{"id":110248,"date":"2025-09-12T06:47:14","date_gmt":"2025-09-12T06:47:14","guid":{"rendered":"https:\/\/www.dumpsbase.com\/freedumps\/?p=110248"},"modified":"2025-10-03T03:42:56","modified_gmt":"2025-10-03T03:42:56","slug":"updated-the-dp-100-dumps-to-v23-02-for-microsoft-exam-preparation-begin-with-our-dp-100-free-dumps-part-1-q1-q40","status":"publish","type":"post","link":"https:\/\/www.dumpsbase.com\/freedumps\/updated-the-dp-100-dumps-to-v23-02-for-microsoft-exam-preparation-begin-with-our-dp-100-free-dumps-part-1-q1-q40.html","title":{"rendered":"Updated the DP-100 Dumps to V23.02 for Microsoft Exam Preparation: Begin with our DP-100 Free Dumps (Part 1, Q1-Q40)"},"content":{"rendered":"<p>DumpsBase has updated the Microsoft DP-100 dumps to V23.02 for the Designing and Implementing a Data Science Solution on Azure exam preparation, so you can practice with authentic and up-to-date exam questions, improving both speed and accuracy. In this new version, we have set 506 practice exam questions and answers to help you identify mistakes, track improvement, and gradually build the confidence needed to pass the real Microsoft DP-100 exam. All these questions are directly aligned with official objectives. Learning with DumpsBase\u2019s DP-100 dumps (V23.02) will strengthen your subject knowledge and teach you how to manage time, minimize stress, and answer questions efficiently. Begin with our free dumps today, you can verify the most current DP-100 dumps (V23.02) before downloading the materials for preparation.<\/p>\n<h2>Microsoft <span style=\"background-color: #99ccff;\"><em>DP-100 free dumps (Part 1, Q1-Q40) of V23.02 are below<\/em><\/span> for reading first:<\/h2>\n<script>\n\t  window.fbAsyncInit = function() {\n\t    FB.init({\n\t      appId            : '622169541470367',\n\t      autoLogAppEvents : true,\n\t      xfbml            : true,\n\t      version          : 'v3.1'\n\t    });\n\t  };\n\t\n\t  (function(d, s, id){\n\t     var js, fjs = d.getElementsByTagName(s)[0];\n\t     if (d.getElementById(id)) {return;}\n\t     js = d.createElement(s); js.id = id;\n\t     js.src = \"https:\/\/connect.facebook.net\/en_US\/sdk.js\";\n\t     fjs.parentNode.insertBefore(js, fjs);\n\t   }(document, 'script', 'facebook-jssdk'));\n\t<\/script><script type=\"text\/javascript\" >\ndocument.addEventListener(\"DOMContentLoaded\", function(event) { \nif(!window.jQuery) alert(\"The important jQuery library is not properly loaded in your site. Your WordPress theme is probably missing the essential wp_head() call. You can switch to another theme and you will see that the plugin works fine and this notice disappears. If you are still not sure what to do you can contact us for help.\");\n});\n<\/script>  \n  \n<div  id=\"watupro_quiz\" class=\"quiz-area single-page-quiz\">\n<p id=\"submittingExam10805\" style=\"display:none;text-align:center;\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/plugins\/watupro\/img\/loading.gif\" width=\"16\" height=\"16\"><\/p>\n\n<div class=\"watupro-exam-description\" id=\"description-quiz-10805\"><\/div>\n\n<form action=\"\" method=\"post\" class=\"quiz-form\" id=\"quiz-10805\"  enctype=\"multipart\/form-data\" >\n<div class='watu-question ' id='question-1' style=';'><div id='questionWrap-1'  class='   watupro-question-id-426474'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>1. <\/span>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. <br \/>\r<br>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. <br \/>\r<br>You are using Azure Machine Learning Studio to perform feature engineering on a dataset. <br \/>\r<br>You need to normalize values to produce a feature column grouped into bins. <br \/>\r<br>Solution: Apply an Entropy Minimum Description Length (MDL) binning mode. <br \/>\r<br>Does the solution meet the goal?<\/div><input type='hidden' name='question_id[]' id='qID_1' value='426474' \/><input type='hidden' id='answerType426474' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426474[]' id='answer-id-1650923' class='answer   answerof-426474 ' value='1650923'   \/><label for='answer-id-1650923' id='answer-label-1650923' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426474[]' id='answer-id-1650924' class='answer   answerof-426474 ' value='1650924'   \/><label for='answer-id-1650924' id='answer-label-1650924' class=' answer'><span>No<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-2' style=';'><div id='questionWrap-2'  class='   watupro-question-id-426475'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>2. <\/span>You create a classification model with a dataset that contains 100 samples with Class A and 10,000 samples with Class B <br \/>\r<br>The variation of Class B is very high. <br \/>\r<br>You need to resolve imbalances. <br \/>\r<br>Which method should you use?<\/div><input type='hidden' name='question_id[]' id='qID_2' value='426475' \/><input type='hidden' id='answerType426475' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426475[]' id='answer-id-1650925' class='answer   answerof-426475 ' value='1650925'   \/><label for='answer-id-1650925' id='answer-label-1650925' class=' answer'><span>Partition and Sample<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426475[]' id='answer-id-1650926' class='answer   answerof-426475 ' value='1650926'   \/><label for='answer-id-1650926' id='answer-label-1650926' class=' answer'><span>Cluster Centroids<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426475[]' id='answer-id-1650927' class='answer   answerof-426475 ' value='1650927'   \/><label for='answer-id-1650927' id='answer-label-1650927' class=' answer'><span>Tomek links<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426475[]' id='answer-id-1650928' class='answer   answerof-426475 ' value='1650928'   \/><label for='answer-id-1650928' id='answer-label-1650928' class=' answer'><span>Synthetic Minority Oversampling Technique (SMOTE)<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-3' style=';'><div id='questionWrap-3'  class='   watupro-question-id-426476'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>3. <\/span>You are determining if two sets of data are significantly different from one another by using Azure Machine Learning Studio. <br \/>\r<br>Estimated values in one set of data may be more than or less than reference values in the other set of data. You must produce a distribution that has a constant Type I error as a function of the correlation. <br \/>\r<br>You need to produce the distribution. <br \/>\r<br>Which type of distribution should you produce?<\/div><input type='hidden' name='question_id[]' id='qID_3' value='426476' \/><input type='hidden' id='answerType426476' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426476[]' id='answer-id-1650929' class='answer   answerof-426476 ' value='1650929'   \/><label for='answer-id-1650929' id='answer-label-1650929' class=' answer'><span>Paired t-test with a two-tail option<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426476[]' id='answer-id-1650930' class='answer   answerof-426476 ' value='1650930'   \/><label for='answer-id-1650930' id='answer-label-1650930' class=' answer'><span>Unpaired t-test with a two tail option<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426476[]' id='answer-id-1650931' class='answer   answerof-426476 ' value='1650931'   \/><label for='answer-id-1650931' id='answer-label-1650931' class=' answer'><span>Paired t-test with a one-tail option<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426476[]' id='answer-id-1650932' class='answer   answerof-426476 ' value='1650932'   \/><label for='answer-id-1650932' id='answer-label-1650932' class=' answer'><span>Unpaired t-test with a one-tail option<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-4' style=';'><div id='questionWrap-4'  class='   watupro-question-id-426477'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>4. <\/span>You are a data scientist creating a linear regression model. <br \/>\r<br>You need to determine how closely the data fits the regression line. <br \/>\r<br>Which metric should you review?