Liam Roberts Liam Roberts

0 Course Enrolled • 0 Course Completed

Biography

Designing and Implementing a Data Science Solution on Azure valid practice questions & DP-100 exam pdf torrent & Designing and Implementing a Data Science Solution on Azure latest study dumps

DOWNLOAD the newest CertkingdomPDF DP-100 PDF dumps from Cloud Storage for free: https://drive.google.com/open?id=1WDz476tlwYF1ezvRSwojGh7-daEE6eM9

The Designing and Implementing a Data Science Solution on Azure (DP-100) exam questions are the real, valid, and updated DP-100 Exam Questions that are specifically designed for quick and complete DP-100 exam preparation. With CertkingdomPDF Designing and Implementing a Data Science Solution on Azure (DP-100) practice test questions you can start Microsoft DP-100 exam preparation immediately.

The DP-100 Certification Exam is a great way to demonstrate your skills and knowledge in designing and implementing data science solutions on Azure. Designing and Implementing a Data Science Solution on Azure certification is recognized worldwide and is highly valued by employers, making it an excellent investment for your career. Additionally, it can help you differentiate yourself from other professionals in the competitive job market and increase your earning potential.

>> DP-100 Test Testking <<

Download DP-100 Free Dumps & Exam DP-100 Overview

Our DP-100 exam materials allows you to have a 98% to 100% pass rate; allows you takes only 20 to 30 hours to practice before you take the exam; provide you with 24 free online customer service; provide professional personnel remote assistance; give you full refund if you fail to pass the DP-100 Exam. Our DP-100 real test serve you with the greatest sincerity. Face to such an excellent product which has so much advantages, do you fall in love with our DP-100 study materials now? If your answer is yes, then come and buy our DP-100 exam questions now.

Microsoft DP-100 certification exam is a comprehensive assessment of the candidate's knowledge and expertise in the field of data science. DP-100 exam covers a wide range of topics, including data exploration and preparation, modeling, feature engineering, training and tuning models, and deploying and managing models in Microsoft Azure. DP-100 Exam is designed to test the candidate's ability to design and implement data science solutions using Microsoft Azure data services, including Azure Machine Learning, Azure Databricks, and Azure HDInsight.

Microsoft Designing and Implementing a Data Science Solution on Azure Sample Questions (Q462-Q467):

NEW QUESTION # 462
You create an Azure Machine Learning pipeline named pipeline 1 with two steps that contain Python scnpts. Data processed by the first step is passed to the second step.
You must update the content of the downstream data source of pipeline 1 and run the pipeline again.
You need to ensure the new run of pipeline 1 fully processes the updated content.
Solution: Change the value of the compute.target parameter of the PythonScriptStep object in the two steps.
Does the solution meet the goal'

A. Yes
B. No

Answer: B

NEW QUESTION # 463
You need to configure the Feature Based Feature Selection module based on the experiment requirements and datasets.
How should you configure the module properties? To answer, select the appropriate options in the dialog box in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation

Box 1: Mutual Information.
The mutual information score is particularly useful in feature selection because it maximizes the mutual information between the joint distribution and target variables in datasets with many dimensions.
Box 2: MedianValue
MedianValue is the feature column, , it is the predictor of the dataset.
Scenario: The MedianValue and AvgRoomsinHouse columns both hold data in numeric format. You need to select a feature selection algorithm to analyze the relationship between the two columns in more detail.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/filter-based-feature-selection

NEW QUESTION # 464
You register a model in an Azure Machine Learning workspace by running the following code:

You are creating a scoring script to use in a real-time service for the model.
You need to write code in the scoring script to set the path of the registered model so that it can be loaded by the service. You include the necessary import statements.
Which code segment should you use?

A. path = ws.models('loan_model')
B. path = 'outputs/model.pkl'
C. path = 'model.pkl'
D. path = Model.get_model_path('loan_model')

Answer: D

NEW QUESTION # 465
You need to select a feature extraction method.
Which method should you use?

A. Spearman correlation
B. Mann-Whitney test
C. Pearson's correlation
D. Mutual information

Answer: A

Explanation:
Explanation
Spearman's rank correlation coefficient assesses how well the relationship between two variables can be described using a monotonic function.
Note: Both Spearman's and Kendall's can be formulated as special cases of a more general correlation coefficient, and they are both appropriate in this scenario.
Scenario: The MedianValue and AvgRoomsInHouse columns both hold data in numeric format. You need to select a feature selection algorithm to analyze the relationship between the two columns in more detail.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/feature-selection-modules

NEW QUESTION # 466
You are running a training experiment on remote compute in Azure Machine Learning.
The experiment is configured to use a conda environment that includes the mlflow and azureml-contrib-run packages.
You must use MLflow as the logging package for tracking metrics generated in the experiment.
You need to complete the script for the experiment.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation

Box 1: import mlflow
Import the mlflow and Workspace classes to access MLflow's tracking URI and configure your workspace.
Box 2: mlflow.start_run()
Set the MLflow experiment name with set_experiment() and start your training run with start_run().
Box 3: mlflow.log_metric(' ..')
Use log_metric() to activate the MLflow logging API and begin logging your training run metrics.
Box 4: mlflow.end_run()
Close the run:
run.endRun()
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-use-mlflow

NEW QUESTION # 467
......

Download DP-100 Free Dumps: https://www.certkingdompdf.com/DP-100-latest-certkingdom-dumps.html

BTW, DOWNLOAD part of CertkingdomPDF DP-100 dumps from Cloud Storage: https://drive.google.com/open?id=1WDz476tlwYF1ezvRSwojGh7-daEE6eM9

Liam Roberts Liam Roberts

Biography

Designing and Implementing a Data Science Solution on Azure valid practice questions & DP-100 exam pdf torrent & Designing and Implementing a Data Science Solution on Azure latest study dumps

Download DP-100 Free Dumps & Exam DP-100 Overview

Microsoft Designing and Implementing a Data Science Solution on Azure Sample Questions (Q462-Q467):

Call us free

Feature Links

Information

Download Now

Blog

Liam Roberts Liam Roberts

Biography

Designing and Implementing a Data Science Solution on Azure valid practice questions & DP-100 exam pdf torrent & Designing and Implementing a Data Science Solution on Azure latest study dumps

Download DP-100 Free Dumps & Exam DP-100 Overview

Microsoft Designing and Implementing a Data Science Solution on Azure Sample Questions (Q462-Q467):

Call us free

Sign in

Sign up