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Microsoft DP-100 Exam Dumps

Exam pack

VENDOR

Microsoft

Exam Code

DP-100

EXAM NAME

Designing and Implementing a Data Science Solution on Azure

TOTAL QUESTIONS

506

RELATED CERTIFICATION

Microsoft Azure Data Scientist Associate Certification

TIME DURATION

100 minutes

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$45

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Exam Q&A

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Question 1

You are building a recurrent neural network (RNN) for a binary classification task. The training loss, validation loss, training accuracy, and validation accuracy for each training epoch are available. You need to determine whether the model is overfitting. Which of the following statements is correct?

Question 2

You plan to run a Python script as an Azure Machine Learning experiment. The script contains the following code: import os, argparse, glob from azureml.core import Run parser = argparse.ArgumentParser() parser.add_argument('--input-data', type=str, dest='data_folder') args = parser.parse_args() data_path = args.data_folder file_paths = glob.glob(data_path + "/*.jpg") You must specify a file dataset as input to the script. The dataset contains large image files and must be streamed directly from its source. You need to write code to define a ScriptRunConfig object for the experiment and pass the dataset (ds) as an argument. Which code segment should you use?

Question 3

You are creating a machine learning model and have a dataset that contains null or missing values. You need to use the Clean Missing Data module in Azure Machine Learning Studio to detect and handle the null and missing values in the dataset. Which parameter should you configure?

Question 4

You need to address a performance issue in your local machine learning pipeline. What should you do?

Question 5

You are a data scientist building a deep convolutional neural network (CNN) for image classification. The CNN model exhibits signs of overfitting. You need to reduce overfitting and help the model converge to an optimal fit. Which two actions should you take? Each correct answer represents a complete solution. Note: Each correct selection is worth one point.