This page was exported from Actual Test Materials [ http://blog.actualtests4sure.com ] Export date:Mon Apr 14 1:00:20 2025 / +0000 GMT ___________________________________________________ Title: [Apr-2025] DP-100 Certification with Actual Questions from Actualtests4sure [Q150-Q173] --------------------------------------------------- [Apr-2025] DP-100 Certification with Actual Questions from Actualtests4sure Updated DP-100 Dumps PDF - DP-100 Real Valid Brain Dumps With 445 Questions! QUESTION 150You manage an Azure Machine Learning workspace named workspace1by using the Python SDK v2.You must register datastores in workspace 1 for Azure Blot storage and Azure Fetes storage to meet the following requirements.* Azure Active Directory (Azure AD) authentication must be used for access to storage when possible.* Credentials and secrets steed in workspace1 must be valid lot a specified time period when accessing Azure Files storage.You need to configure a security access method used to register the Azure Blob and azure files storage in workspace1.Which security access method should you configure? To answer, select the appropriate options in the answer area.NOTE: Each correct selection is worth one point. ExplanationQUESTION 151You are building recurrent neural network to perform a binary classification.The training loss, validation loss, training accuracy, and validation accuracy of each training epoch has been provided. You need to identify whether the classification model is over fitted.Which of the following is correct?  The training loss increases while the validation loss decreases when training the model.  The training loss decreases while the validation loss increases when training the model.  The training loss stays constant and the validation loss decreases when training the model.  The training loss .stays constant and the validation loss stays on a constant value and close to the training loss value when training the model. ExplanationAn overfit model is one where performance on the train set is good and continues to improve, whereas performance on the validation set improves to a point and then begins to degrade.References:https://machinelearningmastery.com/diagnose-overfitting-underfitting-lstm-models/QUESTION 152You use an Azure Machine Learning workspace.You create the following Python 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://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.scriptrunconfighttps://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.environment.environmentQUESTION 153You register a file dataset named csvjolder that references a folder. The folder includes multiple com ma-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)B)C)D)  Option A  Option B  Option C  Option D Example:from azureml.train.estimator import Estimatorscript_params = {# to mount files referenced by mnist dataset‘–data-folder’: mnist_file_dataset.as_named_input(‘mnist_opendataset’).as_mount(),‘–regularization’: 0.5}est = Estimator(source_directory=script_folder,script_params=script_params,compute_target=compute_target,environment_definition=env,entry_script=’train.py’)Reference:https://docs.microsoft.com/en-us/azure/machine-learning/tutorial-train-models-with-amlQUESTION 154You are developing a machine learning, experiment by using Azure. The following images show the input and output of a machine learning experiment:Use the drop-down menus to select the answer choice that answers each question based on the information presented in the graphic.NOTE: Each correct selection is worth one point. QUESTION 155You need to correct the model fit issue.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. Explanation:Step 1: Augment the dataScenario: Columns in each dataset contain missing and null values. The datasets also contain many outliers.Step 2: Add the Bayesian Linear Regression module.Scenario: You produce a regression model to predict property prices by using the Linear Regression and Bayesian Linear Regression modules.Step 3: Configure the regularization weight.Regularization typically is used to avoid overfitting. For example, in L2 regularization weight, type the value to use as the weight for L2 regularization. We recommend that you use a non-zero value to avoid overfitting.Scenario:Model fit: The model shows signs of overfitting. You need to produce a more refined regression model that reduces the overfitting.Incorrect Answers:Multiclass Decision Jungle module:Decision jungles are a recent extension to decision forests. A decision jungle consists of an ensemble of decision directed acyclic graphs (DAGs).L-BFGS:L-BFGS stands for “limited memory Broyden-Fletcher-Goldfarb-Shanno”. It can be found in the wwo-Class Logistic Regression module, which is used to create a logistic regression model that can be used to predict two (and only two) outcomes.References:<https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/linear-regr ession>QUESTION 156You use Azure Machine Learning to implement hyperparameter tuning for an Azure ML Python SDK v2-based model training.Training runs must terminate when the primary metric is lowered by 25 percent or more compared to the best performing run.You need to configure an early termination policy to terminate training jobs.Which values should you use? To answer, select the appropriate options in the answer area.NOTE: Each correct selection is worth one point. ExplanationQUESTION 157You create a multi-class image classification deep learning model.The model must be retrained monthly with the new image data fetched from a public web portal. You create an Azure Machine Learning pipeline to fetch new data, standardize the size of images, and retrain the model.You need to use the Azure Machine Learning SDK to configure the schedule for the pipeline.Which four 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. ExplanationStep 1: Publish the pipeline.To schedule a pipeline, you’ll need a reference to your workspace, the identifier of your published pipeline, and the name of the experiment in which you wish to create the schedule.Step 2: Retrieve the pipeline ID.Needed for the schedule.Step 3: Create a ScheduleRecurrence..To run a pipeline on a recurring basis, you’ll create a schedule. A Schedule associates a pipeline, an experiment, and a trigger.First create a schedule. Example: Create a Schedule that begins a run every 15 minutes:recurrence = ScheduleRecurrence(frequency=”Minute”, interval=15)Step 4: Define an Azure Machine Learning pipeline schedule..Example, continued:recurring_schedule = Schedule.create(ws, name=”MyRecurringSchedule”,description=”Based on time”,pipeline_id=pipeline_id,experiment_name=experiment_name,recurrence=recurrence)Reference:https://docs.microsoft.com/en-us/azure/machine-learning/how-to-schedule-pipelinesQUESTION 158You arc I mating a deep learning model to identify cats and dogs. You have 25,000 color images.You must meet the following requirements:* Reduce the number of training epochs.