<\/div><input type='hidden' name='question_id[]' id='qID_4' value='426477' \/><input type='hidden' id='answerType426477' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426477[]' id='answer-id-1650933' class='answer   answerof-426477 ' value='1650933'   \/><label for='answer-id-1650933' id='answer-label-1650933' class=' answer'><span>Coefficient of determination<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426477[]' id='answer-id-1650934' class='answer   answerof-426477 ' value='1650934'   \/><label for='answer-id-1650934' id='answer-label-1650934' class=' answer'><span>Recall<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426477[]' id='answer-id-1650935' class='answer   answerof-426477 ' value='1650935'   \/><label for='answer-id-1650935' id='answer-label-1650935' class=' answer'><span>Precision<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426477[]' id='answer-id-1650936' class='answer   answerof-426477 ' value='1650936'   \/><label for='answer-id-1650936' id='answer-label-1650936' class=' answer'><span>Mean absolute error<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426477[]' id='answer-id-1650937' class='answer   answerof-426477 ' value='1650937'   \/><label for='answer-id-1650937' id='answer-label-1650937' class=' answer'><span>Root Mean Square Error<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-5' style=';'><div id='questionWrap-5'  class='   watupro-question-id-426478'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>5. <\/span>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. <br \/>\r<br>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. <br \/>\r<br>You are a data scientist using Azure Machine Learning Studio. <br \/>\r<br>You need to normalize values to produce an output column into bins to predict a target column. <br \/>\r<br>Solution: Apply a Quantiles binning mode with a PQuantile normalization. <br \/>\r<br>Does the solution meet the goal?<\/div><input type='hidden' name='question_id[]' id='qID_5' value='426478' \/><input type='hidden' id='answerType426478' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426478[]' id='answer-id-1650938' class='answer   answerof-426478 ' value='1650938'   \/><label for='answer-id-1650938' id='answer-label-1650938' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426478[]' id='answer-id-1650939' class='answer   answerof-426478 ' value='1650939'   \/><label for='answer-id-1650939' id='answer-label-1650939' class=' answer'><span>No<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-6' style=';'><div id='questionWrap-6'  class='   watupro-question-id-426479'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>6. <\/span>DRAG DROP <br \/>\r<br>You have a dataset that contains over 150 features. You use the dataset to train a Support Vector Machine (SVM) binary classifier. <br \/>\r<br>You need to use the Permutation Feature Importance module in Azure Machine Learning Studio to compute a set of feature importance scores for the dataset. <br \/>\r<br>In which order should you perform the actions? To answer, move all actions from the list of actions to the answer area and arrange them in the correct order. <br \/>\r<br><br><img decoding=\"async\" width=649 height=275 id=\"\u56fe\u7247 203\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2025\/09\/image046.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_6' value='426479' \/><input type='hidden' id='answerType426479' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-426479[]' id='textarea_q_426479' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-7' style=';'><div id='questionWrap-7'  class='   watupro-question-id-426480'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>7. <\/span>You need to implement a new cost factor scenario for the ad response models as illustrated in the <br \/>\r<br>performance curve exhibit. <br \/>\r<br>Which technique should you use?<\/div><input type='hidden' name='question_id[]' id='qID_7' value='426480' \/><input type='hidden' id='answerType426480' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426480[]' id='answer-id-1650941' class='answer   answerof-426480 ' value='1650941'   \/><label for='answer-id-1650941' id='answer-label-1650941' class=' answer'><span>Set the threshold to 0.5 and retrain if weighted Kappa deviates +\/- 5% from 0.45.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426480[]' id='answer-id-1650942' class='answer   answerof-426480 ' value='1650942'   \/><label for='answer-id-1650942' id='answer-label-1650942' class=' answer'><span>Set the threshold to 0.05 and retrain if weighted Kappa deviates +\/- 5% from 0.5.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426480[]' id='answer-id-1650943' class='answer   answerof-426480 ' value='1650943'   \/><label for='answer-id-1650943' id='answer-label-1650943' class=' answer'><span>Set the threshold to 0.2 and retrain if weighted Kappa deviates +\/- 5% from 0.6.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426480[]' id='answer-id-1650944' class='answer   answerof-426480 ' value='1650944'   \/><label for='answer-id-1650944' id='answer-label-1650944' class=' answer'><span>Set the threshold to 0.75 and retrain if weighted Kappa deviates +\/- 5% from 0.15.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-8' style=';'><div id='questionWrap-8'  class='   watupro-question-id-426481'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>8. <\/span>You are developing a data science workspace that uses an Azure Machine Learning service. <br \/>\r<br>You need to select a compute target to deploy the workspace. <br \/>\r<br>What should you use?<\/div><input type='hidden' name='question_id[]' id='qID_8' value='426481' \/><input type='hidden' id='answerType426481' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426481[]' id='answer-id-1650945' class='answer   answerof-426481 ' value='1650945'   \/><label for='answer-id-1650945' id='answer-label-1650945' class=' answer'><span>Azure Data Lake Analytics<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426481[]' id='answer-id-1650946' class='answer   answerof-426481 ' value='1650946'   \/><label for='answer-id-1650946' id='answer-label-1650946' class=' answer'><span>Azure Databrick .<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426481[]' id='answer-id-1650947' class='answer   answerof-426481 ' value='1650947'   \/><label for='answer-id-1650947' id='answer-label-1650947' class=' answer'><span>Apache Spark for HDInsight.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426481[]' id='answer-id-1650948' class='answer   answerof-426481 ' value='1650948'   \/><label for='answer-id-1650948' id='answer-label-1650948' class=' answer'><span>Azure Container Service<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-9' style=';'><div id='questionWrap-9'  class='   watupro-question-id-426482'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>9. <\/span>HOTSPOT <br \/>\r<br>You create a binary classification model using Azure Machine Learning Studio. <br \/>\r<br>You must use a Receiver Operating Characteristic (RO C) curve and an F1 score to evaluate the model. <br \/>\r<br>You need to create the required business metrics. <br \/>\r<br>How should you complete the experiment? To answer, select the appropriate options in the dialog box in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=649 height=401 id=\"\u56fe\u7247 166\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2025\/09\/image072.jpg\"><br><br \/>\r<br><br><img decoding=\"async\" width=564 height=347 id=\"\u56fe\u7247 167\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2025\/09\/image073.png\"><br><\/div><input type='hidden' name='question_id[]' id='qID_9' value='426482' \/><input type='hidden' id='answerType426482' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-426482[]' id='textarea_q_426482' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-10' style=';'><div id='questionWrap-10'  class='   watupro-question-id-426483'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>10. <\/span>HOTSPOT <br \/>\r<br>You have a dataset that contains 2,000 rows. You are building a machine learning classification model by using Azure Learning Studio. You add a Partition and Sample module to the experiment. <br \/>\r<br>You need to configure the module. <br \/>\r<br>You must meet the following requirements: <br \/>\r<br>&#10001; Divide the data into subsets <br \/>\r<br>&#10001; Assign the rows into folds using a round-robin method <br \/>\r<br>&#10001; Allow rows in the dataset to be reused <br \/>\r<br>How should you configure the module? To answer, select the appropriate options in the dialog box in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=563 height=251 id=\"\u56fe\u7247 321\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2025\/09\/image064.png\"><br><\/div><input type='hidden' name='question_id[]' id='qID_10' value='426483' \/><input type='hidden' id='answerType426483' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-426483[]' id='textarea_q_426483' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-11' style=';'><div id='questionWrap-11'  class='   watupro-question-id-426484'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>11. <\/span>HOTSPOT <br \/>\r<br>You need to use the Python language to build a sampling strategy for the global penalty detection models. <br \/>\r<br>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. <br \/>\r<br><br><img decoding=\"async\" width=650 height=614 id=\"\u56fe\u7247 