Latest DP-100 Study Guide Help You Clear Microsoft DP-100 Exam Smoothly

Latest DP-100 Study Guide Help You Clear Microsoft DP-100 Exam Smoothly

Are you the one who is planning to take DP-100 Designing and Implementing a Data Science Solution on Azure exam? Latest DP-100 study guide provided by ITExamShop help you clear the Microsoft DP-100 exam smoothly. DP-100 exam is the requirement of Microsoft Certified: Azure Data Scientist Associate certification. Microsoft DP-100 study guide with actual exam questions and answers covering the exam skills measured have been verified and updated, which help you to prepare your DP-100 exam with less effort in very short time. At ITExamShop, you can instant download the latest Microsoft certification DP-100 study guide in pdf file to learn the Q&As easily. We assure you that after using Microsoft DP-100 study guide for DP-100 Designing and Implementing a Data Science Solution on Azure exam, you will pass DP-100 exam successfully.

Before Getting The Full Version OF DP-100 Study Guide, You Can Read DP-100 Free Questions First:

Page 1 of 3

1. You need to select a feature extraction method.

Which method should you use?

2. HOTSPOT

You are working on a classification task. You have a dataset indicating whether a student would like to play soccer and associated attributes.

The dataset includes the following columns:





You need to classify variables by type.

Which variable should you add to each category? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.



3. DRAG DROP

You need to modify the inputs for the global penalty event model to address the bias and variance 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.



4. 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: Calculate the column median value and use the median value as the replacement for any missing value in the column.

Does the solution meet the goal?

5. You need to select a pre built development environment for a series of data science experiments. You must use the R language for the experiments.

Which three environments can you use? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.

6. You need to implement a scaling strategy for the local penalty detection data.

Which normalization type should you use?

7. You need to select a feature extraction method.

Which method should you use?

8. 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?

9. DRAG DROP

You previously deployed a model that was trained using a tabular dataset named training-dataset, which is based on a folder of CSV files.

Over time, you have collected the features and predicted labels generated by the model in a folder containing a CSV file for each month. You have created two tabular datasets based on the folder containing the inference data: one named predictions-dataset with a schema that matches the training data exactly, including the predicted label; and another named features-dataset with a schema containing all of the feature columns and a timestamp column based on the filename, which includes the day, month, and year.

You need to create a data drift monitor to identify any changing trends in the feature data since the model was trained. To accomplish this, you must define the required datasets for the data drift monitor.

Which datasets should you use to configure the data drift monitor? To answer, drag the appropriate datasets to the correct data drift monitor options. Each source may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content. NOTE: Each correct selection is worth one point.



10. HOTSPOT

You need to configure the Edit Metadata module so that the structure of the datasets match.

Which configuration options should you select? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.




 

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