DP-100 VALID EXAM FEE | DP-100 CERTIFIED QUESTIONS

DP-100 Valid Exam Fee | DP-100 Certified Questions

DP-100 Valid Exam Fee | DP-100 Certified Questions

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Tags: DP-100 Valid Exam Fee, DP-100 Certified Questions, DP-100 Pdf Format, DP-100 Upgrade Dumps, DP-100 Sample Questions Answers

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Obtaining the DP-100 certification demonstrates the candidate's proficiency in designing and implementing data science solutions on Azure. Designing and Implementing a Data Science Solution on Azure certification provides a competitive edge in the job market and opens up various career opportunities for the candidate. The DP-100 certification is also a prerequisite for other advanced Azure-based data science certifications, such as the DP-200 (Implementing an Azure Data Solution) and DP-201 (Designing an Azure Data Solution) certifications.

Microsoft DP-100 is a certification exam that focuses on designing and implementing data science solutions on Azure. DP-100 exam validates the candidate's knowledge and skills in using Azure technologies to build and deploy machine learning models, data pipelines, and data analysis solutions. The DP-100 Certification is designed for data scientists, data engineers, and other professionals who work with data and want to demonstrate their expertise in Azure-based data science solutions.

Microsoft DP-100 exam is designed for data scientists who want to demonstrate their ability to design and implement data science solutions on Microsoft Azure. DP-100 exam is an important step towards earning the Microsoft Certified: Azure Data Scientist Associate certification. It covers a range of topics including data exploration, data preparation, modeling, and deployment. Passing DP-100 exam requires a deep understanding of Azure services and tools, as well as strong data science skills.

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Microsoft Designing and Implementing a Data Science Solution on Azure Sample Questions (Q72-Q77):

NEW QUESTION # 72
You are developing a deep learning model by using TensorFlow. You plan to run the model training workload on an Azure Machine Learning Compute Instance.
You must use CUDA-based model training.
You need to provision the Compute Instance.
Which two virtual machines sizes can you use? To answer, select the appropriate virtual machine sizes in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://www.infoworld.com/article/3299703/what-is-cuda-parallel-programming-for-gpus.html


NEW QUESTION # 73
You create an experiment in Azure Machine Learning Studio. You add a training dataset that contains 10,000 rows. The first 9,000 rows represent class 0 (90 percent).
The remaining 1,000 rows represent class 1 (10 percent).
The training set is imbalances between two classes. You must increase the number of training examples for class 1 to 4,000 by using 5 data rows. You add the Synthetic Minority Oversampling Technique (SMOTE) module to the experiment.
You need to configure the module.
Which values should you use? To answer, select the appropriate options in the dialog box in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/smote


NEW QUESTION # 74
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
An IT department creates the following Azure resource groups and resources:

The IT department creates an Azure Kubernetes Service (AKS)-based inference compute target named aks-cluster in the Azure Machine Learning workspace.
You have a Microsoft Surface Book computer with a GPU. Python 3.6 and Visual Studio Code are installed.
You need to run a script that trains a deep neural network (DNN) model and logs the loss and accuracy metrics.
Solution: Install the Azure ML SDK on the Surface Book. Run Python code to connect to the workspace and then run the training script as an experiment on local compute.

  • A. Yes
  • B. No

Answer: B

Explanation:
Need to attach the mlvm virtual machine as a compute target in the Azure Machine Learning workspace.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-compute-target


NEW QUESTION # 75
You use the following code to run a script as an experiment in Azure Machine Learning:

You must identify the output files that are generated by the experiment run.
You need to add code to retrieve the output file names.
Which code segment should you add to the script?

  • A. files = run.get_details_with_logs()
  • B. files = run.get_details()
  • C. files= run.get_file_names()
  • D. files = run.get_properties()
  • E. files = run.get_metrics()

Answer: C

Explanation:
Explanation
You can list all of the files that are associated with this run record by called run.get_file_names() Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-track-experiments


NEW QUESTION # 76
You manage an Azure Machine Learning workspace named Workspace1 and an Azure Blob Storage accessed by using the URL https://storage1.blob.core.wmdows.net/data1.
You plan to create an Azure Blob datastore in Workspace1. The datastore must target the Blob Storage by using Azure Machine Learning Python SDK v2. Access authorization to the datastore must be limited to a specific amount of time.
You need to select the parameters of the Azure Blob Datastore class that will point to the target datastore and authorize access to it.
Which parameters should you use? To answer, select the appropriate options in the answer area NOTE: Each correct selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 77
......

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