This page was exported from Exams Labs Braindumps [ http://blog.examslabs.com ] Export date:Thu Nov 21 13:34:50 2024 / +0000 GMT ___________________________________________________ Title: [May 12, 2022] Lesson Brilliant PDF for the DP-100 Tests Free Updated Today [Q29-Q46] --------------------------------------------------- [May 12, 2022] Lesson Brilliant PDF for the DP-100 Tests Free Updated Today Get New 2022 Valid Practice Microsoft Azure DP-100 Q&A - Testing Engine NEW QUESTION 29You are creating a machine learning model.You need to identify outliers in the data.Which two visualizations can you use? Each correct answer presents a complete solution.NOTE: Each correct selection is worth one point.NOTE: Each correct selection is worth one point.  box plot  scatter  random forest diagram  Venn diagram  ROC curve The box-plot algorithm can be used to display outliers.One other way to quickly identify Outliers visually is to create scatter plots.Reference:https://blogs.msdn.microsoft.com/azuredev/2017/05/27/data-cleansing-tools-in-azure-machine-learning/NEW QUESTION 30You create a multi-class image classification deep learning experiment by using the PyTorch framework. You plan to run the experiment on an Azure Compute cluster that has nodes with GPU’s.You need to define an Azure Machine Learning service pipeline to perform the monthly retraining of the image classification model. The pipeline must run with minimal cost and minimize the time required to train the model.Which three pipeline steps should you run in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order. Explanation:Step 1: Configure a DataTransferStep() to fetch new image data…Step 2: Configure a PythonScriptStep() to run image_resize.y on the cpu-compute compute target.Step 3: Configure the EstimatorStep() to run training script on the gpu_compute computer target.The PyTorch estimator provides a simple way of launching a PyTorch training job on a compute target.Reference:https://docs.microsoft.com/en-us/azure/machine-learning/how-to-train-pytorchNEW QUESTION 31You need to configure the Permutation Feature Importance module for the model training requirements.What should you do? To answer, select the appropriate options in the dialog box in the answer area.NOTE: Each correct selection is worth one point. ExplanationBox 1: 500For Random seed, type a value to use as seed for randomization. If you specify 0 (the default), a number is generated based on the system clock.A seed value is optional, but you should provide a value if you want reproducibility across runs of the same experiment.Here we must replicate the findings.Box 2: Mean Absolute ErrorScenario: Given a trained model and a test dataset, you must compute the Permutation Feature Importance scores of feature variables. You need to set up the Permutation Feature Importance module to select the correct metric to investigate the model’s accuracy and replicate the findings.Regression. Choose one of the following: Precision, Recall, Mean Absolute Error , Root Mean Squared Error, Relative Absolute Error, Relative Squared Error, Coefficient of Determination References:https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/permutation-feature-importanNEW QUESTION 32You are using Azure Machine Learning to train machine learning models. You need a compute target on which to remotely run the training script. You run the following Python code: Reference:https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.compute.amlcompute.amlcomputeprovisioningconfigurationhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-create-attach-compute-studioNEW QUESTION 33Note: 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 have a Python script named train.py in a local folder named scripts. The script trains a regression model by using scikit-learn. The script includes code to load a training data file which is also located in the scripts folder.You must run the script as an Azure ML experiment on a compute cluster named aml-compute.You need to configure the run to ensure that the environment includes the required packages for model training. You have instantiated a variable named aml-compute that references the target compute cluster.Solution: Run the following code:Does the solution meet the goal?  Yes  No ExplanationThe scikit-learn estimator provides a simple way of launching a scikit-learn training job on a compute target. It is implemented through the SKLearn class, which can be used to support single-node CPU training.Example:from azureml.train.sklearn import SKLearn}estimator = SKLearn(source_directory=project_folder,compute_target=compute_target,entry_script=’train_iris.py’)Reference:https://docs.microsoft.com/en-us/azure/machine-learning/how-to-train-scikit-learnNEW QUESTION 34You have an Azure Machine Learning workspace that contains a training cluster and an inference cluster.You plan to create a classification model by using the Azure Machine Learning designer.You need to ensure that client applications can submit data as HTTP requests and receive predictions as responses.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. 1 – Create a pipeline that trains a classification model and run the pipeline on the compute cluster.2 – Create a batch inference pipeline and run the pipeline on the compute cluster.3 – Deploy a service to the inference cluster.NEW QUESTION 35You are solving a classification task.The dataset is imbalanced.You need to select an Azure Machine Learning Studio module to improve the classification accuracy.Which module should you use?  Permutation Feature Importance  Filter Based Feature Selection  Fisher Linear Discriminant Analysis  Synthetic Minority Oversampling Technique (SMOTE) ExplanationExplanation:Use the SMOTE module in Azure Machine Learning Studio (classic) 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.You connect the SMOTE module to a dataset that is imbalanced. There are many reasons why a dataset might be imbalanced: the category you are targeting might be very rare in the population, or the data might simply be difficult to collect. Typically, you use SMOTE when the class you want to analyze is under-represented.Reference:https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/smoteNEW QUESTION 36You create a binary classification model using Azure Machine Learning Studio.You must use a Receiver Operating Characteristic (RO C) curve and an F1 score to evaluate the model.You need to create the required business metrics.How should you complete the experiment? To answer, select the appropriate options in the dialog box in the answer area.NOTE: Each correct selection is worth one point. NEW QUESTION 37You are a lead data scientist for a project that tracks the health and migration of birds. You create a multi-class image classification deep learning model that uses a set of labeled bird photographs collected by experts.You have 100,000 photographs of birds. All photographs use the JPG format and are stored in an Azure blob container in an Azure subscription.You need to access the bird photograph files in the Azure blob container from the Azure Machine Learning service workspace that will be used for deep learning model training. You must minimize data movement.What should you do?  