16\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2025\/09\/image014.png\"><br><\/div><input type='hidden' name='question_id[]' id='qID_11' value='426484' \/><input type='hidden' id='answerType426484' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-426484[]' id='textarea_q_426484' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-12' style=';'><div id='questionWrap-12'  class='   watupro-question-id-426485'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>12. <\/span>HOTSPOT <br \/>\r<br>You are working on a classification task. You have a dataset indicating whether a student would like to play soccer and associated attributes. <br \/>\r<br>The dataset includes the following columns: <br \/>\r<br><br><img decoding=\"async\" width=367 height=115 id=\"\u56fe\u7247 235\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2025\/09\/image093.png\"><br><br \/>\r<br>You need to classify variables by type. <br \/>\r<br>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. <br \/>\r<br><br><img decoding=\"async\" width=509 height=339 id=\"\u56fe\u7247 236\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2025\/09\/image094.png\"><br><\/div><input type='hidden' name='question_id[]' id='qID_12' value='426485' \/><input type='hidden' id='answerType426485' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-426485[]' id='textarea_q_426485' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-13' style=';'><div id='questionWrap-13'  class='   watupro-question-id-426486'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>13. <\/span>DRAG DROP <br \/>\r<br>You need to define a process for penalty event detection. <br \/>\r<br>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. <br \/>\r<br><br><img decoding=\"async\" width=649 height=282 id=\"\u56fe\u7247 6\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2025\/09\/image008-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_13' value='426486' \/><input type='hidden' id='answerType426486' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-426486[]' id='textarea_q_426486' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-14' style=';'><div id='questionWrap-14'  class='   watupro-question-id-426487'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>14. <\/span>DRAG DROP <br \/>\r<br>You need to define a process for penalty event detection. <br \/>\r<br>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. <br \/>\r<br><br><img decoding=\"async\" width=649 height=545 id=\"\u56fe\u7247 10\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2025\/09\/image006-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_14' value='426487' \/><input type='hidden' id='answerType426487' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-426487[]' id='textarea_q_426487' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-15' style=';'><div id='questionWrap-15'  class='   watupro-question-id-426488'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>15. <\/span>You are with a time series dataset in Azure Machine Learning Studio. <br \/>\r<br>You need to split your dataset into training and testing subsets by using the Split Data module. <br \/>\r<br>Which splitting mode should you use?<\/div><input type='hidden' name='question_id[]' id='qID_15' value='426488' \/><input type='hidden' id='answerType426488' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426488[]' id='answer-id-1650955' class='answer   answerof-426488 ' value='1650955'   \/><label for='answer-id-1650955' id='answer-label-1650955' class=' answer'><span>Regular Expression Split<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426488[]' id='answer-id-1650956' class='answer   answerof-426488 ' value='1650956'   \/><label for='answer-id-1650956' id='answer-label-1650956' class=' answer'><span>Split Rows with the Randomized split parameter set to true<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426488[]' id='answer-id-1650957' class='answer   answerof-426488 ' value='1650957'   \/><label for='answer-id-1650957' id='answer-label-1650957' class=' answer'><span>Relative Expression Split<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426488[]' id='answer-id-1650958' class='answer   answerof-426488 ' value='1650958'   \/><label for='answer-id-1650958' id='answer-label-1650958' class=' answer'><span>Recommender Split<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-16' style=';'><div id='questionWrap-16'  class='   watupro-question-id-426489'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>16. <\/span>You need to implement a model development strategy to determine a user\u2019s tendency to respond to an ad. <br \/>\r<br>Which technique should you use?<\/div><input type='hidden' name='question_id[]' id='qID_16' value='426489' \/><input type='hidden' id='answerType426489' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426489[]' id='answer-id-1650959' class='answer   answerof-426489 ' value='1650959'   \/><label for='answer-id-1650959' id='answer-label-1650959' class=' answer'><span>Use a Relative Expression Split module to partition the data based on centroid distance.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426489[]' id='answer-id-1650960' class='answer   answerof-426489 ' value='1650960'   \/><label for='answer-id-1650960' id='answer-label-1650960' class=' answer'><span>Use a Relative Expression Split module to partition the data based on distance travelled to the event.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426489[]' id='answer-id-1650961' class='answer   answerof-426489 ' value='1650961'   \/><label for='answer-id-1650961' id='answer-label-1650961' class=' answer'><span>Use a Split Rows module to partition the data based on distance travelled to the event.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426489[]' id='answer-id-1650962' class='answer   answerof-426489 ' value='1650962'   \/><label for='answer-id-1650962' id='answer-label-1650962' class=' answer'><span>Use a Split Rows module to partition the data based on centroid distance.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-17' style=';'><div id='questionWrap-17'  class='   watupro-question-id-426490'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>17. <\/span>Topic 3, Mix Questions <br \/>\r<br><br \/>\r<br>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. <br \/>\r<br>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. <br \/>\r<br>You are analyzing a numerical dataset which contains missing values in several columns. <br \/>\r<br>You must clean the missing values using an appropriate operation without affecting the dimensionality of the feature set. <br \/>\r<br>You need to analyze a full dataset to include all values. <br \/>\r<br>Solution: Replace each missing value using the Multiple Imputation by Chained Equations (MICE) method. <br \/>\r<br>Does the solution meet the goal?<\/div><input type='hidden' name='question_id[]' id='qID_17' value='426490' \/><input type='hidden' id='answerType426490' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426490[]' id='answer-id-1650963' class='answer   answerof-426490 ' value='1650963'   \/><label for='answer-id-1650963' id='answer-label-1650963' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426490[]' id='answer-id-1650964' class='answer   answerof-426490 ' value='1650964'   \/><label for='answer-id-1650964' id='answer-label-1650964' class=' answer'><span>NO<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-18' style=';'><div id='questionWrap-18'  class='   watupro-question-id-426491'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>18. <\/span>HOTSPOT <br \/>\r<br>You need to identify the methods for dividing the data according to the testing requirements. <br \/>\r<br>Which properties should you select? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=443 height=888 id=\"\u56fe\u7247 38\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2025\/09\/image042.png\"><br><\/div><input type='hidden' name='question_id[]' id='qID_18' value='426491' \/><input type='hidden' id='answerType426491' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-426491[]' id='textarea_q_426491' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-19' style=';'><div id='questionWrap-19'  class='   watupro-question-id-426492'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>19. <\/span>You are creating a binary classification by using a two-class logistic regression model. <br \/>\r<br>You need to evaluate the model results for imbalance. <br \/>\r<br>Which evaluation metric should you use?