Free Practice Questions for Microsoft DP-100 Exam

You plan to deliver a hands-on workshop to several students. The workshop will focus on creating datavisualizations using Python. Each student will use a device that has internet access.Student devices are not configured for Python development. Students do not have administrator access toinstall software on their devices. Azure subscriptions are not available for students.You need to ensure that students can run Python-based data visualization code.Which Azure tool should you use?

• Anaconda Data Science Platform
• Azure BatchAl
• Azure Notebooks
• Azure Machine Learning Service

You create a workspace by using Azure Machine Learning Studio.You must run a Python SDK v2 notebook in the workspace by using Azure Machine Learning Studio. You must preserve the current values of variables set in the notebook for the current instance.You need to maintain the state of the notebook.What should you do?

• Change the compute.
• Change the current kernel
• Stop the compute.
• Stop the current kernel.

You are conducting feature engineering to prepuce data for further analysis.The data includes seasonal patterns on inventory requirements.You need to select the appropriate method to conduct feature engineering on the data.Which method should you use?

• Exponential Smoothing (ETS) function.
• One Class Support Vector Machine module
• Time Series Anomaly Detection module
• Finite Impulse Response (FIR) Filter module.

You use Azure Machine Learning Studio to build a machine learning experiment.You need to divide data into two distinct datasets.Which module should you use?

• Partition and Sample
• Assign Data to Clusters
• Group Data into Bins
• Test Hypothesis Using t-Test

You are training machine learning models in Azure Machine Learning. You use Hyperdrive to tune the hyperparameters. In previous model training and tuning runs, many models showed similar performance. You need to select an early termination policy that meets the following requirements:* accounts for the performance of all previous runs when evaluating the current run* avoids comparing the current run with only the best performing run to dateWhich two early termination policies should you use? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

• Bandit
• Median stopping
• Default
• Truncation selection

You are creating a binary classification by using a two-class logistic regression model.You need to evaluate the model results for imbalance.Which evaluation metric should you use?

• Relative Absolute Error
• AUC Curve
• Mean Absolute Error
• Relative Squared Error

You use an Azure Machine Learning workspace.You have a trained model that must be deployed as a web service. Users must authenticate by using Azure Active Directory.What should you do?

• Deploy the model to Azure Kubernetes Service (AKS). During deployment, set the token_auth_enabled parameter of the target configuration object to true
• Deploy the model to Azure Container Instances. During deployment, set the auch_enabled parameter of the target configuration object to true
• Deploy the model to Azure Container Instances. During deployment, set the coken_auch_enabled parameter of the target configuration object to true
• Deploy the model to Azure Kubernetes Service (AKS). During deployment, set the auch. enabled parameter of the target configuration object to true

You are creating a machine learning model. You have a dataset that contains null rows.You need to use the Clean Missing Data module in Azure Machine Learning Studio to identify and resolve the null and missing data in the dataset.Which parameter should you use?

• Replace with mean
• Remove entire column
• Remove entire row
• Hot Deck

You use the Azure Machine learning SDK foe Python to create a pipeline that includes the following step:The output of the step run must be cached and reused on subsequent runs when the source.directory value has not changed.You need to define the step.What should you include in the step definition?

• allow.reuse
• hash_path
• data-as_input(name-)
• version

Note: 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 a data scientist using Azure Machine Learning Studio.You need to normalize values to produce an output column into bins to predict a target column.Solution: Apply a Quantiles binning mode with a PQuantile normalization.Does the solution meet the goal?

• Yes
• No