Create an Azure Data Lake store and move the bird photographs to the store.  Create an Azure Cosmos DB database and attach the Azure Blob containing bird photographs storage to the database.  Create and register a dataset by using TabularDataset class that references the Azure blob storage containing bird photographs.  Register the Azure blob storage containing the bird photographs as a datastore in Azure Machine Learning service.  Copy the bird photographs to the blob datastore that was created with your Azure Machine Learning service workspace. ExplanationWe recommend creating a datastore for an Azure Blob container. When you create a workspace, an Azure blob container and an Azure file share are automatically registered to the workspace.Reference:https://docs.microsoft.com/en-us/azure/machine-learning/how-to-access-dataNEW QUESTION 38You need to define a process for penalty event detection.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. NEW QUESTION 39You are preparing to use the Azure ML SDK to run an experiment and need to create compute. 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. Reference:https://notebooks.azure.com/azureml/projects/azureml-getting-started/html/how-to-use-azureml/training/train-on-amlcompute/train-on-amlcompute.ipynbhttps://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.compute.computetargetNEW QUESTION 40You must use the Azure Machine Learning SDK to interact with data and experiments in the workspace.You need to configure the config.json file to connect to the workspace from the Python environment.Which two additional parameters must you add to the config.json file in order to connect to the workspace? Each correct answer presents part of the solution.NOTE: Each correct selection is worth one point.  subscription_Id  Key  resource_group  region  Login To use the same workspace in multiple environments, create a JSON configuration file. The configuration file saves your subscription (subscription_id), resource (resource_group), and workspace name so that it can be easily loaded.The following sample shows how to create a workspace.from azureml.core import Workspacews = Workspace.create(name=’myworkspace’,subscription_id='<azure-subscription-id>’,resource_group=’myresourcegroup’,create_resource_group=True,location=’eastus2′)Reference:https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.workspace.workspaceNEW QUESTION 41Note: 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 tin- 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 Principal Components Analysis (PCA) sampling mode.Does the solution meet the goal?  Yes  No NEW QUESTION 42You need to visually identify whether outliers exist in the Age column and quantify the outliers before the outliers are removed.Which three Azure Machine Learning Studio modules should you use in sequence? To answer, move the appropriate modules from the list of modules to the answer area and arrange them in the correct order. Explanation:You can use the Clip Values module in Azure Machine Learning Studio, to identify and optionally replace data values that are above or below a specified threshold. This is useful when you want to remove outliers or replace them with a mean, a constant, or other substitute value.References:https://blogs.msdn.microsoft.com/azuredev/2017/05/27/data-cleansing-tools-in-azure-machine-learning/https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/clip-valuesNEW QUESTION 43You are building a machine learning model for translating English language textual content into French language textual content.You need to build and train the machine learning model to learn the sequence of the textual content.Which type of neural network should you use?  Multilayer Perceptions (MLPs)  Convolutional Neural Networks (CNNs)  Recurrent Neural Networks (RNNs)  Generative Adversarial Networks (GANs) To translate a corpus of English text to French, we need to build a recurrent neural network (RNN).Note: RNNs are designed to take sequences of text as inputs or return sequences of text as outputs, or both.They’re called recurrent because the network’s hidden layers have a loop in which the output and cell state from each time step become inputs at the next time step. This recurrence serves as a form of memory. It allows contextual information to flow through the network so that relevant outputs from previous time steps can be applied to network operations at the current time step.Reference:https://towardsdatascience.com/language-translation-with-rnns-d84d43b40571NEW QUESTION 44You need to produce a visualization for the diagnostic test evaluation according to the data visualization requirements.Which three modules should you recommend be used in sequence? To answer, move the appropriate modules from the list of modules to the answer area and arrange them in the correct order. 1 – SweepClustering2 – Train Model3 – Evaluate ModelNEW QUESTION 45You plan to run a script as an experiment using a Script Run Configuration. The script uses modules from the scipy library as well as several Python packages that are not typically installed in a default conda environment.You plan to run the experiment on your local workstation for small datasets and scale out the experiment by running it on more powerful remote compute clusters for larger datasets.You need to ensure that the experiment runs successfully on local and remote compute with the least administrative effort.What should you do?  Do not specify an environment in the run configuration for the experiment. Run the experiment by using the default environment.  Create a virtual machine (VM) with the required Python configuration and attach the VM as a compute target. Use this compute target for all experiment runs.  Create and register an Environment that includes the required packages. Use this Environment for all experiment runs.  Create a config.yaml file defining the conda packages that are required and save the file in the experiment folder.  Always run the experiment with an Estimator by using the default packages. If you have an existing Conda environment on your local computer, then you can use the service to create an environment object. By using this strategy, you can reuse your local interactive environment on remote runs.Reference:https://docs.microsoft.com/en-us/azure/machine-learning/how-to-use-environmentsNEW QUESTION 46You have an Azure Machine Learning workspace that contains a training cluster and an inference cluster.You plan to create a classification model by using the Azure Machine Learning designer.You need to ensure that client applications can submit data as HTTP requests and receive predictions as responses.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.  Loading … DP-100 Dumps PDF - 100% Passing Guarantee: https://www.examslabs.com/Microsoft/Microsoft-Azure/best-DP-100-exam-dumps.html --------------------------------------------------- Images: https://blog.examslabs.com/wp-content/plugins/watu/loading.gif https://blog.examslabs.com/wp-content/plugins/watu/loading.gif --------------------------------------------------- --------------------------------------------------- Post date: 2022-05-12 20:55:33 Post date GMT: 2022-05-12 20:55:33 Post modified date: 2022-05-12 20:55:33 Post modified date GMT: 2022-05-12 20:55:33