<\/div><input type='hidden' name='question_id[]' id='qID_19' value='426492' \/><input type='hidden' id='answerType426492' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426492[]' id='answer-id-1650966' class='answer   answerof-426492 ' value='1650966'   \/><label for='answer-id-1650966' id='answer-label-1650966' class=' answer'><span>Relative Absolute Error<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426492[]' id='answer-id-1650967' class='answer   answerof-426492 ' value='1650967'   \/><label for='answer-id-1650967' id='answer-label-1650967' class=' answer'><span>AUC Curve<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426492[]' id='answer-id-1650968' class='answer   answerof-426492 ' value='1650968'   \/><label for='answer-id-1650968' id='answer-label-1650968' class=' answer'><span>Mean Absolute Error<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426492[]' id='answer-id-1650969' class='answer   answerof-426492 ' value='1650969'   \/><label for='answer-id-1650969' id='answer-label-1650969' class=' answer'><span>Relative Squared Error<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-20' style=';'><div id='questionWrap-20'  class='   watupro-question-id-426493'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>20. <\/span>HOTSPOT <br \/>\r<br>You create a binary classification model to predict whether a person has a disease. <br \/>\r<br>You need to detect possible classification errors. <br \/>\r<br>Which error type should you choose for each description? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=649 height=663 id=\"\u56fe\u7247 209\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2025\/09\/image050.png\"><br><\/div><input type='hidden' name='question_id[]' id='qID_20' value='426493' \/><input type='hidden' id='answerType426493' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-426493[]' id='textarea_q_426493' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-21' style=';'><div id='questionWrap-21'  class='   watupro-question-id-426494'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>21. <\/span>You are evaluating a completed binary classification machine. <br \/>\r<br>You need to use the precision as the evaluation metric. <br \/>\r<br>Which visualization should you use?<\/div><input type='hidden' name='question_id[]' id='qID_21' value='426494' \/><input type='hidden' id='answerType426494' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426494[]' id='answer-id-1650971' class='answer   answerof-426494 ' value='1650971'   \/><label for='answer-id-1650971' id='answer-label-1650971' class=' answer'><span>scatter plot<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426494[]' id='answer-id-1650972' class='answer   answerof-426494 ' value='1650972'   \/><label for='answer-id-1650972' id='answer-label-1650972' class=' answer'><span>coefficient of determination<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426494[]' id='answer-id-1650973' class='answer   answerof-426494 ' value='1650973'   \/><label for='answer-id-1650973' id='answer-label-1650973' class=' answer'><span>Receiver Operating Characteristic CROC) curve<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426494[]' id='answer-id-1650974' class='answer   answerof-426494 ' value='1650974'   \/><label for='answer-id-1650974' id='answer-label-1650974' class=' answer'><span>Gradient descent<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-22' style=';'><div id='questionWrap-22'  class='   watupro-question-id-426495'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>22. <\/span>You are analyzing a dataset by using Azure Machine Learning Studio. <br \/>\r<br>YOU need to generate a statistical summary that contains the p value and the unique value count for each feature column. <br \/>\r<br>Which two modules can you users? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.<\/div><input type='hidden' name='question_id[]' id='qID_22' value='426495' \/><input type='hidden' id='answerType426495' value='checkbox'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-426495[]' id='answer-id-1650975' class='answer   answerof-426495 ' value='1650975'   \/><label for='answer-id-1650975' id='answer-label-1650975' class=' answer'><span>Execute Python Script<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-426495[]' id='answer-id-1650976' class='answer   answerof-426495 ' value='1650976'   \/><label for='answer-id-1650976' id='answer-label-1650976' class=' answer'><span>Export Count Table<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-426495[]' id='answer-id-1650977' class='answer   answerof-426495 ' value='1650977'   \/><label for='answer-id-1650977' id='answer-label-1650977' class=' answer'><span>Convert to Indicator Values<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-426495[]' id='answer-id-1650978' class='answer   answerof-426495 ' value='1650978'   \/><label for='answer-id-1650978' id='answer-label-1650978' class=' answer'><span>Summarize Data<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-426495[]' id='answer-id-1650979' class='answer   answerof-426495 ' value='1650979'   \/><label for='answer-id-1650979' id='answer-label-1650979' class=' answer'><span>Compute linear Correlation<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-23' style=';'><div id='questionWrap-23'  class='   watupro-question-id-426496'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>23. <\/span>You train a machine learning model. <br \/>\r<br>You must deploy the model as a real-time inference service for testing. The service requires low CPU utilization and less than 48 MB of RAM. The compute target for the deployed service must initialize automatically while minimizing cost and administrative overhead. <br \/>\r<br>Which compute target should you use?<\/div><input type='hidden' name='question_id[]' id='qID_23' value='426496' \/><input type='hidden' id='answerType426496' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426496[]' id='answer-id-1650980' class='answer   answerof-426496 ' value='1650980'   \/><label for='answer-id-1650980' id='answer-label-1650980' class=' answer'><span>Azure Kubernetes Service (AKS) inference cluster<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426496[]' id='answer-id-1650981' class='answer   answerof-426496 ' value='1650981'   \/><label for='answer-id-1650981' id='answer-label-1650981' class=' answer'><span>Azure Machine Learning compute cluster<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426496[]' id='answer-id-1650982' class='answer   answerof-426496 ' value='1650982'   \/><label for='answer-id-1650982' id='answer-label-1650982' class=' answer'><span>Azure Container Instance (ACI)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426496[]' id='answer-id-1650983' class='answer   answerof-426496 ' value='1650983'   \/><label for='answer-id-1650983' id='answer-label-1650983' class=' answer'><span>attached Azure Databricks cluster<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-24' style=';'><div id='questionWrap-24'  class='   watupro-question-id-426497'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>24. <\/span>DRAG DROP <br \/>\r<br>You need to define a modeling strategy for ad response. <br \/>\r<br>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. <br \/>\r<br><br><img decoding=\"async\" width=650 height=336 id=\"\u56fe\u7247 19\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2025\/09\/image016.png\"><br><\/div><input type='hidden' name='question_id[]' id='qID_24' value='426497' \/><input type='hidden' id='answerType426497' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-426497[]' id='textarea_q_426497' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-25' style=';'><div id='questionWrap-25'  class='   watupro-question-id-426498'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>25. <\/span>DRAG DROP <br \/>\r<br>You need to define an evaluation strategy for the crowd sentiment models. <br \/>\r<br>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. <br \/>\r<br><br><img decoding=\"async\" width=650 height=397 id=\"\u56fe\u7247 4\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2025\/09\/image010.png\"><br><\/div><input type='hidden' name='question_id[]' id='qID_25' value='426498' \/><input type='hidden' id='answerType426498' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-426498[]' id='textarea_q_426498' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-26' style=';'><div id='questionWrap-26'  class='   watupro-question-id-426499'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>26. <\/span>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. <br \/>\r<br>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. <br \/>\r<br>You are creating a new experiment in Azure Machine Learning Studio. <br \/>\r<br>One class has a much smaller number of observations than the other classes in the training set. <br \/>\r<br>You need to select an appropriate data sampling strategy to compensate for the class imbalance. <br \/>\r<br>Solution: You use the Stratified split for the sampling mode. <br \/>\r<br>Does the solution meet the goal?