{"id":90034,"date":"2024-10-15T03:23:21","date_gmt":"2024-10-15T03:23:21","guid":{"rendered":"https:\/\/www.dumpsbase.com\/freedumps\/?p=90034"},"modified":"2024-10-15T03:23:27","modified_gmt":"2024-10-15T03:23:27","slug":"microsoft-dp-100-dumps-v20-02-updated-help-you-pass-the-designing-and-implementing-a-data-science-solution-on-azure-certification-exam","status":"publish","type":"post","link":"https:\/\/www.dumpsbase.com\/freedumps\/microsoft-dp-100-dumps-v20-02-updated-help-you-pass-the-designing-and-implementing-a-data-science-solution-on-azure-certification-exam.html","title":{"rendered":"Microsoft DP-100 Dumps (V20.02) Updated &#8211; Help You Pass the Designing and Implementing a Data Science Solution on Azure Certification Exam"},"content":{"rendered":"\n<p>Come to DumpsBase to download the Microsoft DP-100 dumps (V20.02) and prepare for the Designing and Implementing a Data Science Solution on Azure certification exam. We regularly update our dumps to match them with the changes in the outline and pattern of the Designing and Implementing a Data Science Solution on Azure exam. This collection of DP-100 exam questions and answers helps you practice all the necessary skills to solve complicated networking tasks as an IT engineer. Download the Microsoft DP-100 dumps (V20.02) and make preparations. Our latest DP-100 exam questions help you pass the Microsoft Designing and Implementing a Data Science Solution on Azure DP-100 exam on the first attempt.<\/p>\n<h2>Microsoft Designing and Implementing a Data Science Solution on Azure <em><span style=\"background-color: #00ffff;\">DP-100 Free Dumps<\/span><\/em><\/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=\"submittingExam9087\" 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-9087\"><\/div>\n\n<form action=\"\" method=\"post\" class=\"quiz-form\" id=\"quiz-9087\"  enctype=\"multipart\/form-data\" >\n<div class='watu-question ' id='question-1' style=';'><div id='questionWrap-1'  class='   watupro-question-id-357514'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>1. <\/span>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\/2024\/10\/image001-8.jpg\"><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\/2024\/10\/image002-8.jpg\"><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\/2024\/10\/image003-6.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_1' value='357514' \/><input type='hidden' id='answerType357514' 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-357514[]' id='answer-id-1395257' class='answer   answerof-357514 ' value='1395257'   \/><label for='answer-id-1395257' id='answer-label-1395257' class=' answer'><span>Increase Graphic Processing Units (GPUs).<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357514[]' id='answer-id-1395258' class='answer   answerof-357514 ' value='1395258'   \/><label for='answer-id-1395258' id='answer-label-1395258' class=' answer'><span>Increase the learning rate.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357514[]' id='answer-id-1395259' class='answer   answerof-357514 ' value='1395259'   \/><label for='answer-id-1395259' id='answer-label-1395259' class=' answer'><span>Increase the training iterations,<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357514[]' id='answer-id-1395260' class='answer   answerof-357514 ' value='1395260'   \/><label for='answer-id-1395260' id='answer-label-1395260' 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-2' style=';'><div id='questionWrap-2'  class='   watupro-question-id-357515'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>2. <\/span>DRAG DROP <br \/>\r<br>You need to modify the inputs for the global penalty event model to address the bias and variance issue. <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=256 id=\"\u56fe\u7247 14\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image004-4.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_2' value='357515' \/><input type='hidden' id='answerType357515' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357515[]' id='textarea_q_357515' 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-3' style=';'><div id='questionWrap-3'  class='   watupro-question-id-357516'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>3. <\/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_3' value='357516' \/><input type='hidden' id='answerType357516' 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-357516[]' id='answer-id-1395262' class='answer   answerof-357516 ' value='1395262'   \/><label for='answer-id-1395262' id='answer-label-1395262' class=' answer'><span>Azure HDInsight with Spark MLlib<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357516[]' id='answer-id-1395263' class='answer   answerof-357516 ' value='1395263'   \/><label for='answer-id-1395263' id='answer-label-1395263' class=' answer'><span>Azure Cognitive Services<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357516[]' id='answer-id-1395264' class='answer   answerof-357516 ' value='1395264'   \/><label for='answer-id-1395264' id='answer-label-1395264' class=' answer'><span>Azure Machine Learning Studio<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357516[]' id='answer-id-1395265' class='answer   answerof-357516 ' value='1395265'   \/><label for='answer-id-1395265' id='answer-label-1395265' class=' answer'><span>Microsoft Machine Learning Server<\/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-357517'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>4. <\/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\/2024\/10\/image006-4.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_4' value='357517' \/><input type='hidden' id='answerType357517' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357517[]' id='textarea_q_357517' 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-5' style=';'><div id='questionWrap-5'  class='   watupro-question-id-357518'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>5. <\/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\/2024\/10\/image008-3.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_5' value='357518' \/><input type='hidden' id='answerType357518' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357518[]' id='textarea_q_357518' 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-6' style=';'><div id='questionWrap-6'  class='   watupro-question-id-357519'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>6. <\/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\/2024\/10\/image010-3.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_6' value='357519' \/><input type='hidden' id='answerType357519' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357519[]' id='textarea_q_357519' 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-357520'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>7. <\/span>HOTSPOT <br \/>\r<br>You need to build a feature extraction strategy for the local 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=601 height=406 id=\"\u56fe\u7247 45\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image012-3.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_7' value='357520' \/><input type='hidden' id='answerType357520' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357520[]' id='textarea_q_357520' 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-8' style=';'><div id='questionWrap-8'  class='   watupro-question-id-357521'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>8. <\/span>You need to implement a scaling strategy for the local penalty detection data. <br \/>\r<br>Which normalization type should you use?<\/div><input type='hidden' name='question_id[]' id='qID_8' value='357521' \/><input type='hidden' id='answerType357521' 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-357521[]' id='answer-id-1395270' class='answer   answerof-357521 ' value='1395270'   \/><label for='answer-id-1395270' id='answer-label-1395270' class=' answer'><span>Streaming<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357521[]' id='answer-id-1395271' class='answer   answerof-357521 ' value='1395271'   \/><label for='answer-id-1395271' id='answer-label-1395271' class=' answer'><span>Weight<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357521[]' id='answer-id-1395272' class='answer   answerof-357521 ' value='1395272'   \/><label for='answer-id-1395272' id='answer-label-1395272' class=' answer'><span>Batch<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357521[]' id='answer-id-1395273' class='answer   answerof-357521 ' value='1395273'   \/><label for='answer-id-1395273' id='answer-label-1395273' class=' answer'><span>Cosine<\/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-357522'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>9. <\/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\/2024\/10\/image014-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_9' value='357522' \/><input type='hidden' id='answerType357522' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357522[]' id='textarea_q_357522' 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-357523'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>10. <\/span>You need to implement a feature engineering strategy for the crowd sentiment local models. <br \/>\r<br>What should you do?<\/div><input type='hidden' name='question_id[]' id='qID_10' value='357523' \/><input type='hidden' id='answerType357523' 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-357523[]' id='answer-id-1395275' class='answer   answerof-357523 ' value='1395275'   \/><label for='answer-id-1395275' id='answer-label-1395275' class=' answer'><span>Apply an analysis of variance (ANOVA).<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357523[]' id='answer-id-1395276' class='answer   answerof-357523 ' value='1395276'   \/><label for='answer-id-1395276' id='answer-label-1395276' class=' answer'><span>Apply a Pearson correlation coefficient.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357523[]' id='answer-id-1395277' class='answer   answerof-357523 ' value='1395277'   \/><label for='answer-id-1395277' id='answer-label-1395277' class=' answer'><span>Apply a Spearman correlation coefficient.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357523[]' id='answer-id-1395278' class='answer   answerof-357523 ' value='1395278'   \/><label for='answer-id-1395278' id='answer-label-1395278' class=' answer'><span>Apply a linear discriminant analysis.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-11' style=';'><div id='questionWrap-11'  class='   watupro-question-id-357524'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>11. <\/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\/2024\/10\/image016-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_11' value='357524' \/><input type='hidden' id='answerType357524' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357524[]' id='textarea_q_357524' 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-357525'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>12. <\/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=649 height=261 id=\"\u56fe\u7247 8\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image018-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_12' value='357525' \/><input type='hidden' id='answerType357525' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357525[]' id='textarea_q_357525' 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-357526'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>13. <\/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_13' value='357526' \/><input type='hidden' id='answerType357526' 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-357526[]' id='answer-id-1395281' class='answer   answerof-357526 ' value='1395281'   \/><label for='answer-id-1395281' id='answer-label-1395281' 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-357526[]' id='answer-id-1395282' class='answer   answerof-357526 ' value='1395282'   \/><label for='answer-id-1395282' id='answer-label-1395282' 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-357526[]' id='answer-id-1395283' class='answer   answerof-357526 ' value='1395283'   \/><label for='answer-id-1395283' id='answer-label-1395283' 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-357526[]' id='answer-id-1395284' class='answer   answerof-357526 ' value='1395284'   \/><label for='answer-id-1395284' id='answer-label-1395284' 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-14' style=';'><div id='questionWrap-14'  class='   watupro-question-id-357527'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>14. <\/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_14' value='357527' \/><input type='hidden' id='answerType357527' 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-357527[]' id='answer-id-1395285' class='answer   