Free Microsoft DP-100 Practice Questions & Answers 2026 Part3

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?

This question is included in a number of questions that depicts the identical set-up. However, every question has a distinctive result. Establish if the recommendation satisfies the requirements.You have been tasked with constructing a machine learning model that translates language text into a different language text.The machine learning model must be constructed and trained to learn the sequence of the.Recommendation: You make use of Generative Adversarial Networks (GANs).Will the requirements be satisfied?

You create an Azure Machine Learning workspace.You must use the Python SDK v2 to implement an experiment from a Jupyter notebook in the workspace. The experiment must log string metrics. You need to implement the method to log the string metrics. Which method should you use?

This question is included in a number of questions that depicts the identical set-up. However, every question has a distinctive result. Establish if the recommendation satisfies the requirements.You have been tasked with employing a machine learning model, which makes use of a PostgreSQL database and needs GPU processing, to forecast prices.You are preparing to create a virtual machine that has the necessary tools built into it.You need to make use of the correct virtual machine type.Recommendation: You make use of a Geo AI Data Science Virtual Machine (Geo-DSVM) Windows edition.Will the requirements be satisfied?

You are analyzing a dataset by using Azure Machine Learning Studio.You need to generate a statistical summary that contains the p-value and the unique count for each feature column.Which two modules can you use? Each correct answer presents a complete solution.NOTE: Each correct selection is worth one point.

You plan to create a speech recognition deep learning model.The model must support the latest version of Python.You need to recommend a deep learning framework for speech recognition to include in the Data Science Virtual Machine (DSVM).What should you recommend?

You are making use of the Azure Machine Learning to designer construct an experiment.After dividing a dataset into training and testing sets, you configure the algorithm to be Two-Class Boosted Decision Tree.You are preparing to ascertain the Area Under the Curve (AUC).Which of the following is a sequential combination of the models required to achieve your goal?

You are preparing to train a regression model via automated machine learning. The data available to you has features with missing values, as well as categorical features with little discrete values.You want to make sure that automated machine learning is configured as follows:-missing values must be automatically imputed.-categorical features must be encoded as part of the training task.Which of the following actions should you take?

You create an Azure Machine Learning workspace named woricspace1. The workspace contains a Python SDK v2 notebook that uses MLflow to collect model training metrics and artifacts from your local computer.You must reuse the notebook to run on Azure Machine Learning compute instance in workspace1.You need to continue to log metrics and artifacts from your data science code.What should you do?

You are in the process of constructing a deep convolutional neural network (CNN). The CNN will be used for image classification.You notice that the CNN model you constructed displays hints of overfitting.You want to make sure that overfitting is minimized, and that the model is converged to an optimal fit.Which of the following is TRUE with regards to achieving your goal?

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?

You make use of Azure Machine Learning Studio to create a binary classification model.You are preparing to carry out a parameter sweep of the model to tune hyperparameters. You have to make sure that the sweep allows for every possible combination of hyperparameters to be iterated. Also, the computing resources needed to carry out the sweep must be reduced.Which of the following actions should you take?

You create a binary classification model by using Azure Machine Learning Studio.You must tune hyperparameters by performing a parameter sweep of the model. The parameter sweep must meet the following requirements:iterate all possible combinations of hyperparametersminimize computing resources required to perform the sweepYou need to perform a parameter sweep of the model.Which parameter sweep mode should you use?

You have been tasked with designing a deep learning model, which accommodates the most recent edition of Python, to recognize language.You have to include a suitable deep learning framework in the Data Science Virtual Machine (DSVM).Which of the following actions should you take?

You are moving a large dataset from Azure Machine Learning Studio to a Weka environment.You need to format the data for the Weka environment.Which module should you use?

You have been tasked with designing a deep learning model, which accommodates the most recent edition of Python, to recognize language.You have to include a suitable deep learning framework in the Data Science Virtual Machine (DSVM).Which of the following actions should you take?

This question is included in a number of questions that depicts the identical set-up. However, every question has a distinctive result. Establish if the recommendation satisfies the requirements.You have been tasked with evaluating your model on a partial data sample via k-fold cross-validation.You have already configured a k parameter as the number of splits. You now have to configure the k parameter for the cross-validation with the usual value choice.Recommendation: You configure the use of the value k=1.Will the requirements be satisfied?