<\/div><input type='hidden' name='question_id[]' id='qID_26' value='426499' \/><input type='hidden' id='answerType426499' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426499[]' id='answer-id-1650986' class='answer   answerof-426499 ' value='1650986'   \/><label for='answer-id-1650986' id='answer-label-1650986' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426499[]' id='answer-id-1650987' class='answer   answerof-426499 ' value='1650987'   \/><label for='answer-id-1650987' id='answer-label-1650987' class=' answer'><span>No<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-27' style=';'><div id='questionWrap-27'  class='   watupro-question-id-426500'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>27. <\/span>Topic 2, Case Study 2 <br \/>\r<br><br \/>\r<br>Case study <br \/>\r<br>Overview <br \/>\r<br>You are a data scientist for Fabrikam Residences, a company specializing in quality private and commercial property in the United States. Fabrikam Residences is considering expanding into Europe and has asked you to investigate prices for private residences in major European cities. You use Azure Machine Learning Studio to measure the median value of properties. You produce a regression model to predict property prices by using the Linear Regression and Bayesian Linear Regression modules. <br \/>\r<br><br \/>\r<br>Datasets <br \/>\r<br>There are two datasets in CSV format that contain property details for two cities, London and Paris, with the following columns: <br \/>\r<br><br><img decoding=\"async\" width=615 height=310 id=\"\u56fe\u7247 43\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2025\/09\/image021.png\"><br><br \/>\r<br><br \/>\r<br>The two datasets have been added to Azure Machine Learning Studio as separate datasets and included as the starting point of the experiment. <br \/>\r<br><br \/>\r<br>Dataset issues <br \/>\r<br>The AccessibilityToHighway column in both datasets contains missing values. The missing data must be replaced with new data so that it is modeled conditionally using the other variables in the data before filling in the missing values. <br \/>\r<br>Columns in each dataset contain missing and null values. The dataset also contains many outliers. The Age column has a high proportion of outliers. You need to remove the rows that have outliers in the Age column. The MedianValue and AvgRoomsinHouse columns both hold data in numeric format. You need to select a feature selection algorithm to analyze the relationship between the two columns in more detail. <br \/>\r<br><br \/>\r<br>Model fit <br \/>\r<br>The model shows signs of overfitting. You need to produce a more refined regression model that reduces the overfitting. <br \/>\r<br><br \/>\r<br>Experiment requirements <br \/>\r<br>You must set up the experiment to cross-validate the Linear Regression and Bayesian Linear Regression modules to evaluate performance. <br \/>\r<br><br \/>\r<br>In each case, the predictor of the dataset is the column named MedianValue. An initial investigation showed that the datasets are identical in structure apart from the MedianValue column. The smaller Paris dataset contains the MedianValue in text format, whereas the larger London dataset contains the MedianValue in numerical format. You must ensure that the datatype of the MedianValue column of the Paris dataset matches the structure of the London dataset. <br \/>\r<br><br \/>\r<br>You must prioritize the columns of data for predicting the outcome. You must use non-parameters statistics to measure the relationships. <br \/>\r<br><br \/>\r<br>You must use a feature selection algorithm to analyze the relationship between the MedianValue and AvgRoomsinHouse columns. <br \/>\r<br><br \/>\r<br>Model training <br \/>\r<br>Given a trained model and a test dataset, you need to compute the permutation feature importance scores of feature variables. You need to set up the Permutation Feature Importance module to select the correct metric to investigate the model\u2019s accuracy and replicate the findings. <br \/>\r<br>You want to configure hyperparameters in the model learning process to speed the learning phase by using hyperparameters. In addition, this configuration should cancel the lowest performing runs at each evaluation interval, thereby directing effort and resources towards models that are more likely to be successful. <br \/>\r<br><br \/>\r<br>You are concerned that the model might not efficiently use compute resources in hyperparameter tuning. You also are concerned that the model might prevent an increase in the overall tuning time. Therefore, you need to implement an early stopping criterion on models that provides savings without terminating promising jobs. <br \/>\r<br><br \/>\r<br>Testing <br \/>\r<br>You must produce multiple partitions of a dataset based on sampling using the Partition and Sample module in Azure Machine Learning Studio. You must create three equal partitions for cross-validation. You must also configure the cross-validation process so that the rows in the test and training datasets are divided evenly by properties that are near each city\u2019s main river. The data that identifies that a property is near a river is held in the column named NextToRiver. You want to complete this task before the data goes through the sampling process. <br \/>\r<br><br \/>\r<br>When you train a Linear Regression module using a property dataset that shows data for property prices for a large city, you need to determine the best features to use in a model. You can choose standard metrics provided to measure performance before and after the feature importance process completes. You must ensure that the distribution of the features across multiple training models is consistent. <br \/>\r<br><br \/>\r<br>Data visualization <br \/>\r<br>You need to provide the test results to the Fabrikam Residences team. You create data visualizations to aid in presenting the results. <br \/>\r<br>You must produce a Receiver Operating Characteristic (ROC) curve to conduct a <br \/>\r<br>diagnostic test evaluation of the model. You need to select appropriate methods for producing the ROC curve in Azure Machine Learning Studio to compare the Two-Class Decision Forest and the Two-Class Decision Jungle modules with one another. <br \/>\r<br><br \/>\r<br>DRAG DROP <br \/>\r<br>You need to implement early stopping criteria as suited in the model training requirements. <br \/>\r<br>Which three code segments should you use to develop the solution? To answer, move the appropriate code segments from the list of code segments 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. <br \/>\r<br><br><img decoding=\"async\" width=649 height=301 id=\"\u56fe\u7247 26\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2025\/09\/image022.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_27' value='426500' \/><input type='hidden' id='answerType426500' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-426500[]' id='textarea_q_426500' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-28' style=';'><div id='questionWrap-28'  class='   watupro-question-id-426501'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>28. <\/span>You need to select an environment that will meet the business and data requirements. <br \/>\r<br>Which environment should you use?<\/div><input type='hidden' name='question_id[]' id='qID_28' value='426501' \/><input type='hidden' id='answerType426501' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426501[]' id='answer-id-1650989' class='answer   answerof-426501 ' value='1650989'   \/><label for='answer-id-1650989' id='answer-label-1650989' class=' answer'><span>Azure HDInsight with Spark MLlib<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426501[]' id='answer-id-1650990' class='answer   answerof-426501 ' value='1650990'   \/><label for='answer-id-1650990' id='answer-label-1650990' class=' answer'><span>Azure Cognitive Services<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426501[]' id='answer-id-1650991' class='answer   answerof-426501 ' value='1650991'   \/><label for='answer-id-1650991' id='answer-label-1650991' class=' answer'><span>Azure Machine Learning Studio<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426501[]' id='answer-id-1650992' class='answer   answerof-426501 ' value='1650992'   \/><label for='answer-id-1650992' id='answer-label-1650992' class=' answer'><span>Microsoft Machine Learning Server<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-29' style=';'><div id='questionWrap-29'  class='   watupro-question-id-426502'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>29. <\/span>HOTSPOT <br \/>\r<br>You are using C-Support Vector classification to do a multi-class classification with an unbalanced training dataset. <br \/>\r<br>The C-Support Vector classification using Python code shown below: <br \/>\r<br><br><img decoding=\"async\" width=650 height=92 id=\"\u56fe\u7247 315\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2025\/09\/image116.jpg\"><br><br \/>\r<br>You need to evaluate the C-Support Vector classification code. <br \/>\r<br>Which evaluation statement should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=649 height=225 id=\"\u56fe\u7247 316\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2025\/09\/image117.