answerof-357527 ' value='1395285'   \/><label for='answer-id-1395285' id='answer-label-1395285' 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-357527[]' id='answer-id-1395286' class='answer   answerof-357527 ' value='1395286'   \/><label for='answer-id-1395286' id='answer-label-1395286' 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-357527[]' id='answer-id-1395287' class='answer   answerof-357527 ' value='1395287'   \/><label for='answer-id-1395287' id='answer-label-1395287' 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-357527[]' id='answer-id-1395288' class='answer   answerof-357527 ' value='1395288'   \/><label for='answer-id-1395288' id='answer-label-1395288' 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-15' style=';'><div id='questionWrap-15'  class='   watupro-question-id-357528'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>15. <\/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\/2024\/10\/image021-2.jpg\"><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\/2024\/10\/image022-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_15' value='357528' \/><input type='hidden' id='answerType357528' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357528[]' id='textarea_q_357528' 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-16' style=';'><div id='questionWrap-16'  class='   watupro-question-id-357529'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>16. <\/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 option-, m the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=614 height=406 id=\"\u56fe\u7247 42\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image024-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_16' value='357529' \/><input type='hidden' id='answerType357529' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357529[]' id='textarea_q_357529' 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-17' style=';'><div id='questionWrap-17'  class='   watupro-question-id-357530'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>17. <\/span>HOTSPOT <br \/>\r<br>You need to configure the Permutation Feature Importance module for the model training requirements. <br \/>\r<br>What should you do? 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=492 height=500 id=\"\u56fe\u7247 22\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image026-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_17' value='357530' \/><input type='hidden' id='answerType357530' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357530[]' id='textarea_q_357530' 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-18' style=';'><div id='questionWrap-18'  class='   watupro-question-id-357531'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>18. <\/span>HOTSPOT <br \/>\r<br>You need to configure the Edit Metadata module so that the structure of the datasets match. <br \/>\r<br>Which configuration 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=606 height=714 id=\"\u56fe\u7247 34\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image028-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_18' value='357531' \/><input type='hidden' id='answerType357531' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357531[]' id='textarea_q_357531' 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-357532'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>19. <\/span>DRAG DROP <br \/>\r<br>You need to correct the model fit issue. <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=601 height=526 id=\"\u56fe\u7247 32\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image030-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_19' value='357532' \/><input type='hidden' id='answerType357532' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357532[]' id='textarea_q_357532' 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-20' style=';'><div id='questionWrap-20'  class='   watupro-question-id-357533'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>20. <\/span>DRAG DROP <br \/>\r<br>You need to visually identify whether outliers exist in the Age column and quantify the outliers before the outliers are removed. <br \/>\r<br>Which three Azure Machine Learning Studio modules should you use in sequence? To answer, move the appropriate modules from the list of modules to the answer area and arrange them in the correct order. <br \/>\r<br><br><img decoding=\"async\" width=543 height=275 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image032-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_20' value='357533' \/><input type='hidden' id='answerType357533' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357533[]' id='textarea_q_357533' 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-357534'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>21. <\/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\/2024\/10\/image034-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_21' value='357534' \/><input type='hidden' id='answerType357534' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357534[]' id='textarea_q_357534' 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-22' style=';'><div id='questionWrap-22'  class='   watupro-question-id-357535'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>22. <\/span>DRAG DROP <br \/>\r<br>You need to produce a visualization for the diagnostic test evaluation according to the data visualization requirements. <br \/>\r<br>Which three modules should you recommend be used in sequence? To answer, move the appropriate modules from the list of modules to the answer area and arrange them in the correct order. <br \/>\r<br><br><img decoding=\"async\" width=649 height=477 id=\"\u56fe\u7247 40\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image036-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_22' value='357535' \/><input type='hidden' id='answerType357535' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357535[]' id='textarea_q_357535' 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-23' style=';'><div id='questionWrap-23'  class='   watupro-question-id-357536'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>23. <\/span>HOTSPOT <br \/>\r<br>You need to set up the Permutation Feature Importance module according to the model training 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=620 height=584 id=\"\u56fe\u7247 30\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image038-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_23' value='357536' \/><input type='hidden' id='answerType357536' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357536[]' id='textarea_q_357536' 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-24' style=';'><div id='questionWrap-24'  class='   watupro-question-id-357537'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>24. <\/span>HOTSPOT <br \/>\r<br>You need to configure the Feature Based Feature Selection module based on the experiment requirements and datasets. <br \/>\r<br>How should you configure the module properties? 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=347 height=395 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image040-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_24' value='357537' \/><input type='hidden' id='answerType357537' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357537[]' id='textarea_q_357537' 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-357538'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>25. <\/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_25' value='357538' \/><input type='hidden' id='answerType357538' 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-357538[]' id='answer-id-1395299' class='answer   answerof-357538 ' value='1395299'   \/><label for='answer-id-1395299' id='answer-label-1395299' class=' answer'><span>Mutual information<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357538[]' id='answer-id-1395300' class='answer   answerof-357538 ' value='1395300'   \/><label for='answer-id-1395300' id='answer-label-1395300' class=' answer'><span>Mood\u2019s median test<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357538[]' id='answer-id-1395301' class='answer   answerof-357538 ' value='1395301'   \/><label for='answer-id-1395301' id='answer-label-1395301' class=' answer'><span>Kendall correlation<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357538[]' id='answer-id-1395302' class='answer   answerof-357538 ' value='1395302'   \/><label for='answer-id-1395302' id='answer-label-1395302' class=' answer'><span>Permutation Feature Importance<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-26' style=';'><div id='questionWrap-26'  class='   watupro-question-id-357539'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>26. <\/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\/2024\/10\/image042-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_26' value='357539' \/><input type='hidden' id='answerType357539' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357539[]' id='textarea_q_357539' 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-27' style=';'><div id='questionWrap-27'  class='   watupro-question-id-357540'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>27. <\/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_27' value='357540' \/><input type='hidden' id='answerType357540' 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-357540[]' id='answer-id-1395304' class='answer   answerof-357540 ' value='1395304'   \/><label for='answer-id-1395304' id='answer-label-1395304' class=' answer'><span>Spearman correlation<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357540[]' id='answer-id-1395305' class='answer   answerof-357540 ' value='1395305'   \/><label for='answer-id-1395305' id='answer-label-1395305' class=' answer'><span>Mutual information<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357540[]' id='answer-id-1395306' class='answer   answerof-357540 ' value='1395306'   \/><label for='answer-id-1395306' id='answer-label-1395306' class=' answer'><span>Mann-Whitney test<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357540[]' id='answer-id-1395307' class='answer   answerof-357540 ' value='1395307'   \/><label for='answer-id-1395307' id='answer-label-1395307' class=' answer'><span>Pearson\u2019s correlation<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-28' style=';'><div id='questionWrap-28'  class='   watupro-question-id-357541'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>28. <\/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_28' value='357541' \/><input type='hidden' id='answerType357541' 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-357541[]' id='answer-id-1395308' class='answer   answerof-357541 ' value='1395308'   \/><label for='answer-id-1395308' id='answer-label-1395308' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357541[]' id='answer-id-1395309' class='answer   answerof-357541 ' value='1395309'   \/><label for='answer-id-1395309' id='answer-label-1395309' class=' answer'><span>NO<\/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-357542'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>29. <\/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 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: Remove the entire column that contains the missing data point. <br \/>\r<br>Does the solution meet the goal?<\/div><input type='hidden' name='question_id[]' id='qID_29' value='357542' \/><input type='hidden' id='answerType357542' 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-357542[]' id='answer-id-1395310' class='answer   answerof-357542 ' value='1395310'   \/><label for='answer-id-1395310' id='answer-label-1395310' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357542[]' id='answer-id-1395311' class='answer   answerof-357542 ' value='1395311'   \/><label for='answer-id-1395311' id='answer-label-1395311' class=' answer'><span>No<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-30' style=';'><div id='questionWrap-30'  class='   watupro-question-id-357543'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>30. <\/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 analyzing a numerical dataset which contain 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: Use the last Observation Carried Forward (IOCF) method to impute the missing data points. <br \/>\r<br>Does the solution meet the goal?