You write a Python script that processes data in a comma-separated values (CSV) file.You plan to run this script as an Azure Machine Learning experiment.The script loads the data and determines the number of rows it contains using the following code: You need to record the row count as a metric named row_count that can be returned using the get_metrics method of the Run object after the experiment run completes.Which code should you use?

run.upload_file(T3 row_count', './data.csv')

run.log_table('row_count', rows)

You are evaluating a completed binary classification machine learning model.You need to use the precision as the evaluation metric.Which visualization should you use?

Binary classification confusion matrix

You create a multi-class image classification deep learning model that uses the PyTorch deep learning framework.You must configure Azure Machine Learning Hyperdrive to optimize the hyperparameters for the classification model.You need to define a primary metric to determine the hyperparameter values that result in the model with the best accuracy score.Which three actions must you perform? Each correct answer presents part of the solution.NOTE: Each correct selection is worth one point.

Set the primary_metric_goal of the estimator used to run the bird_classifier_train.py script to maximize.

Set the primary_metric_name of the estimator used to run the bird_classifier_train.py script to accuracy.

Add code to the bird_classifier_train.py script to calculate the validation accuracy of the model and log it as a float value with the key accuracy.

Set the primary_metric_goal of the estimator used to run the bird_classifier_train.py script to maximize.

Add code to the bird_classifier_train.py script to calculate the validation loss of the model and log it as a float value with the key loss.

Set the primary_metric_goal of the estimator used to run the bird_classifier_train.py script to minimize.

Set the primary_metric_name of the estimator used to run the bird_classifier_train.py script to accuracy.

Set the primary_metric_name of the estimator used to run the bird_classifier_train.py script to loss.

Add code to the bird_classifier_train.py script to calculate the validation accuracy of the model and log it as a float value with the key accuracy.

You are building a regression model for estimating the number of calls during an event.You need to determine whether the feature values achieve the conditions to build a Poisson regression model.Which two conditions must the feature set contain? Each correct answer presents part of the solution.NOTE: Each correct selection is worth one point.

The label data must be whole numbers.

The label data must be a positive value.

The label data must be a negative value.

The label data must be whole numbers.

The label data must be non-discrete.

The label data must be a positive value.

The label data can be positive or negative.

You are evaluating a completed binary classification machine learning model.You need to use the precision as the evaluation metric.Which visualization should you use?

Receiver Operating Characteristic (ROC) curve

You use the Azure Machine Learning service to create a tabular dataset named training_data. You plan to use this dataset in a training script.You create a variable that references the dataset using the following code:training_ds = workspace.datasets.get("training_data")You define an estimator to run the script.You need to set the correct property of the estimator to ensure that your script can access the training_data dataset.Which property should you set?

inputs = [training_ds.as_named_input('training_ds')]

environment_definition = {"training_data":training_ds}

inputs = [training_ds.as_named_input('training_ds')]

script_params = {"--training_ds":training_ds}

You register a file dataset named csv_folder that references a folder. The folder includes multiple comma-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?

inputs=[file_dataset.as_named_input('training_files').as_mount()],

inputs=[file_dataset.as_named_input('training_files')],

inputs=[file_dataset.as_named_input('training_files').as_mount()],

inputs=[file_dataset.as_named_input('training_files').to_pandas_dataframe()],

script_params={'--training_files': file_dataset},

You plan to use the Hyperdrive feature of Azure Machine Learning to determine the optimal hyperparameter values when training a model.You must use Hyperdrive to try combinations of the following hyperparameter values:learning_rate: any value between 0.001 and 0.1 batch_size: 16, 32, or 64You need to configure the search space for the Hyperdrive experiment.Which two parameter expressions should you use? Each correct answer presents part of the solution.NOTE: Each correct selection is worth one point.

a uniform expression for learning_rate

a choice expression for batch_size

a choice expression for learning_rate

a uniform expression for learning_rate

a normal expression for batch_size

a choice expression for batch_size

a uniform expression for batch_size

You have a comma-separated values (CSV) file containing data from which you want to train a classification model.You are using the Automated Machine Learning interface in Azure Machine Learning studio to train the classification model. You set the task type to Classification.You need to ensure that the Automated Machine Learning process evaluates only linear models.What should you do?

Add all algorithms other than linear ones to the blocked algorithms list.

Set the Exit criterion option to a metric score threshold.

Clear the option to perform automatic featurization.

Clear the option to enable deep learning.

Set the task type to Regression.

You create a pipeline in designer to train a model that predicts automobile prices.Because of non-linear relationships in the data, the pipeline calculates the natural log (Ln) of the prices in the training data, trains a model to predict this natural log of price value, and then calculates the exponential of the scored label to get the predicted price.The training pipeline is shown in the exhibit. (Click the Training pipeline tab.)Training pipeline You create a real-time inference pipeline from the training pipeline, as shown in the exhibit. (Click the Real-time pipeline tab.)Real-time pipeline You need to modify the inference pipeline to ensure that the web service returns the exponential of the scored label as the predicted automobile price and that client applications are not required to include a price value in the input values.Which three modifications must you make to the inference pipeline? Each correct answer presents part of the solution.NOTE: Each correct selection is worth one point.

Connect the output of the Apply SQL Transformation to the Web Service Output module.

Add a Select Columns module before the Score Model module to select all columns other than price.

Remove the Apply Math Operation module that replaces price with its natural log from the data flow.

Connect the output of the Apply SQL Transformation to the Web Service Output module.

Replace the Web Service Input module with a data input that does not include the price column.

Add a Select Columns module before the Score Model module to select all columns other than price.

Replace the training dataset module with a data input that does not include the price column.

Remove the Apply Math Operation module that replaces price with its natural log from the data flow.

Remove the Apply SQL Transformation module from the data flow.

You are creating a classification model for a banking company to identify possible instances of credit card fraud. You plan to create the model in Azure Machine Learning by using automated machine learning.The training dataset that you are using is highly unbalanced.You need to evaluate the classification model.Which primary metric should you use?

normalized_root_mean_squared_error

You create a machine learning model by using the Azure Machine Learning designer. You publish the model as a real-time service on an Azure Kubernetes Service (AKS) inference compute cluster. You make no change to the deployed endpoint configuration.You need to provide application developers with the information they need to consume the endpoint.Which two values should you provide to application developers? Each correct answer presents part of the solution.NOTE: Each correct selection is worth one point.

The name of the AKS cluster where the endpoint is hosted.

The name of the inference pipeline for the endpoint.

The run ID of the inference pipeline experiment for the endpoint.

You run an experiment that uses an AutoMLConfig class to define an automated machine learning task with a maximum of ten model training iterations. The task will attempt to find the best performing model based on a metric named accuracy.You submit the experiment with the following code: You need to create Python code that returns the best model that is generated by the automated machine learning task.Which code segment should you use?

best_model = automl_run.get_output()[1]

best_model = automl_run.get_details()

best_model = automl_run.get_metrics()

best_model = automl_run.get_file_names()[1]

best_model = automl_run.get_output()[1]

Microsoft DP-100 Practice Test 4 - Free Online Exam Prep & Questions

You 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?

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Microsoft DP-100 Practice Test 4

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