100% PASS 2025 TRUSTABLE DP-100: RELIABLE DESIGNING AND IMPLEMENTING A DATA SCIENCE SOLUTION ON AZURE EXAM CRAM

100% Pass 2025 Trustable DP-100: Reliable Designing and Implementing a Data Science Solution on Azure Exam Cram

100% Pass 2025 Trustable DP-100: Reliable Designing and Implementing a Data Science Solution on Azure Exam Cram

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The DP-100 Exam is a valuable certification for data scientists who work with Azure, as it demonstrates their proficiency in designing and implementing data science solutions on this platform. Designing and Implementing a Data Science Solution on Azure certification can help data scientists advance their careers and increase their earning potential.

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Microsoft Designing and Implementing a Data Science Solution on Azure Sample Questions (Q90-Q95):

NEW QUESTION # 90
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.
You are creating a new experiment in Azure Machine Learning Studio.
One class has a much smaller number of observations than the other classes in the training set.
You need to select an appropriate data sampling strategy to compensate for the class imbalance.
Solution: You use the Stratified split for the sampling mode.
Does the solution meet the goal?

  • A. No
  • B. Yes

Answer: A

Explanation:
Instead use the Synthetic Minority Oversampling Technique (SMOTE) sampling mode.
Note: SMOTE is used to increase the number of underepresented cases in a dataset used for machine learning. SMOTE is a better way of increasing the number of rare cases than simply duplicating existing cases.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/smote


NEW QUESTION # 91
You manage an Azure Machine Learning workspace. You create an experiment named experiment1 by using the Azure Machine Learning Python SDK v2 and MLflow. You are reviewing the results of experiment1 by using the following code segment:

For each of the following statements, Select Yes if the statement is true Otherwise, select No.

Answer:

Explanation:

Explanation:


NEW QUESTION # 92
You manage an Azure Machine Learning workspace named workspaces
You plan to create a registry named registry01 with the help of the following registry.yml (line numbers are used for reference only):

You need to use Azure Machine Learning Python SDK v2 with Python 3.10 in a notebook to interact with workspace1.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Answer:

Explanation:

Explanation:


NEW QUESTION # 93
You use Azure Machine Learning studio to analyze a dataset containing a decimal column named column1. You need to verity that the column1 values are normally distributed.
Which static should you use?

  • A. Profile
  • B. Type
  • C. Max
  • D. Mean

Answer: A


NEW QUESTION # 94
You are implementing hyperparameter tuning for a model training from a notebook. The notebook is in an Azure Machine Learning workspace.
You must configure a grid sampling method over the search space for the num_hidden_layers and batch_size hyperparameters.
You need to identify the hyperparameters for the grid sampling.
Which hyperparameter sampling approach should you use?

  • A. choice
  • B. normal
  • C. uniform
  • D. qlognormal

Answer: A

Explanation:
https://learn.microsoft.com/en-us/python/api/azureml-train-
core/azureml.train.hyperdrive.gridparametersampling?view=azure-ml-py


NEW QUESTION # 95
......

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