<\/div><input type='hidden' name='question_id[]' id='qID_30' value='357543' \/><input type='hidden' id='answerType357543' 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-357543[]' id='answer-id-1395312' class='answer   answerof-357543 ' value='1395312'   \/><label for='answer-id-1395312' id='answer-label-1395312' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357543[]' id='answer-id-1395313' class='answer   answerof-357543 ' value='1395313'   \/><label for='answer-id-1395313' id='answer-label-1395313' class=' answer'><span>No<\/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-357544'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>31. <\/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_31' value='357544' \/><input type='hidden' id='answerType357544' 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-357544[]' id='answer-id-1395314' class='answer   answerof-357544 ' value='1395314'   \/><label for='answer-id-1395314' id='answer-label-1395314' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357544[]' id='answer-id-1395315' class='answer   answerof-357544 ' value='1395315'   \/><label for='answer-id-1395315' id='answer-label-1395315' class=' answer'><span>No<\/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-357545'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>32. <\/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 Learning learning Studio. <br \/>\r<br>One class has a much smaller number of observations than the other classes in the training <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 Synthetic Minority Oversampling Technique (SMOTE) sampling mode. <br \/>\r<br>Does the solution meet the goal?<\/div><input type='hidden' name='question_id[]' id='qID_32' value='357545' \/><input type='hidden' id='answerType357545' 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-357545[]' id='answer-id-1395316' class='answer   answerof-357545 ' value='1395316'   \/><label for='answer-id-1395316' id='answer-label-1395316' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357545[]' id='answer-id-1395317' class='answer   answerof-357545 ' value='1395317'   \/><label for='answer-id-1395317' id='answer-label-1395317' class=' answer'><span>No<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-33' style=';'><div id='questionWrap-33'  class='   watupro-question-id-357546'>\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 tin- 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 Principal Components Analysis (PCA) sampling mode. <br \/>\r<br>Does the solution meet the goal?<\/div><input type='hidden' name='question_id[]' id='qID_33' value='357546' \/><input type='hidden' id='answerType357546' 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-357546[]' id='answer-id-1395318' class='answer   answerof-357546 ' value='1395318'   \/><label for='answer-id-1395318' id='answer-label-1395318' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357546[]' id='answer-id-1395319' class='answer   answerof-357546 ' value='1395319'   \/><label for='answer-id-1395319' id='answer-label-1395319' 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-357547'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>34. <\/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 an Equal Width with Custom Start and Stop binning mode. <br \/>\r<br>Does the solution meet the goal?<\/div><input type='hidden' name='question_id[]' id='qID_34' value='357547' \/><input type='hidden' id='answerType357547' 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-357547[]' id='answer-id-1395320' class='answer   answerof-357547 ' value='1395320'   \/><label for='answer-id-1395320' id='answer-label-1395320' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357547[]' id='answer-id-1395321' class='answer   answerof-357547 ' value='1395321'   \/><label for='answer-id-1395321' id='answer-label-1395321' class=' answer'><span>No<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-35' style=';'><div id='questionWrap-35'  class='   watupro-question-id-357548'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>35. <\/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 normalization with a QuantileIndex normalization. <br \/>\r<br>Does the solution meet the GOAL?<\/div><input type='hidden' name='question_id[]' id='qID_35' value='357548' \/><input type='hidden' id='answerType357548' 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-357548[]' id='answer-id-1395322' class='answer   answerof-357548 ' value='1395322'   \/><label for='answer-id-1395322' id='answer-label-1395322' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357548[]' id='answer-id-1395323' class='answer   answerof-357548 ' value='1395323'   \/><label for='answer-id-1395323' id='answer-label-1395323' class=' answer'><span>No<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-36' style=';'><div id='questionWrap-36'  class='   watupro-question-id-357549'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>36. <\/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_36' value='357549' \/><input type='hidden' id='answerType357549' 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-357549[]' id='answer-id-1395324' class='answer   answerof-357549 ' value='1395324'   \/><label for='answer-id-1395324' id='answer-label-1395324' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357549[]' id='answer-id-1395325' class='answer   answerof-357549 ' value='1395325'   \/><label for='answer-id-1395325' id='answer-label-1395325' class=' answer'><span>No<\/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-357550'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>37. <\/span>You are conducting feature engineering to prepuce data for further analysis. <br \/>\r<br>The data includes seasonal patterns on inventory requirements. <br \/>\r<br>You need to select the appropriate method to conduct feature engineering on the data. <br \/>\r<br>Which method should you use?<\/div><input type='hidden' name='question_id[]' id='qID_37' value='357550' \/><input type='hidden' id='answerType357550' 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-357550[]' id='answer-id-1395326' class='answer   answerof-357550 ' value='1395326'   \/><label for='answer-id-1395326' id='answer-label-1395326' class=' answer'><span>Exponential Smoothing (ETS) function.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357550[]' id='answer-id-1395327' class='answer   answerof-357550 ' value='1395327'   \/><label for='answer-id-1395327' id='answer-label-1395327' class=' answer'><span>One Class Support Vector Machine module<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357550[]' id='answer-id-1395328' class='answer   answerof-357550 ' value='1395328'   \/><label for='answer-id-1395328' id='answer-label-1395328' class=' answer'><span>Time Series Anomaly Detection module<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357550[]' id='answer-id-1395329' class='answer   answerof-357550 ' value='1395329'   \/><label for='answer-id-1395329' id='answer-label-1395329' class=' answer'><span>Finite Impulse Response (FIR) Filter module.<\/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-357551'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>38. <\/span>You are solving a classification task. <br \/>\r<br>The dataset is imbalanced. <br \/>\r<br>You need to select an Azure Machine Learning Studio module to improve the classification accuracy. <br \/>\r<br>Which module should you use?<\/div><input type='hidden' name='question_id[]' id='qID_38' value='357551' \/><input type='hidden' id='answerType357551' 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-357551[]' id='answer-id-1395330' class='answer   answerof-357551 ' value='1395330'   \/><label for='answer-id-1395330' id='answer-label-1395330' class=' answer'><span>Fisher Linear Discriminant Analysis.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357551[]' id='answer-id-1395331' class='answer   answerof-357551 ' value='1395331'   \/><label for='answer-id-1395331' id='answer-label-1395331' class=' answer'><span>Filter Based Feature Selection<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357551[]' id='answer-id-1395332' class='answer   answerof-357551 ' value='1395332'   \/><label for='answer-id-1395332' id='answer-label-1395332' class=' answer'><span>Synthetic Minority Oversampling Technique (SMOTE)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357551[]' id='answer-id-1395333' class='answer   answerof-357551 ' value='1395333'   \/><label for='answer-id-1395333' id='answer-label-1395333' class=' answer'><span>Permutation Feature Importance<\/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-357552'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>39. <\/span>DRAG DROP <br \/>\r<br>You are producing a multiple linear regression model in Azure Machine Learning Studio. <br \/>\r<br>Several independent variables are highly correlated. <br \/>\r<br>You need to select appropriate methods for conducting effective feature engineering on all the data. <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=318 id=\"\u56fe\u7247 46\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image044-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_39' value='357552' \/><input type='hidden' id='answerType357552' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357552[]' id='textarea_q_357552' 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-357553'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>40. <\/span>You are performing a filter based feature selection for a dataset 10 build a multi class classifies by using Azure Machine Learning Studio. <br \/>\r<br>The dataset contains categorical features that are highly correlated to the output label column. <br \/>\r<br>You need to select the appropriate feature scoring statistical method to identify the key predictors. <br \/>\r<br>Which method should you use?<\/div><input type='hidden' name='question_id[]' id='qID_40' value='357553' \/><input type='hidden' id='answerType357553' 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-357553[]' id='answer-id-1395335' class='answer   answerof-357553 ' value='1395335'   \/><label for='answer-id-1395335' id='answer-label-1395335' class=' answer'><span>Chi-squared<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357553[]' id='answer-id-1395336' class='answer   answerof-357553 ' value='1395336'   \/><label for='answer-id-1395336' id='answer-label-1395336' class=' answer'><span>Spearman correlation<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357553[]' id='answer-id-1395337' class='answer   answerof-357553 ' value='1395337'   \/><label for='answer-id-1395337' id='answer-label-1395337' class=' answer'><span>Kendall correlation<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357553[]' id='answer-id-1395338' class='answer   answerof-357553 ' value='1395338'   \/><label for='answer-id-1395338' id='answer-label-1395338' class=' answer'><span>Person correlation<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-41' style=';'><div id='questionWrap-41'  class='   watupro-question-id-357554'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>41. <\/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\/2024\/10\/image046-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_41' value='357554' \/><input type='hidden' id='answerType357554' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357554[]' id='textarea_q_357554' 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-42' style=';'><div id='questionWrap-42'  class='   watupro-question-id-357555'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>42. <\/span>HOTSPOT <br \/>\r<br>You are creating a machine learning model in Python. The provided dataset contains several numerical columns and one text column. The text column represents a product's category. <br \/>\r<br>The product category will always be one of the following: <br \/>\r<br>&#10001; Bikes <br \/>\r<br>&#10001; Cars <br \/>\r<br>&#10001; Vans <br \/>\r<br>&#10001; Boats <br \/>\r<br>You are building a regression model using the scikit-learn Python package. <br \/>\r<br>You need to transform the text data to be compatible with the scikit-learn Python package. <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=649 height=428 id=\"\u56fe\u7247 274\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image048-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_42' value='357555' \/><input type='hidden' id='answerType357555' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357555[]' id='textarea_q_357555' 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-43' style=';'><div id='questionWrap-43'  class='   watupro-question-id-357556'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>43. <\/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\/2024\/10\/image050-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_43' value='357556' \/><input type='hidden' id='answerType357556' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357556[]' id='textarea_q_357556' 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-44' style=';'><div id='questionWrap-44'  class='   watupro-question-id-357557'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>44. <\/span>You plan to use a Data Science Virtual Machine (DSVM) with the open source deep learning frameworks Caffe2 and Theano. You need to select a pre configured DSVM to support the framework. <br \/>\r<br>What should you create?