DP-100 Dumps

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Microsoft DP-100 dumps - 100% Pass Guarantee!

Rating: 4.7

Vendor: Microsoft

Certifications: Role-based

Exam Name: Designing and Implementing a Data Science Solution on Azure

Exam Code: DP-100

Total Questions: 487 Q&As ( View Details)

Last Updated: Apr 14, 2024

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DP-100 Practice Questions and Answers Online

Questions 1


You are evaluating a Python NumPy array that contains six data points defined as follows:

data = [10, 20, 30, 40, 50, 60]

You must generate the following output by using the k-fold algorithm implantation in the Python Scikit-learn machine learning library:

train: [10 40 50 60], test: [20 30]train: [20 30 40 60], test: [10 50]train: [10 20 30 50], test: [40 60]

You need to implement a cross-validation to generate the output.

How should you complete the code segment? To answer, select the appropriate code segment in the dialog box in the answer area.

NOTE: Each correct selection is worth one point.

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Questions 2


You create an Azure Machine Learning workspace and set up a development environment. You plan to train a deep neural network (DNN) by using the Tensorflow framework and by using estimators to submit training scripts.

You must optimize computation speed for training runs.

You need to choose the appropriate estimator to use as well as the appropriate training compute target configuration.

Which values should you use? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

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Questions 3


You have an Azure Machine learning workspace. The workspace contains a dataset with data in a tabular form.

You plan to use the Azure Machine Learning SDK for Python vl to create a control script that will load the dataset into a pandas dataframe in preparation for model training The script will accept a parameter designating the dataset

You need to complete the script.

How should you complete the script? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

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Questions 4

You are a data scientist working for a hotel booking website company. You use the Azure Machine Learning service to train a model that identifies fraudulent transactions.

You must deploy the model as an Azure Machine Learning real-time web service using the Model.deploy method in the Azure Machine Learning SDK. The deployed web service must return real-time predictions of fraud based on transaction

data input.

You need to create the script that is specified as the entry_script parameter for the InferenceConfig class used to deploy the model.

What should the entry script do?

A. Register the model with appropriate tags and properties.

B. Create a Conda environment for the web service compute and install the necessary Python packages.

C. Load the model and use it to predict labels from input data.

D. Start a node on the inference cluster where the web service is deployed.

E. Specify the number of cores and the amount of memory required for the inference compute.

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Questions 5

You register a file dataset named csv_folder that references a folder. The folder includes multiple comma- separated values (CSV) files in an Azure storage blob container. You plan to use the following code to run a script that loads data from the file dataset. You create and instantiate the following variables:

You have the following code:

You need to pass the dataset to ensure that the script can read the files it references.

Which code segment should you insert to replace the code comment?

A. inputs=[file_dataset.as_named_input('training_files')],

B. inputs=[file_dataset.as_named_input('training_files').as_mount()],

C. inputs=[file_dataset.as_named_input('training_files').to_pandas_dataframe ()],

D. script_params={'--training_files': file_dataset},

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Success Stories

  • Nigeria
  • kumar from India
  • Apr 12, 2024
  • Rating: 4.6 / 5.0

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Microsoft DP-100 exam official information: As a candidate for this exam, you should have subject matter expertise in applying data science and machine learning to implement and run machine learning workloads on Azure.