NEW DP-100 BRAINDUMPS EBOOK & NEW DP-100 TEST BOOTCAMP

New DP-100 Braindumps Ebook & New DP-100 Test Bootcamp

New DP-100 Braindumps Ebook & New DP-100 Test Bootcamp

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Tags: New DP-100 Braindumps Ebook, New DP-100 Test Bootcamp, Reliable DP-100 Practice Materials, DP-100 Dump Torrent, DP-100 Exam Fee

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The DP-100 Certification Exam is intended for data scientists, data architects, and data engineers who want to validate their expertise in designing and implementing data science solutions on Azure. It is also suitable for professionals who are responsible for implementing Azure-based machine learning and AI solutions, including data analysts, developers, and IT administrators.

Microsoft DP-100 certification exam is a valuable credential for professionals looking to advance their career in data science. It demonstrates to employers that the candidate has the skills and knowledge required to design and implement data science solutions on Azure. Designing and Implementing a Data Science Solution on Azure certification is recognized by Microsoft and is highly respected within the industry.

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The value of professional qualification has been shown to rise with time. For the advancement of your profession, exams like the Microsoft exam given by Microsoft are crucial. Candidates aim to pass the Designing and Implementing a Data Science Solution on Azure exam on their first attempt. With Microsoft DP-100 Exam Questions, applicants may study for and pass their desired certification exam on the first attempt. You may use Test4Cram's top DP-100 study resources to prepare for the Designing and Implementing a Data Science Solution on Azure exam. The Microsoft DP-100 exam questions offered by Test4Cram are dependable and trustworthy sources of preparation.

Microsoft Designing and Implementing a Data Science Solution on Azure Sample Questions (Q133-Q138):

NEW QUESTION # 133
You have an Azure Machine Learning workspace that contains a CPU-based compute cluster and an Azure Kubernetes Services (AKS) inference cluster. You create a tabular dataset containing data that you plan to use to create a classification model.
You need to use the Azure Machine Learning designer to create a web service through which client applications can consume the classification model by submitting new data and getting an immediate prediction as a response.
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

Step 1: Create and start a Compute Instance
To train and deploy models using Azure Machine Learning designer, you need compute on which to run the training process, test the model, and host the model in a deployed service.
There are four kinds of compute resource you can create:
Compute Instances: Development workstations that data scientists can use to work with data and models.
Compute Clusters: Scalable clusters of virtual machines for on-demand processing of experiment code.
Inference Clusters: Deployment targets for predictive services that use your trained models.
Attached Compute: Links to existing Azure compute resources, such as Virtual Machines or Azure Databricks clusters.
Step 2: Create and run a training pipeline..
After you've used data transformations to prepare the data, you can use it to train a machine learning model.
Create and run a training pipeline
Step 3: Create and run a real-time inference pipeline
After creating and running a pipeline to train the model, you need a second pipeline that performs the same data transformations for new data, and then uses the trained model to inference (in other words, predict) label values based on its features. This pipeline will form the basis for a predictive service that you can publish for applications to use.
Reference:
https://docs.microsoft.com/en-us/learn/modules/create-classification-model-azure-machine-learning-designer/


NEW QUESTION # 134
You are analyzing a raw dataset that requires cleaning.
You must perform transformations and manipulations by using Azure Machine Learning Studio.
You need to identify the correct modules to perform the transformations.
Which modules should you choose? To answer, drag the appropriate modules to the correct scenarios. Each module may be used once, more than once, or not at all.
You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

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


NEW QUESTION # 135
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 # 136
You need to identify the methods for dividing the data according, to the testing requirements.
Which properties should you select? To answer, select the appropriate option-, m the answer are a. NOTE: Each correct selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 137
You create a binary classification model to predict whether a person has a disease.
You need to detect possible classification errors.
Which error type should you choose for each description? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:


Reference:
https://developers.google.com/machine-learning/crash-course/classification/true-false-positive-negative


NEW QUESTION # 138
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