<\/div><input type='hidden' name='question_id[]' id='qID_44' value='357557' \/><input type='hidden' id='answerType357557' 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-357557[]' id='answer-id-1395342' class='answer   answerof-357557 ' value='1395342'   \/><label for='answer-id-1395342' id='answer-label-1395342' class=' answer'><span>Data Science Virtual Machine for Linux (CentOS)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357557[]' id='answer-id-1395343' class='answer   answerof-357557 ' value='1395343'   \/><label for='answer-id-1395343' id='answer-label-1395343' class=' answer'><span>Data Science Virtual Machine for Windows 2012<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357557[]' id='answer-id-1395344' class='answer   answerof-357557 ' value='1395344'   \/><label for='answer-id-1395344' id='answer-label-1395344' class=' answer'><span>Data Science Virtual Machine for Windows 2016<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357557[]' id='answer-id-1395345' class='answer   answerof-357557 ' value='1395345'   \/><label for='answer-id-1395345' id='answer-label-1395345' class=' answer'><span>Geo AI Data Science Virtual Machine with ArcGIS<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357557[]' id='answer-id-1395346' class='answer   answerof-357557 ' value='1395346'   \/><label for='answer-id-1395346' id='answer-label-1395346' class=' answer'><span>Data Science Virtual Machine for Linux (Ubuntu)<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-45' style=';'><div id='questionWrap-45'  class='   watupro-question-id-357558'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>45. <\/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_45' value='357558' \/><input type='hidden' id='answerType357558' 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-357558[]' id='answer-id-1395347' class='answer   answerof-357558 ' value='1395347'   \/><label for='answer-id-1395347' id='answer-label-1395347' class=' answer'><span>Coefficient of determination<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357558[]' id='answer-id-1395348' class='answer   answerof-357558 ' value='1395348'   \/><label for='answer-id-1395348' id='answer-label-1395348' class=' answer'><span>Recall<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357558[]' id='answer-id-1395349' class='answer   answerof-357558 ' value='1395349'   \/><label for='answer-id-1395349' id='answer-label-1395349' class=' answer'><span>Precision<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357558[]' id='answer-id-1395350' class='answer   answerof-357558 ' value='1395350'   \/><label for='answer-id-1395350' id='answer-label-1395350' class=' answer'><span>Mean absolute error<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357558[]' id='answer-id-1395351' class='answer   answerof-357558 ' value='1395351'   \/><label for='answer-id-1395351' id='answer-label-1395351' class=' answer'><span>Root Mean Square Error<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-46' style=';'><div id='questionWrap-46'  class='   watupro-question-id-357559'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>46. <\/span>You plan to use a Deep Learning Virtual Machine (DLVM) to train deep learning models using Compute Unified Device Architecture (CUDA) computations. <br \/>\r<br>You need to configure the DLVM to support CUDA. <br \/>\r<br>What should you implement?<\/div><input type='hidden' name='question_id[]' id='qID_46' value='357559' \/><input type='hidden' id='answerType357559' 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-357559[]' id='answer-id-1395352' class='answer   answerof-357559 ' value='1395352'   \/><label for='answer-id-1395352' id='answer-label-1395352' class=' answer'><span>Intel Software Guard Extensions (Intel SGX) technology<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357559[]' id='answer-id-1395353' class='answer   answerof-357559 ' value='1395353'   \/><label for='answer-id-1395353' id='answer-label-1395353' class=' answer'><span>Solid State Drives (SSD)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357559[]' id='answer-id-1395354' class='answer   answerof-357559 ' value='1395354'   \/><label for='answer-id-1395354' id='answer-label-1395354' class=' answer'><span>Graphic Processing Unit (GPU)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357559[]' id='answer-id-1395355' class='answer   answerof-357559 ' value='1395355'   \/><label for='answer-id-1395355' id='answer-label-1395355' class=' answer'><span>Computer Processing Unit (CPU) speed increase by using overcloking<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357559[]' id='answer-id-1395356' class='answer   answerof-357559 ' value='1395356'   \/><label for='answer-id-1395356' id='answer-label-1395356' class=' answer'><span>High Random Access Memory (RAM) configuration<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-47' style=';'><div id='questionWrap-47'  class='   watupro-question-id-357560'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>47. <\/span>DRAG DROP <br \/>\r<br>You configure a Deep Learning Virtual Machine for Windows. <br \/>\r<br>You need to recommend tools and frameworks to perform the following: <br \/>\r<br>&#10001; Build deep neural network (DNN) models <br \/>\r<br>&#10001; Perform interactive data exploration and visualization <br \/>\r<br>Which tools and frameworks should you recommend? To answer, drag the appropriate tools to the correct tasks. Each tool may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=649 height=259 id=\"\u56fe\u7247 215\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image052-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_47' value='357560' \/><input type='hidden' id='answerType357560' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357560[]' id='textarea_q_357560' 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-48' style=';'><div id='questionWrap-48'  class='   watupro-question-id-357561'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>48. <\/span>HOTSPOT <br \/>\r<br>You use Data Science Virtual Machines (DSVMs) for Windows and Linux in Azure. <br \/>\r<br>You need to access the DSVMs. <br \/>\r<br>Which utilities 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=503 height=354 id=\"\u56fe\u7247 558\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image054-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_48' value='357561' \/><input type='hidden' id='answerType357561' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357561[]' id='textarea_q_357561' 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-49' style=';'><div id='questionWrap-49'  class='   watupro-question-id-357562'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>49. <\/span>You need to select a pre built development environment for a series of data science experiments. You must use the R language for the experiments. <br \/>\r<br>Which three environments can you use? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.<\/div><input type='hidden' name='question_id[]' id='qID_49' value='357562' \/><input type='hidden' id='answerType357562' 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-357562[]' id='answer-id-1395359' class='answer   answerof-357562 ' value='1395359'   \/><label for='answer-id-1395359' id='answer-label-1395359' class=' answer'><span>M<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357562[]' id='answer-id-1395360' class='answer   answerof-357562 ' value='1395360'   \/><label for='answer-id-1395360' id='answer-label-1395360' class=' answer'><span>NET Library on a local environment<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357562[]' id='answer-id-1395361' class='answer   answerof-357562 ' value='1395361'   \/><label for='answer-id-1395361' id='answer-label-1395361' class=' answer'><span>Azure Machine Learning Studio<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357562[]' id='answer-id-1395362' class='answer   answerof-357562 ' value='1395362'   \/><label for='answer-id-1395362' id='answer-label-1395362' class=' answer'><span>Data Science Virtual Machine (OSVM)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357562[]' id='answer-id-1395363' class='answer   answerof-357562 ' value='1395363'   \/><label for='answer-id-1395363' id='answer-label-1395363' class=' answer'><span>Azure Data bricks<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357562[]' id='answer-id-1395364' class='answer   answerof-357562 ' value='1395364'   \/><label for='answer-id-1395364' id='answer-label-1395364' class=' answer'><span>Azure Cognitive Services<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-50' style=';'><div id='questionWrap-50'  class='   watupro-question-id-357563'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>50. <\/span>You plan to create a speech recognition deep learning model. <br \/>\r<br>The model must support the latest version of Python. <br \/>\r<br>You need to recommend a deep learning framework for speech recognition to include in the Data Science Virtual Machine (DSVM). <br \/>\r<br>What should you recommend?<\/div><input type='hidden' name='question_id[]' id='qID_50' value='357563' \/><input type='hidden' id='answerType357563' 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-357563[]' id='answer-id-1395365' class='answer   answerof-357563 ' value='1395365'   \/><label for='answer-id-1395365' id='answer-label-1395365' class=' answer'><span>Apache Drill<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357563[]' id='answer-id-1395366' class='answer   answerof-357563 ' value='1395366'   \/><label for='answer-id-1395366' id='answer-label-1395366' class=' answer'><span>Tensorflow<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357563[]' id='answer-id-1395367' class='answer   answerof-357563 ' value='1395367'   \/><label for='answer-id-1395367' id='answer-label-1395367' class=' answer'><span>Rattle<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357563[]' id='answer-id-1395368' class='answer   answerof-357563 ' value='1395368'   \/><label for='answer-id-1395368' id='answer-label-1395368' class=' answer'><span>Weka<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-51' style=';'><div id='questionWrap-51'  class='   watupro-question-id-357564'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>51. <\/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_51' value='357564' \/><input type='hidden' id='answerType357564' 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-357564[]' id='answer-id-1395369' class='answer   answerof-357564 ' value='1395369'   \/><label for='answer-id-1395369' id='answer-label-1395369' class=' answer'><span>Azure Data Lake Analytics<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357564[]' id='answer-id-1395370' class='answer   answerof-357564 ' value='1395370'   \/><label for='answer-id-1395370' id='answer-label-1395370' class=' answer'><span>Azure Databrick .<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357564[]' id='answer-id-1395371' class='answer   answerof-357564 ' value='1395371'   \/><label for='answer-id-1395371' id='answer-label-1395371' class=' answer'><span>Apache Spark for HDInsight.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357564[]' id='answer-id-1395372' class='answer   answerof-357564 ' value='1395372'   \/><label for='answer-id-1395372' id='answer-label-1395372' class=' answer'><span>Azure Container Service<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-52' style=';'><div id='questionWrap-52'  class='   watupro-question-id-357565'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>52. <\/span>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. <br \/>\r<br>You need to select a data cleaning method. <br \/>\r<br>Which method should you use?