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DP-100 Practice Questions

Question # 1
You need to resolve the local machine learning pipeline performance issue. What should you do?
A. Increase Graphic Processing Units (GPUs).
B. Increase the learning rate.
C. Increase the training iterations,
D. Increase Central Processing Units (CPUs).


A. Increase Graphic Processing Units (GPUs).


Question # 2
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?
A. Multilayer Perceptions (MLPs)
B. Convolutional Neural Networks (CNNs)
C. Recurrent Neural Networks (RNNs)
D. Generative Adversarial Networks (GANs)


C. Recurrent Neural Networks (RNNs)

Explanation:

To translate a corpus of English text to French, we need to build a recurrent neural network (RNN).

Note: RNNs are designed to take sequences of text as inputs or return sequences of text as outputs, or both.

They’re called recurrent because the network’s hidden layers have a loop in which the output and cell state from each time step become inputs at the next time step. This recurrence serves as a form of memory. It allows contextual information to flow through the network so that relevant outputs from previous time steps can be applied to network operations at the current time step.

References:

https://towardsdatascience.com/language-translation-with-rnns-d84d43b40571

Question # 3
You are creating a new experiment in Azure Machine Learning Studio. You have a small dataset that has missing values in many columns. The data does not require the application of predictors for each column. You plan to use the Clean Missing Data module to handle the missing data. You need to select a data cleaning method. Which method should you use?
A. Synthetic Minority Oversampling Technique (SMOTE)
B. Replace using MICE
C. Replace using; Probabilistic PCA
D. Normalization


C. Replace using; Probabilistic PCA

Explanation:

Replace using Probabilistic PCA: Compared to other options, such as Multiple Imputation using Chained Equations (MICE), this option has the advantage of not requiring the application of predictors for each column. Instead, it approximates the covariance for the full dataset. Therefore, it might offer better performance for datasets that have missing values in many columns.

References:

https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/clean-missing-data


Question # 4
You train and publish a machine teaming model. You need to run a pipeline that retrains the model based on a trigger from an external system. What should you configure?
A. Azure Data Catalog
B. Azure Batch
C. Azure logic App


C. Azure logic App


Question # 5
You need to implement a model development strategy to determine a user’s tendency to respond to an ad. Which technique should you use?
A. Use a Relative Expression Split module to partition the data based on centroid distance.
B. Use a Relative Expression Split module to partition the data based on distance travelled to the event.
C. Use a Split Rows module to partition the data based on distance travelled to the event.
D. Use a Split Rows module to partition the data based on centroid distance.


A. Use a Relative Expression Split module to partition the data based on centroid distance.

Explanation:

Split Data partitions the rows of a dataset into two distinct sets.

The Relative Expression Split option in the Split Data module of Azure Machine Learning Studio is helpful when you need to divide a dataset into training and testing datasets using a numerical expression.

Relative Expression Split: Use this option whenever you want to apply a condition to a number column. The number could be a date/time field, a column containing age or dollar amounts, or even a percentage. For example, you might want to divide your data set depending on the cost of the items, group people by age ranges, or separate data by a calendar date.

Scenario:

Local market segmentation models will be applied before determining a user’s propensity to respond to an advertisement.

The distribution of features across training and production data are not consistent

References:

https://docs.microsoft.co m/en-us/azure/machine-learning/studio-module-reference/split-data


Question # 6
You create a Python script that runs a training experiment in Azure Machine Learning. The script uses the Azure Machine Learning SDK for Python. You must add a statement that retrieves the names of the logs and outputs generated by the script. You need to reference a Python class object from the SDK for the statement. Which class object should you use?
A. Run
B. ScripcRunConfig
C. Workspace
D. Experiment


A. Run

Explanation:

A run represents a single trial of an experiment. Runs are used to monitor the asynchronous execution of a trial, log metrics and store output of the trial, and to analyze results and access artifacts generated by the trial.

The run Class get_all_logs method downloads all logs for the run to a directory.

[Reference:, https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.run(class), , ]

Question # 7
You manage an Azure Machine learning workspace. The workspace includes an Azure Machine Learning kubernetes compute target configured as an Azure Kubemetes Service (AKS) cluster named AKS1 AKS1 is configured to enable the targeting of different nodes to train workloads.

You must run a command job on AK51 by using the Azure ML Python SDK v2? The command job must select different types of compute nodes. The compare node types must be specified by using a command parameter.

You need to configure the command parameter.

Which parameter should you use?

A. compute
B. environment
C. instance_type
D. limits
Explanation:

from azure.ai.ml import command

# define the command

command_job = command(

command="python -c "print('Hello world!')"",

environment="AzureML-lightgbm-3.2-ubuntu18.04-py37-cpu@latest",

compute="",

instance_type=""


Question # 8
You use Azure Machine Learning studio to analyze an mltable data asset containing a decimal column named column1. You need to verify that the column1 values are normally distributed. Which statistic should you use?
A. Max
B. Type
C. Profile
D. Mean


C. Profile


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Microsoft DP-100 Exam Dumps

Exam Name: Designing and Implementing a Data Science Solution on Azure Exam
Certification Name: Microsoft Azure

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