this format, data is organized by entities and their attributes and is contained in a single text file.Reference:https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/convert-to-arff " target="_blank" style="word-break: break-all;">
You have been tasked with designing a deep learning model, which accommodates the most recent edition of Python, to recognize language.You have to include a suitable deep learning framework in the Data Science Virtual Machine (DSVM).Which of the following actions should you take?
A
You should consider including Rattle.
B
You should consider including TensorFlow.
C
You should consider including Theano.
D
You should consider including Chainer.
Correct Answer:
B. You should consider including TensorFlow.
Explanation:
Reference:https://www.infoworld.com/article/3278008/what-is-tensorflow-the-machine-learning-library-explained.html " target="_blank" style="word-break: break-all;">
This question is included in a number of questions that depict the identical set-up.However, every question has a distinctive result.Establish if the recommendation satisfies the requirements.You have been tasked with evaluating your model on a partial data sample via k-fold cross-validation.You have already configured a k parameter as the number of splits.You now have to configure the k parameter for the cross-validation with the usual value choice.Recommendation: You configure the use of the value k=3.Will the requirements be satisfied?
A
Yes
B
No
Correct Answer:
B. No
Explanation:
Usual choice is the key word here, and the usual choices are k=5 or k=10.So, the answer is B.You can use as many splits as you want; it all depends on the data.Train/test/validate is basically 3 splits that are just swapped around. k=3 is perfectly fine.Reference:https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/cross-validate-model
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