<\/div><input type='hidden' name='question_id[]' id='qID_52' value='357565' \/><input type='hidden' id='answerType357565' 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-357565[]' id='answer-id-1395373' class='answer   answerof-357565 ' value='1395373'   \/><label for='answer-id-1395373' id='answer-label-1395373' class=' answer'><span>Synthetic Minority Oversampling Technique (SMOTE)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357565[]' id='answer-id-1395374' class='answer   answerof-357565 ' value='1395374'   \/><label for='answer-id-1395374' id='answer-label-1395374' class=' answer'><span>Replace using MICE<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357565[]' id='answer-id-1395375' class='answer   answerof-357565 ' value='1395375'   \/><label for='answer-id-1395375' id='answer-label-1395375' class=' answer'><span>Replace using; Probabilistic PCA<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357565[]' id='answer-id-1395376' class='answer   answerof-357565 ' value='1395376'   \/><label for='answer-id-1395376' id='answer-label-1395376' class=' answer'><span>Normalization<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-53' style=';'><div id='questionWrap-53'  class='   watupro-question-id-357566'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>53. <\/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_53' value='357566' \/><input type='hidden' id='answerType357566' 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-357566[]' id='answer-id-1395377' class='answer   answerof-357566 ' value='1395377'   \/><label for='answer-id-1395377' id='answer-label-1395377' 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-357566[]' id='answer-id-1395378' class='answer   answerof-357566 ' value='1395378'   \/><label for='answer-id-1395378' id='answer-label-1395378' 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-357566[]' id='answer-id-1395379' class='answer   answerof-357566 ' value='1395379'   \/><label for='answer-id-1395379' id='answer-label-1395379' 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-357566[]' id='answer-id-1395380' class='answer   answerof-357566 ' value='1395380'   \/><label for='answer-id-1395380' id='answer-label-1395380' 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-54' style=';'><div id='questionWrap-54'  class='   watupro-question-id-357567'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>54. <\/span>HOTSPOT <br \/>\r<br>You are developing a machine learning, experiment by using Azure. <br \/>\r<br>The following images show the input and output of a machine learning experiment: <br \/>\r<br><br><img decoding=\"async\" width=649 height=182 id=\"\u56fe\u7247 244\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image057-2.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 graphic. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=489 height=101 id=\"\u56fe\u7247 245\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image058-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_54' value='357567' \/><input type='hidden' id='answerType357567' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357567[]' id='textarea_q_357567' 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-55' style=';'><div id='questionWrap-55'  class='   watupro-question-id-357568'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>55. <\/span>You are creating a machine learning model. <br \/>\r<br>You need to identify outliers in the data. <br \/>\r<br>Which two visualizations can you use? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point. NOTE: Each correct selection is worth one point.<\/div><input type='hidden' name='question_id[]' id='qID_55' value='357568' \/><input type='hidden' id='answerType357568' 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-357568[]' id='answer-id-1395382' class='answer   answerof-357568 ' value='1395382'   \/><label for='answer-id-1395382' id='answer-label-1395382' class=' answer'><span>box plot<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357568[]' id='answer-id-1395383' class='answer   answerof-357568 ' value='1395383'   \/><label for='answer-id-1395383' id='answer-label-1395383' class=' answer'><span>scatter<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357568[]' id='answer-id-1395384' class='answer   answerof-357568 ' value='1395384'   \/><label for='answer-id-1395384' id='answer-label-1395384' class=' answer'><span>random forest diagram<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357568[]' id='answer-id-1395385' class='answer   answerof-357568 ' value='1395385'   \/><label for='answer-id-1395385' id='answer-label-1395385' class=' answer'><span>Venn diagram<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357568[]' id='answer-id-1395386' class='answer   answerof-357568 ' value='1395386'   \/><label for='answer-id-1395386' id='answer-label-1395386' class=' answer'><span>ROC curve<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-56' style=';'><div id='questionWrap-56'  class='   watupro-question-id-357569'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>56. <\/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. 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\/2024\/10\/image060-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_56' value='357569' \/><input type='hidden' id='answerType357569' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357569[]' id='textarea_q_357569' 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-57' style=';'><div id='questionWrap-57'  class='   watupro-question-id-357570'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>57. <\/span>HOTSPOT <br \/>\r<br>You are performing sentiment analysis using a CSV file that includes 12,000 customer reviews written in a short sentence format. You add the CSV file to Azure Machine Learning Studio and configure it as the starting point dataset of an experiment. You add the Extract N-Gram Features from Text module to the experiment to extract key phrases from the customer review column in the dataset. <br \/>\r<br>You must create a new n-gram dictionary from the customer review text and set the maximum n-gram size to trigrams. <br \/>\r<br>What 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=286 height=842 id=\"\u56fe\u7247 231\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image062-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_57' value='357570' \/><input type='hidden' id='answerType357570' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357570[]' id='textarea_q_357570' 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-58' style=';'><div id='questionWrap-58'  class='   watupro-question-id-357571'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>58. <\/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_58' value='357571' \/><input type='hidden' id='answerType357571' 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-357571[]' id='answer-id-1395389' class='answer   answerof-357571 ' value='1395389'   \/><label for='answer-id-1395389' id='answer-label-1395389' class=' answer'><span>Execute Python Script<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357571[]' id='answer-id-1395390' class='answer   answerof-357571 ' value='1395390'   \/><label for='answer-id-1395390' id='answer-label-1395390' class=' answer'><span>Export Count Table<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357571[]' id='answer-id-1395391' class='answer   answerof-357571 ' value='1395391'   \/><label for='answer-id-1395391' id='answer-label-1395391' class=' answer'><span>Convert to Indicator Values<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357571[]' id='answer-id-1395392' class='answer   answerof-357571 ' value='1395392'   \/><label for='answer-id-1395392' id='answer-label-1395392' class=' answer'><span>Summarize Data<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357571[]' id='answer-id-1395393' class='answer   answerof-357571 ' value='1395393'   \/><label for='answer-id-1395393' id='answer-label-1395393' class=' answer'><span>Compute linear Correlation<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-59' style=';'><div id='questionWrap-59'  class='   watupro-question-id-357572'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>59. <\/span>You are building a binary classification model by using a supplied training set. <br \/>\r<br>The training set is imbalanced between two classes. <br \/>\r<br>You need to resolve the data imbalance. <br \/>\r<br>What are three possible ways to achieve this goal? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.<\/div><input type='hidden' name='question_id[]' id='qID_59' value='357572' \/><input type='hidden' id='answerType357572' 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-357572[]' id='answer-id-1395394' class='answer   answerof-357572 ' value='1395394'   \/><label for='answer-id-1395394' id='answer-label-1395394' class=' answer'><span>Penalize the classification<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357572[]' id='answer-id-1395395' class='answer   answerof-357572 ' value='1395395'   \/><label for='answer-id-1395395' id='answer-label-1395395' class=' answer'><span>Resample the data set using under sampling or oversampling<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357572[]' id='answer-id-1395396' class='answer   answerof-357572 ' value='1395396'   \/><label for='answer-id-1395396' id='answer-label-1395396' class=' answer'><span>Generate synthetic samples in the minority class.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357572[]' id='answer-id-1395397' class='answer   answerof-357572 ' value='1395397'   \/><label for='answer-id-1395397' id='answer-label-1395397' class=' answer'><span>Use accuracy as the evaluation metric of the model.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357572[]' id='answer-id-1395398' class='answer   answerof-357572 ' value='1395398'   \/><label for='answer-id-1395398' id='answer-label-1395398' class=' answer'><span>Normalize the training feature set.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-60' style=';'><div id='questionWrap-60'  class='   watupro-question-id-357573'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>60. <\/span>You are building recurrent neural network to perform a binary classification. <br \/>\r<br>The training loss, validation loss, training accuracy, and validation accuracy of each training epoch has been provided. You need to identify whether the classification model is over fitted. <br \/>\r<br>Which of the following is correct?<\/div><input type='hidden' name='question_id[]' id='qID_60' value='357573' \/><input type='hidden' id='answerType357573' 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-357573[]' id='answer-id-1395399' class='answer   answerof-357573 ' value='1395399'   \/><label for='answer-id-1395399' id='answer-label-1395399' class=' answer'><span>The training loss increases while the validation loss decreases when training the model.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357573[]' id='answer-id-1395400' class='answer   answerof-357573 ' value='1395400'   \/><label for='answer-id-1395400' id='answer-label-1395400' class=' answer'><span>The training loss decreases while the validation loss increases when training the model.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357573[]' id='answer-id-1395401' class='answer   answerof-357573 ' value='1395401'   \/><label for='answer-id-1395401' id='answer-label-1395401' class=' answer'><span>The training loss stays constant and the validation loss decreases when training the model.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357573[]' id='answer-id-1395402' class='answer   answerof-357573 ' value='1395402'   \/><label for='answer-id-1395402' id='answer-label-1395402' class=' answer'><span>The training loss .stays constant and the validation loss stays on a constant value and close to the training loss value when training the model.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-61' style=';'><div id='questionWrap-61'  class='   watupro-question-id-357574'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>61. <\/span>You are analyzing a dataset containing historical data from a local taxi company. You arc developing a regression a regression model. <br \/>\r<br>You must predict the fare of a taxi trip. <br \/>\r<br>You need to select performance metrics to correctly evaluate the- regression model. <br \/>\r<br>Which two metrics can you use? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.<\/div><input type='hidden' name='question_id[]' id='qID_61' value='357574' \/><input type='hidden' id='answerType357574' 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-357574[]' id='answer-id-1395403' class='answer   answerof-357574 ' value='1395403'   \/><label for='answer-id-1395403' id='answer-label-1395403' class=' answer'><span>an F1 score that is high<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357574[]' id='answer-id-1395404' class='answer   answerof-357574 ' value='1395404'   \/><label for='answer-id-1395404' id='answer-label-1395404' class=' answer'><span>an R Squared value dose to 1<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357574[]' id='answer-id-1395405' class='answer   answerof-357574 ' value='1395405'   \/><label for='answer-id-1395405' id='answer-label-1395405' class=' answer'><span>an R-Squared value close to 0<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357574[]' id='answer-id-1395406' class='answer   answerof-357574 ' value='1395406'   \/><label for='answer-id-1395406' id='answer-label-1395406' class=' answer'><span>a Root Mean Square Error value that is high<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357574[]' id='answer-id-1395407' class='answer   answerof-357574 ' value='1395407'   \/><label for='answer-id-1395407' id='answer-label-1395407' class=' answer'><span>a Root Mean Square Error value that is low<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357574[]' id='answer-id-1395408' class='answer   answerof-357574 ' value='1395408'   \/><label for='answer-id-1395408' id='answer-label-1395408' class=' answer'><span>an F 1 score that is low.