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 using Azure Machine Learning Studio to perform feature engineering on a dataset.You need to normalize values to produce a feature column grouped into bins.Solution: Apply an Entropy Minimum Description Length (MDL) binning mode.Does the solution meet the goal?

A set of CSV files contains sales records. All the CSV files have the same data schema.Each CSV file contains the sales record for a particular month and has the filename sales.csv. Each file is stored in a folder that indicates the month and year when the data was recorded. The folders are in an Azure blob container for which a datastore has been defined in an Azure Machine Learning workspace. The folders are organized in a parent folder named sales to create the following hierarchical structure:At the end of each month, a new folder with that month's sales file is added to the sales folder.You plan to use the sales data to train a machine learning model based on the following requirements:-You must define a dataset that loads all of the sales data to date into a structure that can be easily converted to a dataframe.-You must be able to create experiments that use only data that was created before a specific previous month, ignoring any data that was added after that month.-You must register the minimum number of datasets possible.You need to register the sales data as a dataset in Azure Machine Learning service workspace.What should you do?

This question is included in a number of questions that depicts the identical set-up. However, every question has a distinctive result. Establish if the recommendation satisfies the requirements.You have been tasked with employing a machine learning model, which makes use of a PostgreSQL database and needs GPU processing, to forecast prices.You are preparing to create a virtual machine that has the necessary tools built into it.You need to make use of the correct virtual machine type.Recommendation: You make use of a Data Science Virtual Machine (DSVM) Windows edition.Will the requirements be satisfied?

You create an Azure Machine Learning workspace.

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 analyzing a numerical dataset which contains missing values in several columns.You must clean the missing values using an appropriate operation without affecting the dimensionality of the feature set.You need to analyze a full dataset to include all values.Solution: Use the Last Observation Carried Forward (LOCF) method to impute the missing data points.Does the solution meet the goal?

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 analyzing a numerical dataset which contains missing values in several columns.You must clean the missing values using an appropriate operation without affecting the dimensionality of the feature set.You need to analyze a full dataset to include all values.Solution: Replace each missing value using the Multiple Imputation by Chained Equations (MICE) method.Does the solution meet the goal?

you create an Azure Machine learning workspace named workspace1. The workspace contains a Python SOK v2 notebook mat uses Mallow to correct model coaxing men's anal arracks from your local computer.

You have an Azure AI Foundry project.

You make use of Azure Machine Learning Studio to develop a linear regression model. You perform an experiment to assess various algorithms.Which of the following is an algorithm that reduces the variances between actual and predicted values?

You need to consider the underlined segment to establish whether it is accurate.To improve the amount of low incidence cases in a dataset, you should make use of the SMOTE module.Select `No adjustment required` if the underlined segment is accurate. If the underlined segment is inaccurate, select the accurate option.

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 an Equal Width with Custom Start and Stop binning mode.Does the solution meet the goal?

You manage an Azure Machine Learning workspace. You have a folder that contains a CSV file. The folder is registered as a folder data asset You plan to use the folder data asset for data wrangling dunng interactive development. You need to access and load the folder data asset into a Pandas data frame. Which method should you use to achieve this goal?

You are with a time series dataset in Azure Machine Learning Studio.You need to split your dataset into training and testing subsets by using the Split Data module.Which splitting mode should you use?

You plan to deliver a hands-on workshop to several students. The workshop will focus on creating data visualizations 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 to install 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?

You plan to build a team data science environment. Data for training models in machine learning pipelines will be over 20 GB in size.You have the following requirements:-Models must be built using Caffe2 or Chainer frameworks.-Data scientists must be able to use a data science environment to build the machine learning pipelines and train models on their personal devices in both connected and disconnected network environments.Personal devices must support updating machine learning pipelines when connected to a network.You need to select a data science environment.Which environment should you use?

You want to train a classification model using data located in a comma-separated values (CSV) file.The classification model will be trained via the Automated Machine Learning interface using the Classification task type.You have been informed that only linear models need to be assessed by the Automated Machine Learning.Which of the following actions should you take?