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_29' value='426502' \/><input type='hidden' id='answerType426502' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-426502[]' id='textarea_q_426502' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-30' style=';'><div id='questionWrap-30'  class='   watupro-question-id-426503'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>30. <\/span>You are implementing a machine learning model to predict stock prices. <br \/>\r<br>The model uses a PostgreSQL database and requires GPU processing. <br \/>\r<br>You need to create a virtual machine that is pre-configured with the required tools. <br \/>\r<br>What should you do?<\/div><input type='hidden' name='question_id[]' id='qID_30' value='426503' \/><input type='hidden' id='answerType426503' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426503[]' id='answer-id-1650994' class='answer   answerof-426503 ' value='1650994'   \/><label for='answer-id-1650994' id='answer-label-1650994' class=' answer'><span>Create a Data Science Virtual Machine (DSVM) Windows edition.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426503[]' id='answer-id-1650995' class='answer   answerof-426503 ' value='1650995'   \/><label for='answer-id-1650995' id='answer-label-1650995' class=' answer'><span>Create a Geo Al Data Science Virtual Machine (Geo-DSVM) Windows edition.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426503[]' id='answer-id-1650996' class='answer   answerof-426503 ' value='1650996'   \/><label for='answer-id-1650996' id='answer-label-1650996' class=' answer'><span>Create a Deep Learning Virtual Machine (DLVM) Linux edition.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426503[]' id='answer-id-1650997' class='answer   answerof-426503 ' value='1650997'   \/><label for='answer-id-1650997' id='answer-label-1650997' class=' answer'><span>Create a Deep Learning Virtual Machine (DLVM) Windows edition.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426503[]' id='answer-id-1650998' class='answer   answerof-426503 ' value='1650998'   \/><label for='answer-id-1650998' id='answer-label-1650998' class=' answer'><span>Create a Data Science Virtual Machine (DSVM) Linux edition.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-31' style=';'><div id='questionWrap-31'  class='   watupro-question-id-426504'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>31. <\/span>1. Topic 1, Case Study 1 <br \/>\r<br><br \/>\r<br>Overview <br \/>\r<br>You are a data scientist in a company that provides data science for professional sporting events. <br \/>\r<br>Models will be global and local market data to meet the following business goals: <br \/>\r<br>&#8226; Understand sentiment of mobile device users at sporting events based on audio from crowd reactions. <br \/>\r<br>&#8226; Access a user's tendency to respond to an advertisement. <br \/>\r<br>&#8226; Customize styles of ads served on mobile devices. <br \/>\r<br>&#8226; Use video to detect penalty events. <br \/>\r<br><br \/>\r<br>Current environment <br \/>\r<br>Requirements <br \/>\r<br>&#8226; Media used for penalty event detection will be provided by consumer devices. Media may include images and videos captured during the sporting event and snared using social media. The images and videos will have varying sizes and formats. <br \/>\r<br>&#8226; The data available for model building comprises of seven years of sporting event media. The sporting event media includes: recorded videos, transcripts of radio commentary, and logs from related social media feeds feeds captured during the sporting events. <br \/>\r<br>&#8226; Crowd sentiment will include audio recordings submitted by event attendees in both mono and stereo Formats. <br \/>\r<br><br \/>\r<br>Advertisements <br \/>\r<br>&#8226; Ad response models must be trained at the beginning of each event and applied during the sporting event. <br \/>\r<br>&#8226; Market segmentation nxxlels must optimize for similar ad resporr.r history. <br \/>\r<br>&#8226; Sampling must guarantee mutual and collective exclusivity local and global segmentation models that share the same features. <br \/>\r<br>&#8226; Local market segmentation models will be applied before determining a user\u2019s propensity to respond to an advertisement. <br \/>\r<br>&#8226; Data scientists must be able to detect model degradation and decay. <br \/>\r<br>&#8226; Ad response models must support non linear boundaries features. <br \/>\r<br>&#8226; The ad propensity model uses a cut threshold is 0.45 and retrains occur if weighted Kappa deviates from 0.1 +\/-5%. <br \/>\r<br>&#8226; The ad propensity model uses cost factors shown in the following diagram: <br \/>\r<br><br><img decoding=\"async\" width=405 height=199 id=\"\u56fe\u7247 48\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2025\/09\/image001.png\"><br><br \/>\r<br>&#8226; The ad propensity model uses proposed cost factors shown in the following diagram: <br \/>\r<br><br><img decoding=\"async\" width=405 height=199 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2025\/09\/image002-1.png\"><br><br \/>\r<br>Performance curves of current and proposed cost factor scenarios are shown in the following diagram: <br \/>\r<br><br><img decoding=\"async\" width=649 height=209 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2025\/09\/image003-2.jpg\"><br><br \/>\r<br><br \/>\r<br>Penalty detection and sentiment <br \/>\r<br>Findings <br \/>\r<br>&#8226; Data scientists must build an intelligent solution by using multiple machine learning models for penalty event detection. <br \/>\r<br>&#8226; Data scientists must build notebooks in a local environment using automatic feature engineering and model building in machine learning pipelines. <br \/>\r<br>&#8226; Notebooks must be deployed to retrain by using Spark instances with dynamic worker allocation <br \/>\r<br>&#8226; Notebooks must execute with the same code on new Spark instances to recode only the source of the data. <br \/>\r<br>&#8226; Global penalty detection models must be trained by using dynamic runtime graph computation during training. <br \/>\r<br>&#8226; Local penalty detection models must be written by using BrainScript. <br \/>\r<br>&#8226; Experiments for local crowd sentiment models must combine local penalty detection data. <br \/>\r<br>&#8226; Crowd sentiment models must identify known sounds such as cheers and known catch phrases. Individual crowd sentiment models will detect similar sounds. <br \/>\r<br>&#8226; All shared features for local models are continuous variables. <br \/>\r<br>&#8226; Shared features must use double precision. Subsequent layers must have aggregate running mean and standard deviation metrics Available. <br \/>\r<br><br \/>\r<br>segments <br \/>\r<br>During the initial weeks in production, the following was observed: <br \/>\r<br>&#8226; Ad response rates declined. <br \/>\r<br>&#8226; Drops were not consistent across ad styles. <br \/>\r<br>&#8226; The distribution of features across training and production data are not consistent. <br \/>\r<br>Analysis shows that of the 100 numeric features on user location and behavior, the 47 features that come from location sources are being used as raw features. A suggested experiment to remedy the bias and variance issue is to engineer 10 linearly uncorrected features. <br \/>\r<br><br \/>\r<br>Penalty detection and sentiment <br \/>\r<br>&#8226; Initial data discovery shows a wide range of densities of target states in training data used for crowd sentiment models. <br \/>\r<br>&#8226; All penalty detection models show inference phases using a Stochastic Gradient Descent (SGD) are running too stow. <br \/>\r<br>&#8226; Audio samples show that the length of a catch phrase varies between 25%-47%, depending on region. <br \/>\r<br>&#8226; The performance of the global penalty detection models show lower variance but higher bias when comparing training and validation sets. Before implementing any feature changes, you must confirm the bias and variance using all training and validation cases. <br \/>\r<br><br \/>\r<br>You need to resolve the local machine learning pipeline performance issue. <br \/>\r<br>What should you do?