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-62' style=';'><div id='questionWrap-62'  class='   watupro-question-id-357575'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>62. <\/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_62' value='357575' \/><input type='hidden' id='answerType357575' 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-357575[]' id='answer-id-1395409' class='answer   answerof-357575 ' value='1395409'   \/><label for='answer-id-1395409' id='answer-label-1395409' class=' answer'><span>Binary classification confusion matrix<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357575[]' id='answer-id-1395410' class='answer   answerof-357575 ' value='1395410'   \/><label for='answer-id-1395410' id='answer-label-1395410' class=' answer'><span>box plot<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357575[]' id='answer-id-1395411' class='answer   answerof-357575 ' value='1395411'   \/><label for='answer-id-1395411' id='answer-label-1395411' class=' answer'><span>Gradient descent<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357575[]' id='answer-id-1395412' class='answer   answerof-357575 ' value='1395412'   \/><label for='answer-id-1395412' id='answer-label-1395412' class=' answer'><span>coefficient of determination<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-63' style=';'><div id='questionWrap-63'  class='   watupro-question-id-357576'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>63. <\/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_63' value='357576' \/><input type='hidden' id='answerType357576' 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-357576[]' id='answer-id-1395413' class='answer   answerof-357576 ' value='1395413'   \/><label for='answer-id-1395413' id='answer-label-1395413' class=' answer'><span>Partition and Sample<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357576[]' id='answer-id-1395414' class='answer   answerof-357576 ' value='1395414'   \/><label for='answer-id-1395414' id='answer-label-1395414' class=' answer'><span>Cluster Centroids<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357576[]' id='answer-id-1395415' class='answer   answerof-357576 ' value='1395415'   \/><label for='answer-id-1395415' id='answer-label-1395415' class=' answer'><span>Tomek links<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357576[]' id='answer-id-1395416' class='answer   answerof-357576 ' value='1395416'   \/><label for='answer-id-1395416' id='answer-label-1395416' 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-64' style=';'><div id='questionWrap-64'  class='   watupro-question-id-357577'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>64. <\/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\/2024\/10\/image064-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_64' value='357577' \/><input type='hidden' id='answerType357577' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357577[]' id='textarea_q_357577' 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-65' style=';'><div id='questionWrap-65'  class='   watupro-question-id-357578'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>65. <\/span>HOTSPOT <br \/>\r<br>You are using the Azure Machine Learning Service to automate hyperparameter exploration of your neural network classification model. <br \/>\r<br>You must define the hyperparameter space to automatically tune hyperparameters using random sampling according to following requirements: <br \/>\r<br>The learning rate must be selected from a normal distribution with a mean value of 10 and a standard deviation of 3. <br \/>\r<br>Batch size must be 16, 32 and 64. <br \/>\r<br>Keep probability must be a value selected from a uniform distribution between the range of 0.05 and 0.1. <br \/>\r<br>You need to use the param_sampling method of the Python API for the Azure Machine Learning Service. <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=649 height=449 id=\"\u56fe\u7247 70\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image066-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_65' value='357578' \/><input type='hidden' id='answerType357578' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357578[]' id='textarea_q_357578' 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-66' style=';'><div id='questionWrap-66'  class='   watupro-question-id-357579'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>66. <\/span>You are a data scientist building a deep convolutional neural network (CNN) for image classification. <br \/>\r<br>The CNN model you built shows signs of overfitting. <br \/>\r<br>You need to reduce overfitting and converge the model to an optimal fit. <br \/>\r<br>Which two actions should you perform? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.<\/div><input type='hidden' name='question_id[]' id='qID_66' value='357579' \/><input type='hidden' id='answerType357579' 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-357579[]' id='answer-id-1395419' class='answer   answerof-357579 ' value='1395419'   \/><label for='answer-id-1395419' id='answer-label-1395419' class=' answer'><span>Reduce the amount of training data.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357579[]' id='answer-id-1395420' class='answer   answerof-357579 ' value='1395420'   \/><label for='answer-id-1395420' id='answer-label-1395420' class=' answer'><span>Add an additional dense layer with 64 input units<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357579[]' id='answer-id-1395421' class='answer   answerof-357579 ' value='1395421'   \/><label for='answer-id-1395421' id='answer-label-1395421' class=' answer'><span>Add L1\/L2 regularization.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357579[]' id='answer-id-1395422' class='answer   answerof-357579 ' value='1395422'   \/><label for='answer-id-1395422' id='answer-label-1395422' class=' answer'><span>Use training data augmentation<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357579[]' id='answer-id-1395423' class='answer   answerof-357579 ' value='1395423'   \/><label for='answer-id-1395423' id='answer-label-1395423' class=' answer'><span>Add an additional dense layer with 512 input units.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-67' style=';'><div id='questionWrap-67'  class='   watupro-question-id-357580'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>67. <\/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_67' value='357580' \/><input type='hidden' id='answerType357580' 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-357580[]' id='answer-id-1395424' class='answer   answerof-357580 ' value='1395424'   \/><label for='answer-id-1395424' id='answer-label-1395424' class=' answer'><span>Regular Expression Split<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357580[]' id='answer-id-1395425' class='answer   answerof-357580 ' value='1395425'   \/><label for='answer-id-1395425' id='answer-label-1395425' 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-357580[]' id='answer-id-1395426' class='answer   answerof-357580 ' value='1395426'   \/><label for='answer-id-1395426' id='answer-label-1395426' class=' answer'><span>Relative Expression Split<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357580[]' id='answer-id-1395427' class='answer   answerof-357580 ' value='1395427'   \/><label for='answer-id-1395427' id='answer-label-1395427' class=' answer'><span>Recommender Split<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-68' style=';'><div id='questionWrap-68'  class='   watupro-question-id-357581'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>68. <\/span>HOTSPOT <br \/>\r<br>You create an experiment in Azure Machine Learning Studio- You add a training dataset that contains 10.000 rows. The first 9.000 rows represent class 0 (90 percent). The first 1.000 rows represent class 1 (10 percent). <br \/>\r<br>The training set is unbalanced between two Classes. You must increase the number of training examples for class 1 to 4,000 by using data rows. You add the Synthetic Minority Oversampling Technique (SMOTE) module to the experiment. <br \/>\r<br>You need to configure the module. <br \/>\r<br>Which values should you use? 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=619 height=236 id=\"\u56fe\u7247 187\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image068-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_68' value='357581' \/><input type='hidden' id='answerType357581' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357581[]' id='textarea_q_357581' 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-69' style=';'><div id='questionWrap-69'  class='   watupro-question-id-357582'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>69. <\/span>You are performing clustering by using the K-means algorithm. <br \/>\r<br>You need to define the possible termination conditions. <br \/>\r<br>Which three conditions can you use? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.<\/div><input type='hidden' name='question_id[]' id='qID_69' value='357582' \/><input type='hidden' id='answerType357582' 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-357582[]' id='answer-id-1395429' class='answer   answerof-357582 ' value='1395429'   \/><label for='answer-id-1395429' id='answer-label-1395429' class=' answer'><span>A fixed number of iterations is executed.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357582[]' id='answer-id-1395430' class='answer   answerof-357582 ' value='1395430'   \/><label for='answer-id-1395430' id='answer-label-1395430' class=' answer'><span>The residual sum of squares (RSS) rises above a threshold.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357582[]' id='answer-id-1395431' class='answer   answerof-357582 ' value='1395431'   \/><label for='answer-id-1395431' id='answer-label-1395431' class=' answer'><span>The sum of distances between centroids reaches a maximum.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357582[]' id='answer-id-1395432' class='answer   answerof-357582 ' value='1395432'   \/><label for='answer-id-1395432' id='answer-label-1395432' class=' answer'><span>The residual sum of squares (RSS) falls below a threshold.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357582[]' id='answer-id-1395433' class='answer   answerof-357582 ' value='1395433'   \/><label for='answer-id-1395433' id='answer-label-1395433' class=' answer'><span>Centroids do not change between iterations.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-70' style=';'><div id='questionWrap-70'  class='   watupro-question-id-357583'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>70. <\/span>You are building a regression model tot estimating the number of calls during an event. <br \/>\r<br>You need to determine whether the feature values achieve the conditions to build a Poisson regression model. <br \/>\r<br>Which two conditions must the feature set contain? I ach correct answer presents part of the solution. NOTE: Each correct selection is worth one point.<\/div><input type='hidden' name='question_id[]' id='qID_70' value='357583' \/><input type='hidden' id='answerType357583' 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-357583[]' id='answer-id-1395434' class='answer   answerof-357583 ' value='1395434'   \/><label for='answer-id-1395434' id='answer-label-1395434' class=' answer'><span>The label data must be a negative value.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357583[]' id='answer-id-1395435' class='answer   answerof-357583 ' value='1395435'   \/><label for='answer-id-1395435' id='answer-label-1395435' class=' answer'><span>The label data can be positive or negative,<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357583[]' id='answer-id-1395436' class='answer   answerof-357583 ' value='1395436'   \/><label for='answer-id-1395436' id='answer-label-1395436' class=' answer'><span>The label data must be a positive value<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357583[]' id='answer-id-1395437' class='answer   answerof-357583 ' value='1395437'   \/><label for='answer-id-1395437' id='answer-label-1395437' class=' answer'><span>The label data must be non discrete.