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Free Microsoft DP-100 Exam Dumps

Here you can find all the free questions related with Microsoft Designing and Implementing a Data Science Solution on Azure (DP-100) exam. You can also find on this page links to recently updated premium files with which you can practice for actual Microsoft Designing and Implementing a Data Science Solution on Azure Exam. These premium versions are provided as DP-100 exam practice tests, both as desktop software and browser based application, you can use whatever suits your style. Feel free to try the Designing and Implementing a Data Science Solution on Azure Exam premium files for free, Good luck with your Microsoft Designing and Implementing a Data Science Solution on Azure Exam.
Question No: 61

Hotspot

You are using a decision tree algorithm. You have trained a model that generalizes well at a tree depth equal to 10.

You need to select the bias and variance properties of the model with varying tree depth values.

Which properties should you select for each tree depth? To answer, select the appropriate options in the answer area.

References:

Question No: 62

DragDrop

You have a model with a large difference between the training and validation error values.

You must create a new model and perform cross-validation.

You need to identify a parameter set for the new model using Azure Machine Learning Studio.

Which module you should use for each step? To answer, drag the appropriate modules to the correct steps. Each module may be used once or 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.

References:

Question No: 63

Hotspot

You have a dataset created for multiclass classification tasks that contains a normalized numerical feature set with 10,000 data points and 150 features.

You use 75 percent of the data points for training and 25 percent for testing. You are using the scikit-learn machine learning library in Python. You use X to denote the feature set and Y to denote class labels.

You create the following Python data frames:

You need to apply the Principal Component Analysis (PCA) method to reduce the dimensionality of the feature set to 10 features in both training and testing sets.

How should you complete the code segment? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

References:

Question No: 64

Hotspot

You have a feature set containing the following numerical features: X, Y, and Z.

The Poisson correlation coefficient (r-value) of X, Y, and Z features is shown in the following image:

Use the drop-down menus to select the answer choice that answers each question based on the information presented in the graphic.

NOTE: Each correct selection is worth one point.

References:

Question No: 65

Hotspot

You are performing feature scaling by using the scikit-learn Python library for x.1 x2, and x3 features.

Original and scaled data is shown in the following image.

Use the drop-down menus to select the answer choice that answers each question based on the information presented in the graphic.

NOTE: Each correct selection is worth one point.

References:

Question No: 66

Hotspot

You are developing a linear regression model in Azure Machine Learning Studio. You run an experiment to compare different algorithms.

The following image displays the results dataset output:

Use the drop-down menus to select the answer choice that answers each question based on the information presented in the image.

NOTE: Each correct selection is worth one point.

References:

Question No: 67

Hotspot

You plan to preprocess text from CSV files. You load the Azure Machine Learning Studio default stop words list.

You need to configure the Preprocess Text module to meet the following requirements:

Ensure that multiple related words from a single canonical form.

Remove pipe characters from text.

Remove words to optimize information retrieval.

Which three options should you select? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

References:

Question No: 68

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.

References:

Question No: 69

Hotspot

You have a Python data frame named salesData in the following format:

The data frame must be unpivoted to a long data format as follows:

You need to use the pandas.melt() function in Python to perform the transformation.

How should you complete the code segment? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

References:

Question No: 70

OrderList

You are creating an experiment by using Azure Machine Learning Studio.

You must divide the data into four subsets for evaluation. There is a high degree of missing values in the dat

a. You must prepare the data for analysis.

You need to select appropriate methods for producing the experiment.

Which three modules should you run in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.

References:


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