<\/div><input type='hidden' name='question_id[]' id='qID_31' value='426504' \/><input type='hidden' id='answerType426504' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426504[]' id='answer-id-1650999' class='answer   answerof-426504 ' value='1650999'   \/><label for='answer-id-1650999' id='answer-label-1650999' class=' answer'><span>Increase Graphic Processing Units (GPUs).<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426504[]' id='answer-id-1651000' class='answer   answerof-426504 ' value='1651000'   \/><label for='answer-id-1651000' id='answer-label-1651000' class=' answer'><span>Increase the learning rate.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426504[]' id='answer-id-1651001' class='answer   answerof-426504 ' value='1651001'   \/><label for='answer-id-1651001' id='answer-label-1651001' class=' answer'><span>Increase the training iterations,<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426504[]' id='answer-id-1651002' class='answer   answerof-426504 ' value='1651002'   \/><label for='answer-id-1651002' id='answer-label-1651002' class=' answer'><span>Increase Central Processing Units (CPUs).<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-32' style=';'><div id='questionWrap-32'  class='   watupro-question-id-426505'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>32. <\/span>DRAG DROP <br \/>\r<br>You are building an intelligent solution using machine learning models. <br \/>\r<br>The environment must support the following requirements: <br \/>\r<br>&#10001; Data scientists must build notebooks in a cloud environment <br \/>\r<br>&#10001; Data scientists must use automatic feature engineering and model building in machine learning pipelines. <br \/>\r<br>&#10001; Notebooks must be deployed to retrain using Spark instances with dynamic worker allocation. <br \/>\r<br>&#10001; Notebooks must be exportable to be version controlled locally. <br \/>\r<br>You need to create the environment. <br \/>\r<br>Which four 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. <br \/>\r<br><br><img decoding=\"async\" width=649 height=370 id=\"\u56fe\u7247 269\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2025\/09\/image079.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_32' value='426505' \/><input type='hidden' id='answerType426505' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-426505[]' id='textarea_q_426505' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-33' style=';'><div id='questionWrap-33'  class='   watupro-question-id-426506'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>33. <\/span>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. <br \/>\r<br>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. <br \/>\r<br>You are creating a new experiment in Azure Machine Learning Studio. <br \/>\r<br>One class has a much smaller number of observations than the other classes in the training set. <br \/>\r<br>You need to select an appropriate data sampling strategy to compensate for the class imbalance. <br \/>\r<br>Solution: You use the Scale and Reduce sampling mode. <br \/>\r<br>Does the solution meet the goal?<\/div><input type='hidden' name='question_id[]' id='qID_33' value='426506' \/><input type='hidden' id='answerType426506' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426506[]' id='answer-id-1651004' class='answer   answerof-426506 ' value='1651004'   \/><label for='answer-id-1651004' id='answer-label-1651004' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426506[]' id='answer-id-1651005' class='answer   answerof-426506 ' value='1651005'   \/><label for='answer-id-1651005' id='answer-label-1651005' class=' answer'><span>No<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-34' style=';'><div id='questionWrap-34'  class='   watupro-question-id-426507'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>34. <\/span>HOTSPOT <br \/>\r<br>You are developing a linear regression model in Azure Machine Learning Studio. You run an experiment to compare different algorithms. <br \/>\r<br>The following image displays the results dataset output: <br \/>\r<br><br><img decoding=\"async\" width=650 height=192 id=\"\u56fe\u7247 137\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2025\/09\/image109.jpg\"><br><br \/>\r<br>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. <br \/>\r<br><br><img decoding=\"async\" width=650 height=333 id=\"\u56fe\u7247 138\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2025\/09\/image110.png\"><br><\/div><input type='hidden' name='question_id[]' id='qID_34' value='426507' \/><input type='hidden' id='answerType426507' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-426507[]' id='textarea_q_426507' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-35' style=';'><div id='questionWrap-35'  class='   watupro-question-id-426508'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>35. <\/span>HOTSPOT <br \/>\r<br>You arc I mating a deep learning model to identify cats and dogs. You have 25,000 color images. <br \/>\r<br>You must meet the following requirements: <br \/>\r<br>&#8226; Reduce the number of training epochs. <br \/>\r<br>&#8226; Reduce the size of the neural network. <br \/>\r<br>&#8226; Reduce over-fitting of the neural network. <br \/>\r<br>You need to select the image modification values. <br \/>\r<br>Which value should you use? To answer, select the appropriate Options in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=316 height=111 id=\"\u56fe\u7247 323\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2025\/09\/image060.png\"><br><\/div><input type='hidden' name='question_id[]' id='qID_35' value='426508' \/><input type='hidden' id='answerType426508' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-426508[]' id='textarea_q_426508' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-36' style=';'><div id='questionWrap-36'  class='   watupro-question-id-426509'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>36. <\/span>You use Azure Machine Learning Studio to build a machine learning experiment. <br \/>\r<br>You need to divide data into two distinct datasets. <br \/>\r<br>Which module should you use?<\/div><input type='hidden' name='question_id[]' id='qID_36' value='426509' \/><input type='hidden' id='answerType426509' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426509[]' id='answer-id-1651008' class='answer   answerof-426509 ' value='1651008'   \/><label for='answer-id-1651008' id='answer-label-1651008' class=' answer'><span>Split Data<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426509[]' id='answer-id-1651009' class='answer   answerof-426509 ' value='1651009'   \/><label for='answer-id-1651009' id='answer-label-1651009' class=' answer'><span>Load Trained Model<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426509[]' id='answer-id-1651010' class='answer   answerof-426509 ' value='1651010'   \/><label for='answer-id-1651010' id='answer-label-1651010' class=' answer'><span>Assign Data to Clusters<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426509[]' id='answer-id-1651011' class='answer   answerof-426509 ' value='1651011'   \/><label for='answer-id-1651011' id='answer-label-1651011' class=' answer'><span>Group Data into Bins<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-37' style=';'><div id='questionWrap-37'  class='   watupro-question-id-426510'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>37. <\/span>You are evaluating a completed binary classification machine learning model. <br \/>\r<br>You need to use the precision as the valuation metric. <br \/>\r<br>Which visualization should you use?<\/div><input type='hidden' name='question_id[]' id='qID_37' value='426510' \/><input type='hidden' id='answerType426510' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426510[]' id='answer-id-1651012' class='answer   answerof-426510 ' value='1651012'   \/><label for='answer-id-1651012' id='answer-label-1651012' class=' answer'><span>Binary classification confusion matrix<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426510[]' id='answer-id-1651013' class='answer   answerof-426510 ' value='1651013'   \/><label for='answer-id-1651013' id='answer-label-1651013' class=' answer'><span>box plot<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426510[]' id='answer-id-1651014' class='answer   answerof-426510 ' value='1651014'   \/><label for='answer-id-1651014' id='answer-label-1651014' class=' answer'><span>Gradient descent<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426510[]' id='answer-id-1651015' class='answer   answerof-426510 ' value='1651015'   \/><label for='answer-id-1651015' id='answer-label-1651015' class=' answer'><span>coefficient of determination<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-38' style=';'><div id='questionWrap-38'  class='   watupro-question-id-426511'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>38. <\/span>You need to select a feature extraction method. <br \/>\r<br>Which method should you use?