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357583[]' id='answer-id-1395438' class='answer   answerof-357583 ' value='1395438'   \/><label for='answer-id-1395438' id='answer-label-1395438' class=' answer'><span>The data must be whole numbers.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-71' style=';'><div id='questionWrap-71'  class='   watupro-question-id-357584'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>71. <\/span>HOTSPOT <br \/>\r<br>You are performing a classification task in Azure Machine Learning Studio. <br \/>\r<br>You must prepare balanced testing and training samples based on a provided data set. <br \/>\r<br>You need to split the data with a 0.75:0.25 ratio. <br \/>\r<br>Which value should you use for each parameter? 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=537 height=571 id=\"\u56fe\u7247 160\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image070-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_71' value='357584' \/><input type='hidden' id='answerType357584' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357584[]' id='textarea_q_357584' 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-72' style=';'><div id='questionWrap-72'  class='   watupro-question-id-357585'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>72. <\/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\/2024\/10\/image072-1.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\/2024\/10\/image073-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_72' value='357585' \/><input type='hidden' id='answerType357585' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357585[]' id='textarea_q_357585' 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-73' style=';'><div id='questionWrap-73'  class='   watupro-question-id-357586'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>73. <\/span>HOTSPOT <br \/>\r<br>You are tuning a hyperparameter for an algorithm. The following table shows a data set with different hyperparameter, training error, and validation errors. <br \/>\r<br><br><img decoding=\"async\" width=649 height=154 id=\"\u56fe\u7247 200\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image075-1.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 graphic. <br \/>\r<br><br><img decoding=\"async\" width=650 height=478 id=\"\u56fe\u7247 201\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image076-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_73' value='357586' \/><input type='hidden' id='answerType357586' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357586[]' id='textarea_q_357586' 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-74' style=';'><div id='questionWrap-74'  class='   watupro-question-id-357587'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>74. <\/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_74' value='357587' \/><input type='hidden' id='answerType357587' 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-357587[]' id='answer-id-1395442' class='answer   answerof-357587 ' value='1395442'   \/><label for='answer-id-1395442' id='answer-label-1395442' class=' answer'><span>Partition and Sample<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357587[]' id='answer-id-1395443' class='answer   answerof-357587 ' value='1395443'   \/><label for='answer-id-1395443' id='answer-label-1395443' class=' answer'><span>Assign Data to Clusters<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357587[]' id='answer-id-1395444' class='answer   answerof-357587 ' value='1395444'   \/><label for='answer-id-1395444' id='answer-label-1395444' class=' answer'><span>Group Data into Bins<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357587[]' id='answer-id-1395445' class='answer   answerof-357587 ' value='1395445'   \/><label for='answer-id-1395445' id='answer-label-1395445' class=' answer'><span>Test Hypothesis Using t-Test<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-75' style=';'><div id='questionWrap-75'  class='   watupro-question-id-357588'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>75. <\/span>You are developing a hands-on workshop to introduce Docker for Windows to attendees. <br \/>\r<br>You need to ensure that workshop attendees can install Docker on their devices. <br \/>\r<br>Which two prerequisite components should attendees install on the devices? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.<\/div><input type='hidden' name='question_id[]' id='qID_75' value='357588' \/><input type='hidden' id='answerType357588' 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-357588[]' id='answer-id-1395446' class='answer   answerof-357588 ' value='1395446'   \/><label for='answer-id-1395446' id='answer-label-1395446' class=' answer'><span>Microsoft Hardware-Assisted Virtualization Detection Tool<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357588[]' id='answer-id-1395447' class='answer   answerof-357588 ' value='1395447'   \/><label for='answer-id-1395447' id='answer-label-1395447' class=' answer'><span>Kitematic<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357588[]' id='answer-id-1395448' class='answer   answerof-357588 ' value='1395448'   \/><label for='answer-id-1395448' id='answer-label-1395448' class=' answer'><span>BIOS-enabled virtualization<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357588[]' id='answer-id-1395449' class='answer   answerof-357588 ' value='1395449'   \/><label for='answer-id-1395449' id='answer-label-1395449' class=' answer'><span>VirtualBox<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357588[]' id='answer-id-1395450' class='answer   answerof-357588 ' value='1395450'   \/><label for='answer-id-1395450' id='answer-label-1395450' class=' answer'><span>Windows 10 64-bit Professional<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-76' style=';'><div id='questionWrap-76'  class='   watupro-question-id-357589'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>76. <\/span>Your team is building a data engineering and data science development environment. <br \/>\r<br>The environment must support the following requirements: <br \/>\r<br>&#10001; support Python and Scala <br \/>\r<br>&#10001; compose data storage, movement, and processing services into automated data pipelines <br \/>\r<br>&#10001; the same tool should be used for the orchestration of both data engineering and data science <br \/>\r<br>&#10001; support workload isolation and interactive workloads <br \/>\r<br>&#10001; enable scaling across a cluster of machines <br \/>\r<br>You need to create the environment. <br \/>\r<br>What should you do?<\/div><input type='hidden' name='question_id[]' id='qID_76' value='357589' \/><input type='hidden' id='answerType357589' 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-357589[]' id='answer-id-1395451' class='answer   answerof-357589 ' value='1395451'   \/><label for='answer-id-1395451' id='answer-label-1395451' class=' answer'><span>Build the environment in Apache Hive for HDInsight and use Azure Data Factory for orchestration.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357589[]' id='answer-id-1395452' class='answer   answerof-357589 ' value='1395452'   \/><label for='answer-id-1395452' id='answer-label-1395452' class=' answer'><span>Build the environment in Azure Databricks and use Azure Data Factory for orchestration.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357589[]' id='answer-id-1395453' class='answer   answerof-357589 ' value='1395453'   \/><label for='answer-id-1395453' id='answer-label-1395453' class=' answer'><span>Build the environment in Apache Spark for HDInsight and use Azure Container Instances for orchestration.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357589[]' id='answer-id-1395454' class='answer   answerof-357589 ' value='1395454'   \/><label for='answer-id-1395454' id='answer-label-1395454' class=' answer'><span>Build the environment in Azure Databricks and use Azure Container Instances for orchestration.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-77' style=';'><div id='questionWrap-77'  class='   watupro-question-id-357590'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>77. <\/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\/2024\/10\/image079-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_77' value='357590' \/><input type='hidden' id='answerType357590' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357590[]' id='textarea_q_357590' 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-78' style=';'><div id='questionWrap-78'  class='   watupro-question-id-357591'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>78. <\/span>You plan to build a team data science environment. Data for training models in machine learning pipelines will be over 20 GB in size. <br \/>\r<br>You have the following requirements: <br \/>\r<br>&#10001; Models must be built using Caffe2 or Chainer frameworks. <br \/>\r<br>&#10001; Data scientists must be able to use a data science environment to build the machine learning pipelines and train models on their personal devices in both connected and disconnected network environments. <br \/>\r<br>&#10001; Personal devices must support updating machine learning pipelines when connected to a network. <br \/>\r<br>You need to select a data science environment. <br \/>\r<br>Which environment should you use?<\/div><input type='hidden' name='question_id[]' id='qID_78' value='357591' \/><input type='hidden' id='answerType357591' 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-357591[]' id='answer-id-1395456' class='answer   answerof-357591 ' value='1395456'   \/><label for='answer-id-1395456' id='answer-label-1395456' class=' answer'><span>Azure Machine Learning Service<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357591[]' id='answer-id-1395457' class='answer   answerof-357591 ' value='1395457'   \/><label for='answer-id-1395457' id='answer-label-1395457' class=' answer'><span>Azure Machine Learning Studio<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357591[]' id='answer-id-1395458' class='answer   answerof-357591 ' value='1395458'   \/><label for='answer-id-1395458' id='answer-label-1395458' class=' answer'><span>Azure Databricks<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357591[]' id='answer-id-1395459' class='answer   answerof-357591 ' value='1395459'   \/><label for='answer-id-1395459' id='answer-label-1395459' class=' answer'><span>Azure Kubernetes Service (AKS)<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-79' style=';'><div id='questionWrap-79'  class='   watupro-question-id-357592'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>79. <\/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_79' value='357592' \/><input type='hidden' id='answerType357592' 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-357592[]' id='answer-id-1395460' class='answer   answerof-357592 ' value='1395460'   \/><label for='answer-id-1395460' id='answer-label-1395460' 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-357592[]' id='answer-id-1395461' class='answer   answerof-357592 ' value='1395461'   \/><label for='answer-id-1395461' id='answer-label-1395461' 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-357592[]' id='answer-id-1395462' class='answer   answerof-357592 ' value='1395462'   \/><label for='answer-id-1395462' id='answer-label-1395462' 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-357592[]' id='answer-id-1395463' class='answer   answerof-357592 ' value='1395463'   \/><label for='answer-id-1395463' id='answer-label-1395463' 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-357592[]' id='answer-id-1395464' class='answer   answerof-357592 ' value='1395464'   \/><label for='answer-id-1395464' id='answer-label-1395464' 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-80' style=';'><div id='questionWrap-80'  class='   watupro-question-id-357593'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>80. <\/span>You are developing deep learning models to analyze semi-structured, unstructured, and structured data types. <br \/>\r<br>You have the following data available for model building: <br \/>\r<br>&#10001; Video recordings of sporting events <br \/>\r<br>&#10001; Transcripts of radio commentary about events <br \/>\r<br>&#10001; Logs from related social media feeds captured during sporting events <br \/>\r<br>You need to select an environment for creating the model. <br \/>\r<br>Which environment should you use?