Complete DP-100 Latest Exam Preparation & Leader in Qualification Exams & Newest Exam DP-100 Braindumps
Complete DP-100 Latest Exam Preparation & Leader in Qualification Exams & Newest Exam DP-100 Braindumps
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Microsoft DP-100 (Designing and Implementing a Data Science Solution on Azure) Certification Exam is a popular certification exam designed to test the skills and knowledge of data professionals in designing and implementing data science solutions on the Microsoft Azure platform. DP-100 exam is ideal for data scientists, data analysts, and other professionals who want to demonstrate their expertise in working with data on the Azure platform.
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Languages: English, Japanese, Chinese (Simplified), Korean
Retirement date: none
This exam measures your ability to accomplish the following technical tasks: manage Azure resources for machine learning; run experiments and train models; deploy and operationalize machine learning solutions; and implement responsible machine learning.
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Prep4away's Microsoft DP-100 questions are available in PDF format. Our Designing and Implementing a Data Science Solution on Azure (DP-100) PDF is embedded with questions relevant to the actual exam content only. Microsoft DP-100 PDF is printable and portable, so you can learn with ease and share it on multiple devices. You can use this Microsoft DP-100 PDF on your mobile and tablet anywhere, anytime, without the internet and installation process. Our qualified team of Designing and Implementing a Data Science Solution on Azure Professionals update Designing and Implementing a Data Science Solution on Azure (DP-100) study material to improve the quality and to match the changes in the syllabus and pattern shared by Microsoft.
Microsoft Designing and Implementing a Data Science Solution on Azure Sample Questions (Q46-Q51):
NEW QUESTION # 46
You have an Azure blob container that contains a set of TSV files. The Azure blob container is registered as a datastore for an Azure Machine Learning service workspace. Each TSV file uses the same data schema.
You plan to aggregate data for all of the TSV files together and then register the aggregated data as a dataset in an Azure Machine Learning workspace by using the Azure Machine Learning SDK for Python.
You run the following code.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.data.tabulardataset
NEW QUESTION # 47
You are determining if two sets of data are significantly different from one another by using Azure Machine Learning Studio.
Estimated values in one set of data may be more than or less than reference values in the other set of data. You must produce a distribution that has a constant Type I error as a function of the correlation.
You need to produce the distribution.
Which type of distribution should you produce?
- A. Unpaired t-test with a two tail option
- B. Paired t-test with a two-tail option
- C. Unpaired t-test with a one-tail option
- D. Paired t-test with a one-tail option
Answer: B
Explanation:
Explanation
Choose a one-tail or two-tail test. The default is a two-tailed test. This is the most common type of test, in which the expected distribution is symmetric around zero.
Example: Type I error of unpaired and paired two-sample t-tests as a function of the correlation. The simulated random numbers originate from a bivariate normal distribution with a variance of 1.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/test-hypothesis-using-t-test
https://en.wikipedia.org/wiki/Student%27s_t-test
NEW QUESTION # 48
You have a Jupyter Notebook that contains Python code that is used to train a model.
You must create a Python script for the production deployment. The solution must minimize code maintenance.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
- A. Remove all comments and functions from the Python script
- B. Save each function to a separate Python file
- C. Define a main() function in the Python script
- D. Refactor the Jupyter Notebook code into functions
Answer: C,D
Explanation:
Reference:
https://www.guru99.com/learn-python-main-function-with-examples-understand-main.html
https://towardsdatascience.com/from-jupyter-notebook-to-deployment-a-straightforward-example-
1838c203a437
NEW QUESTION # 49
You need to build a feature extraction strategy for the local models.
How should you complete the code segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
NEW QUESTION # 50
You create an Azure Machine learning workspace. The workspace contains a folder named src. The folder contains a Python script named script 1 .py.
You use the Azure Machine Learning Python SDK v2 to create a control script. You must use the control script to run script l.py as part of a training job.
You need to complete the section of script that defines the job parameters.
How should you complete the script? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
NEW QUESTION # 51
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