<\/div><input type='hidden' name='question_id[]' id='qID_38' value='426511' \/><input type='hidden' id='answerType426511' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426511[]' id='answer-id-1651016' class='answer   answerof-426511 ' value='1651016'   \/><label for='answer-id-1651016' id='answer-label-1651016' class=' answer'><span>Spearman correlation<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426511[]' id='answer-id-1651017' class='answer   answerof-426511 ' value='1651017'   \/><label for='answer-id-1651017' id='answer-label-1651017' class=' answer'><span>Mutual information<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426511[]' id='answer-id-1651018' class='answer   answerof-426511 ' value='1651018'   \/><label for='answer-id-1651018' id='answer-label-1651018' class=' answer'><span>Mann-Whitney test<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-426511[]' id='answer-id-1651019' class='answer   answerof-426511 ' value='1651019'   \/><label for='answer-id-1651019' id='answer-label-1651019' class=' answer'><span>Pearson\u2019s correlation<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-39' style=';'><div id='questionWrap-39'  class='   watupro-question-id-426512'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>39. <\/span>HOTSPOT <br \/>\r<br>You plan to preprocess text from CSV files. You load the Azure Machine Learning Studio default stop words list. <br \/>\r<br>You need to configure the Preprocess Text module to meet the following requirements: <br \/>\r<br>&#10001; Ensure that multiple related words from a single canonical form. <br \/>\r<br>&#10001; Remove pipe characters from text. <br \/>\r<br>&#10001; Remove words to optimize information retrieval. <br \/>\r<br>Which three options should you select? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=396 height=690 id=\"\u56fe\u7247 284\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2025\/09\/image096.png\"><br><\/div><input type='hidden' name='question_id[]' id='qID_39' value='426512' \/><input type='hidden' id='answerType426512' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-426512[]' id='textarea_q_426512' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-40' style=';'><div id='questionWrap-40'  class='   watupro-question-id-426513'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>40. <\/span>HOTSPOT <br \/>\r<br>You need to replace the missing data in the AccessibilityToHighway columns. <br \/>\r<br>How should you configure the Clean Missing Data module? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=548 height=878 id=\"\u56fe\u7247 28\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2025\/09\/image034.png\"><br><\/div><input type='hidden' name='question_id[]' id='qID_40' value='426513' \/><input type='hidden' id='answerType426513' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-426513[]' id='textarea_q_426513' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div style='display:none' id='question-41'>\n\t<div class='question-content'>\n\t\t<img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/plugins\/watupro\/img\/loading.gif\" width=\"16\" height=\"16\" alt=\"Loading...\" title=\"Loading...\" \/>&nbsp;Loading...\t<\/div>\n<\/div>\n\n<br \/>\n\t\n\t\t\t<div class=\"watupro_buttons flex \" id=\"watuPROButtons10805\" >\n\t\t  <div id=\"prev-question\" style=\"display:none;\"><input type=\"button\" value=\"&lt; Previous\" onclick=\"WatuPRO.nextQuestion(event, 'previous');\"\/><\/div>\t\t  \t\t  \t\t   \n\t\t   \t  \t\t<div><input type=\"button\" name=\"action\" class=\"watupro-submit-button\" onclick=\"WatuPRO.submitResult(event)\" id=\"action-button\" value=\"View Results\"  \/>\n\t\t<\/div>\n\t\t<\/div>\n\t\t\n\t<input type=\"hidden\" name=\"quiz_id\" value=\"10805\" id=\"watuPROExamID\"\/>\n\t<input type=\"hidden\" name=\"start_time\" id=\"startTime\" value=\"2026-05-01 05:07:01\" \/>\n\t<input type=\"hidden\" name=\"start_timestamp\" id=\"startTimeStamp\" value=\"1777612021\" \/>\n\t<input type=\"hidden\" name=\"question_ids\" value=\"\" \/>\n\t<input type=\"hidden\" name=\"watupro_questions\" value=\"426474:1650923,1650924 | 426475:1650925,1650926,1650927,1650928 | 426476:1650929,1650930,1650931,1650932 | 426477:1650933,1650934,1650935,1650936,1650937 | 426478:1650938,1650939 | 426479:1650940 | 426480:1650941,1650942,1650943,1650944 | 426481:1650945,1650946,1650947,1650948 | 426482:1650949 | 426483:1650950 | 426484:1650951 | 426485:1650952 | 426486:1650953 | 426487:1650954 | 426488:1650955,1650956,1650957,1650958 | 426489:1650959,1650960,1650961,1650962 | 426490:1650963,1650964 | 426491:1650965 | 426492:1650966,1650967,1650968,1650969 | 426493:1650970 | 426494:1650971,1650972,1650973,1650974 | 426495:1650975,1650976,1650977,1650978,1650979 | 426496:1650980,1650981,1650982,1650983 | 426497:1650984 | 426498:1650985 | 426499:1650986,1650987 | 426500:1650988 | 426501:1650989,1650990,1650991,1650992 | 426502:1650993 | 426503:1650994,1650995,1650996,1650997,1650998 | 426504:1650999,1651000,1651001,1651002 | 426505:1651003 | 426506:1651004,1651005 | 426507:1651006 | 426508:1651007 | 426509:1651008,1651009,1651010,1651011 | 426510:1651012,1651013,1651014,1651015 | 426511:1651016,1651017,1651018,1651019 | 426512:1651020 | 426513:1651021\" \/>\n\t<input type=\"hidden\" name=\"no_ajax\" value=\"0\">\t\t\t<\/form>\n\t<p>&nbsp;<\/p>\n<\/div>\n\n<script type=\"text\/javascript\">\n\/\/jQuery(document).ready(function(){\ndocument.addEventListener(\"DOMContentLoaded\", function(event) { \t\nvar question_ids = \"426474,426475,426476,426477,426478,426479,426480,426481,426482,426483,426484,426485,426486,426487,426488,426489,426490,426491,426492,426493,426494,426495,426496,426497,426498,426499,426500,426501,426502,426503,426504,426505,426506,426507,426508,426509,426510,426511,426512,426513\";\nWatuPROSettings[10805] = {};\nWatuPRO.qArr = question_ids.split(',');\nWatuPRO.exam_id = 10805;\t    \nWatuPRO.post_id = 110248;\nWatuPRO.store_progress = 0;\nWatuPRO.curCatPage = 1;\nWatuPRO.requiredIDs=\"0\".split(\",\");\nWatuPRO.hAppID = \"0.26925600 1777612021\";\nvar url = \"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/plugins\/watupro\/show_exam.php\";\nWatuPRO.examMode = 1;\nWatuPRO.siteURL=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-admin\/admin-ajax.php\";\nWatuPRO.emailIsNotRequired = 0;\nWatuPROIntel.init(10805);\nWatuPRO.inCategoryPages=1;});    \t \n<\/script>\n<p>&nbsp;<\/p>\n<h3>Continue to read <a href=\"https:\/\/www.dumpsbase.com\/freedumps\/pass-your-exam-with-updated-dp-100-dumps-v23-02-continue-to-check-the-dp-100-free-dumps-part-2-q41-q80-online.html\"><span style=\"background-color: #99ccff;\"><em>DP-100 free dumps (Part 2, Q41-Q80) of V23.02<\/em><\/span><\/a> online.<\/h3>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>DumpsBase has updated the Microsoft DP-100 dumps to V23.02 for the Designing and Implementing a Data Science Solution on Azure exam preparation, so you can practice with authentic and up-to-date exam questions, improving both speed and accuracy. In this new version, we have set 506 practice exam questions and answers to help you identify mistakes, [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[101,18981,6074],"tags":[6070,6072],"class_list":["post-110248","post","type-post","status-publish","format-standard","hentry","category-microsoft","category-microsoft-certified-azure-data-scientist-associate","category-microsoft-data-certification","tag-dp-100-dumps","tag-dp-100-exam-questions"],"_links":{"self":[{"href":"https:\/\/www.dumpsbase.com\/freedumps\/wp-json\/wp\/v2\/posts\/110248","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.dumpsbase.com\/freedumps\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.dumpsbase.com\/freedumps\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.dumpsbase.com\/freedumps\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.dumpsbase.com\/freedumps\/wp-json\/wp\/v2\/comments?post=110248"}],"version-history":[{"count":2,"href":"https:\/\/www.dumpsbase.com\/freedumps\/wp-json\/wp\/v2\/posts\/110248\/revisions"}],"predecessor-version":[{"id":111632,"href":"https:\/\/www.dumpsbase.com\/freedumps\/wp-json\/wp\/v2\/posts\/110248\/revisions\/111632"}],"wp:attachment":[{"href":"https:\/\/www.dumpsbase.com\/freedumps\/wp-json\/wp\/v2\/media?parent=110248"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.dumpsbase.com\/freedumps\/wp-json\/wp\/v2\/categories?post=110248"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.dumpsbase.com\/freedumps\/wp-json\/wp\/v2\/tags?post=110248"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}