* Reduce the size of the neural network.* Reduce over-fitting of the neural network.You need to select the image modification values.Which value should you use? To answer, select the appropriate Options in the answer area.NOTE: Each correct selection is worth one point. QUESTION 159You plan to use Hyperdrive to optimize the hyperparameters selected when training a model. You create the following code to define options for the hyperparameter experimentFor 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://docs.microsoft.com/en-us/python/api/azureml-train-core/azureml.train.hyperdrive.hyperdriveconfighttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparametersQUESTION 160You have an Azure Machine Learning workspace.You plan to use the terminal to configure a compute instance to run a notebook.You need to add a new R kernel to the compute instance.In which order should you perform the actions? To answer, move all actions from the list of actions to the answer area and arrange them in the correct order. Explanation:QUESTION 161You train classification and regression models by using automated machine learning.You must evaluate automated machine learning experiment results. The results include how a classification model is making systematic errors in its predictions and the relationship between the target feature and the regression model’s predictions. You must use charts generated by automated machine learning.You need to choose a chart type for each model type.Which chart types should you use? To answer, select the appropriate options in the answer area.NOTE: Each correct selection is worth one point. See below imageQUESTION 162Note: 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.An IT department creates the following Azure resource groups and resources:The IT department creates an Azure Kubernetes Service (AKS)-based inference compute target named aks-cluster in the Azure Machine Learning workspace.You have a Microsoft Surface Book computer with a GPU. Python 3.6 and Visual Studio Code are installed.You need to run a script that trains a deep neural network (DNN) model and logs the loss and accuracy metrics.Solution: Install the Azure ML SDK on the Surface Book. Run Python code to connect to the workspace and then run the training script as an experiment on local compute.  Yes  No Need to attach the mlvm virtual machine as a compute target in the Azure Machine Learning workspace.Reference:https://docs.microsoft.com/en-us/azure/machine-learning/concept-compute-targetQUESTION 163You create an Azure Machine Learning compute target named ComputeOne by using the STANDARD_D1 virtual machine image.You define a Python variable named was that references the Azure Machine Learning workspace. You run the following Python 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://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.compute.computetargetQUESTION 164You create an experiment in Azure Machine Learning Studio. You add a training dataset that contains 10,000 rows. The first 9,000 rows represent class 0 (90 percent).The remaining 1,000 rows represent class 1 (10 percent).The training set is imbalances between two classes. You must increase the number of training examples for class 1 to 4,000 by using 5 data rows. You add the Synthetic Minority Oversampling Technique (SMOTE) module to the experiment.You need to configure the module.Which values should you use? To answer, select the appropriate options in the dialog box in the answer area.NOTE: Each correct selection is worth one point. Explanation:Box 1: 300You type 300 (%), the module triples the percentage of minority cases (3000) compared to the original dataset (1000).Box 2: 5We should use 5 data rows.Use the Number of nearest neighbors option to determine the size of the feature space that the SMOTE algorithm uses when in building new cases. A nearest neighbor is a row of data (a case) that is very similar to some target case. The distance between any two cases is measured by combining the weighted vectors of all features.By increasing the number of nearest neighbors, you get features from more cases.By keeping the number of nearest neighbors low, you use features that are more like those in the original sample.References:https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/smoteQUESTION 165You train and register a model by using the Azure Machine Learning SDK on a local workstation. Python 3.6 and Visual Studio Code are installed on the workstation.When you try to deploy the model into production as an Azure Kubernetes Service (AKS)-based web service, you experience an error in the scoring script that causes deployment to fail.You need to debug the service on the local workstation before deploying the service to production.Which four 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 – Install Docker on the workstation2 – Create an AksWebservice deployment configuration and deploy the model to it3 – Create a LocalWebservice deployment configuration for the service and deploy the model to it4 – Debug and modify the scoring script as necessary. Use the reload() method of the service after each modification.Reference:https://docs.microsoft.com/en-us/azure/machine-learning/how-to-deploy-azure-kubernetes-servicehttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-deployment-localQUESTION 