Microsoft DP-100 Practice Test - Questions Answers, Page 17

You are training machine learning models in Azure Machine Learning. You use Hyperdrive to tune the hyperparameter.

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 date

Which two early termination policies should you use? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

You use the Azure Machine Learning SDK in a notebook to run an experiment using a script file in an experiment folder.

The experiment fails.

You need to troubleshoot the failed experiment.

What are two possible ways to achieve this goal? Each correct answer presents a complete solution.

You use the Two-Class Neural Network module in Azure Machine Learning Studio to build a binary classification model. You use the Tune Model Hyperparameters module to tune accuracy for the model.

You need to configure the Tune Model Hyperparameters module.

Which two values should you use? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

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 hyperparameters

minimize computing resources required to perform the sweep

You need to perform a parameter sweep of the model.

Which parameter sweep mode should you use?

You are building a recurrent neural network to perform a binary classification.

You review the training loss, validation loss, training accuracy, and validation accuracy for each training epoch.

You need to analyze model performance.

You need to identify whether the classification model is overfitted.

Which of the following is correct?

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 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?

You are performing clustering by using the K-means algorithm.

You need to define the possible termination conditions.

Which three conditions can you use? Each correct answer presents a complete solution.

NOTE: Each correct selection is worth one point.

You 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?

You create a binary classification model.

You need to evaluate the model performance.

Which two metrics can you use? Each correct answer presents a complete solution.

NOTE: Each correct selection is worth one point.