166You create a Python script named train.py and save it in a folder named scripts. The script uses the scikit-learn framework to train a machine learning model.You must run the script as an Azure Machine Learning experiment on your local workstation.You need to write Python code to initiate an experiment that runs the train.py script.How should you complete the code segment? To answer, select the appropriate options in the answer area.NOTE: Each correct selection is worth one point. Reference:https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.scriptrunconfigQUESTION 167You are developing a linear regression model in Azure Machine Learning Studio. You run an experiment to compare different algorithms.The following image displays the results dataset output:Use the drop-down menus to select the answer choice that answers each question based on the information presented in the image.NOTE: Each correct selection is worth one point. Reference:https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/evaluate-modelhttps://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/linear-regressionQUESTION 168You have a dataset created for multiclass classification tasks that contains a normalized numerical feature set with 10,000 data points and 150 features.You use 75 percent of the data points for training and 25 percent for testing. You are using the scikit-learn machine learning library in Python. You use X to denote the feature set and Y to denote class labels.You create the following Python data frames:You need to apply the Principal Component Analysis (PCA) method to reduce the dimensionality of the feature set to 10 features in both training and testing sets.How should you complete the code segment? To answer, select the appropriate options in the answer area.NOTE: Each correct selection is worth one point. Explanation:Box 1: PCA(n_components = 10)Need to reduce the dimensionality of the feature set to 10 features in both training and testing sets.Example:from sklearn.decomposition import PCApca = PCA(n_components=2) ;2 dimensionsprincipalComponents = pca.fit_transform(x)Box 2: pcafit_transform(X[, y])fits the model with X and apply the dimensionality reduction on X.Box 3: transform(x_test)transform(X) applies dimensionality reduction to X.References:https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.htmlQUESTION 169You train classification and regression models by using automated machine learning.You must evaluate automated machine learning experiment results. The results include how a classification model is making systematic errors in its predictions and the relationship between the target feature and the regression model’s predictions. You must use charts generated by automated machine learning.You need to choose a chart type for each model type.Which chart types should you use? To answer, select the appropriate options in the answer area.NOTE: Each correct selection is worth one point. QUESTION 170You need to replace the missing data in the AccessibilityToHighway columns.How should you configure the Clean Missing Data module? To answer, select the appropriate options in the answer area.NOTE: Each correct selection is worth one point. Reference:https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/clean-missing-dataQUESTION 171You create an Azure Machine Learning compute resource to train models. The compute resource is configured as follows:* Minimum nodes: 2* Maximum nodes: 4You must decrease the minimum number of nodes and increase the maximum number of nodes to the following values:* Minimum nodes: 0* Maximum nodes: 8You need to reconfigure the compute resource.What are three possible ways to achieve this goal? Each correct answer presents a complete solution.NOTE: Each correct selection is worth one point.  Use the Azure Machine Learning studio.  Run the update method of the AmlCompute class in the Python SDK.  Use the Azure portal.  Use the Azure Machine Learning designer.  Run the refresh_state() method of the BatchCompute class in the Python SDK Reference:https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.compute.amlcompute(class)QUESTION 172You manage are Azure Machine Learning workspace by using the Python SDK v2.You must create an automated machine learning job to generate a classification model by using data files stored in Parquet format. You must configure an auto scaling compute target and a data asset for the job.You need to configure the resources for the job.Which resource configuration should you use? to answer, select the appropriate options in the answer area.NOTE: Each correct selection is worth one point. QUESTION 173The finance team asks you to train a model using data in an Azure Storage blob container named finance-data.You need to register the container as a datastore in an Azure Machine Learning workspace and ensure that an error will be raised if the container does not exist.How should you complete the code? To answer, select the appropriate options in the answer area.NOTE: Each correct selection is worth one point. Explanation:Box 1: register_azure_blob_containerRegister an Azure Blob Container to the datastore.Box 2: create_if_not_exists = FalseCreate the file share if it does not exists, defaults to False.Reference:https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.datastore.datastore Loading … The Microsoft DP-100 test helps candidates check their machine learning knowledge and skills and prove themselves as qualified data scientists.   Pass Your DP-100 Exam Easily With 100% Exam Passing Guarantee: https://www.actualtests4sure.com/DP-100-test-questions.html --------------------------------------------------- Images: https://blog.actualtests4sure.com/wp-content/plugins/watu/loading.gif https://blog.actualtests4sure.com/wp-content/plugins/watu/loading.gif --------------------------------------------------- --------------------------------------------------- Post date: 2025-04-12 16:13:12 Post date GMT: 2025-04-12 16:13:12 Post modified date: 2025-04-12 16:13:12 Post modified date GMT: 2025-04-12 16:13:12