<\/div><input type='hidden' name='question_id[]' id='qID_80' value='357593' \/><input type='hidden' id='answerType357593' 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-357593[]' id='answer-id-1395465' class='answer   answerof-357593 ' value='1395465'   \/><label for='answer-id-1395465' id='answer-label-1395465' class=' answer'><span>Azure Cognitive Services<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357593[]' id='answer-id-1395466' class='answer   answerof-357593 ' value='1395466'   \/><label for='answer-id-1395466' id='answer-label-1395466' class=' answer'><span>Azure Data Lake Analytics<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357593[]' id='answer-id-1395467' class='answer   answerof-357593 ' value='1395467'   \/><label for='answer-id-1395467' id='answer-label-1395467' class=' answer'><span>Azure HDInsight with Spark MLib<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357593[]' id='answer-id-1395468' class='answer   answerof-357593 ' value='1395468'   \/><label for='answer-id-1395468' id='answer-label-1395468' class=' answer'><span>Azure Machine Learning Studio<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-81' style=';'><div id='questionWrap-81'  class='   watupro-question-id-357594'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>81. <\/span>You must store data in Azure Blob Storage to support Azure Machine Learning. <br \/>\r<br>You need to transfer the data into Azure Blob Storage. <br \/>\r<br>What are three possible ways to achieve the goal? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.<\/div><input type='hidden' name='question_id[]' id='qID_81' value='357594' \/><input type='hidden' id='answerType357594' 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-357594[]' id='answer-id-1395469' class='answer   answerof-357594 ' value='1395469'   \/><label for='answer-id-1395469' id='answer-label-1395469' class=' answer'><span>Bulk Insert SQL Query<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357594[]' id='answer-id-1395470' class='answer   answerof-357594 ' value='1395470'   \/><label for='answer-id-1395470' id='answer-label-1395470' class=' answer'><span>AzCopy<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357594[]' id='answer-id-1395471' class='answer   answerof-357594 ' value='1395471'   \/><label for='answer-id-1395471' id='answer-label-1395471' class=' answer'><span>Python script<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357594[]' id='answer-id-1395472' class='answer   answerof-357594 ' value='1395472'   \/><label for='answer-id-1395472' id='answer-label-1395472' class=' answer'><span>Azure Storage Explorer<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-357594[]' id='answer-id-1395473' class='answer   answerof-357594 ' value='1395473'   \/><label for='answer-id-1395473' id='answer-label-1395473' class=' answer'><span>Bulk Copy Program (BCP)<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-82' style=';'><div id='questionWrap-82'  class='   watupro-question-id-357595'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>82. <\/span>You are moving a large dataset from Azure Machine Learning Studio to a Weka environment. <br \/>\r<br>You need to format the data for the Weka environment. <br \/>\r<br>Which module should you use?<\/div><input type='hidden' name='question_id[]' id='qID_82' value='357595' \/><input type='hidden' id='answerType357595' 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-357595[]' id='answer-id-1395474' class='answer   answerof-357595 ' value='1395474'   \/><label for='answer-id-1395474' id='answer-label-1395474' class=' answer'><span>Convert to CSV<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357595[]' id='answer-id-1395475' class='answer   answerof-357595 ' value='1395475'   \/><label for='answer-id-1395475' id='answer-label-1395475' class=' answer'><span>Convert to Dataset<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357595[]' id='answer-id-1395476' class='answer   answerof-357595 ' value='1395476'   \/><label for='answer-id-1395476' id='answer-label-1395476' class=' answer'><span>Convert to ARFF<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357595[]' id='answer-id-1395477' class='answer   answerof-357595 ' value='1395477'   \/><label for='answer-id-1395477' id='answer-label-1395477' class=' answer'><span>Convert to SVMLight<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-83' style=';'><div id='questionWrap-83'  class='   watupro-question-id-357596'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>83. <\/span>You plan to deliver a hands-on workshop to several students. The workshop will focus on creating data visualizations using Python. Each student will use a device that has internet access. <br \/>\r<br>Student devices are not configured for Python development. Students do not have administrator access to install software on their devices. Azure subscriptions are not available for students. You need to ensure that students can run Python-based data visualization code. <br \/>\r<br>Which Azure tool should you use?<\/div><input type='hidden' name='question_id[]' id='qID_83' value='357596' \/><input type='hidden' id='answerType357596' 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-357596[]' id='answer-id-1395478' class='answer   answerof-357596 ' value='1395478'   \/><label for='answer-id-1395478' id='answer-label-1395478' class=' answer'><span>Anaconda Data Science Platform<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357596[]' id='answer-id-1395479' class='answer   answerof-357596 ' value='1395479'   \/><label for='answer-id-1395479' id='answer-label-1395479' class=' answer'><span>Azure BatchAl<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357596[]' id='answer-id-1395480' class='answer   answerof-357596 ' value='1395480'   \/><label for='answer-id-1395480' id='answer-label-1395480' class=' answer'><span>Azure Notebooks<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357596[]' id='answer-id-1395481' class='answer   answerof-357596 ' value='1395481'   \/><label for='answer-id-1395481' id='answer-label-1395481' class=' answer'><span>Azure Machine Learning Service<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-84' style=';'><div id='questionWrap-84'  class='   watupro-question-id-357597'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>84. <\/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 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: Calculate the column median value and use the median value as the replacement for any missing value in the column. <br \/>\r<br>Does the solution meet the goal?<\/div><input type='hidden' name='question_id[]' id='qID_84' value='357597' \/><input type='hidden' id='answerType357597' 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-357597[]' id='answer-id-1395482' class='answer   answerof-357597 ' value='1395482'   \/><label for='answer-id-1395482' id='answer-label-1395482' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357597[]' id='answer-id-1395483' class='answer   answerof-357597 ' value='1395483'   \/><label for='answer-id-1395483' id='answer-label-1395483' class=' answer'><span>No<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-85' style=';'><div id='questionWrap-85'  class='   watupro-question-id-357598'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>85. <\/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_85' value='357598' \/><input type='hidden' id='answerType357598' 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-357598[]' id='answer-id-1395484' class='answer   answerof-357598 ' value='1395484'   \/><label for='answer-id-1395484' id='answer-label-1395484' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357598[]' id='answer-id-1395485' class='answer   answerof-357598 ' value='1395485'   \/><label for='answer-id-1395485' id='answer-label-1395485' class=' answer'><span>No<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-86' style=';'><div id='questionWrap-86'  class='   watupro-question-id-357599'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>86. <\/span>HOTSPOT <br \/>\r<br>You create an experiment in Azure Machine Learning Studio. You add a training dataset that contains 10,000 rows. The first 9,000 rows represent class 0 (90 percent). <br \/>\r<br>The remaining 1,000 rows represent class 1 (10 percent). <br \/>\r<br>The training set is imbalances between two classes. You must increase the number of training examples for class 1 to 4,000 by using 5 data rows. You add the Synthetic Minority Oversampling Technique (SMOTE) module to the experiment. <br \/>\r<br>You need to configure the module. <br \/>\r<br>Which values should you use? 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=404 height=500 id=\"\u56fe\u7247 97\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image081-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_86' value='357599' \/><input type='hidden' id='answerType357599' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357599[]' id='textarea_q_357599' 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-87' style=';'><div id='questionWrap-87'  class='   watupro-question-id-357600'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>87. <\/span>You are solving a classification task. <br \/>\r<br>You must evaluate your model on a limited data sample by using k-fold cross validation. You start by configuring a k parameter as the number of splits. <br \/>\r<br>You need to configure the k parameter for the cross-validation. <br \/>\r<br>Which value should you use?<\/div><input type='hidden' name='question_id[]' id='qID_87' value='357600' \/><input type='hidden' id='answerType357600' 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-357600[]' id='answer-id-1395487' class='answer   answerof-357600 ' value='1395487'   \/><label for='answer-id-1395487' id='answer-label-1395487' class=' answer'><span>k=0.5<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357600[]' id='answer-id-1395488' class='answer   answerof-357600 ' value='1395488'   \/><label for='answer-id-1395488' id='answer-label-1395488' class=' answer'><span>k=0<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357600[]' id='answer-id-1395489' class='answer   answerof-357600 ' value='1395489'   \/><label for='answer-id-1395489' id='answer-label-1395489' class=' answer'><span>k=5<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357600[]' id='answer-id-1395490' class='answer   answerof-357600 ' value='1395490'   \/><label for='answer-id-1395490' id='answer-label-1395490' class=' answer'><span>k=1<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-88' style=';'><div id='questionWrap-88'  class='   watupro-question-id-357601'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>88. <\/span>DRAG DROP <br \/>\r<br>You are creating an experiment by using Azure Machine Learning Studio. <br \/>\r<br>You must divide the data into four subsets for evaluation. There is a high degree of missing values in the data. You must prepare the data for analysis. <br \/>\r<br>You need to select appropriate methods for producing the experiment. <br \/>\r<br>Which three modules should you run in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order. NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select. <br \/>\r<br><br><img decoding=\"async\" width=460 height=360 id=\"\u56fe\u7247 52\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image083-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_88' value='357601' \/><input type='hidden' id='answerType357601' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357601[]' id='textarea_q_357601' 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-89' style=';'><div id='questionWrap-89'  class='   watupro-question-id-357602'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>89. <\/span>HOTSPOT <br \/>\r<br>You are retrieving data from a large datastore by using Azure Machine Learning Studio. <br \/>\r<br>You must create a subset of the data for testing purposes using a random sampling seed based on the system clock. <br \/>\r<br>You add the Partition and Sample module to your experiment. <br \/>\r<br>You need to select the properties for the module. <br \/>\r<br>Which values 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=455 height=500 id=\"\u56fe\u7247 89\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image085-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_89' value='357602' \/><input type='hidden' id='answerType357602' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357602[]' id='textarea_q_357602' 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-90' style=';'><div id='questionWrap-90'  class='   watupro-question-id-357603'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>90. <\/span>You are creating a machine learning model. You have a dataset that contains null rows. <br \/>\r<br>You need to use the Clean Missing Data module in Azure Machine Learning Studio to identify and resolve the null and missing data in the dataset. <br \/>\r<br>Which parameter should you use?<\/div><input type='hidden' name='question_id[]' id='qID_90' value='357603' \/><input type='hidden' id='answerType357603' 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-357603[]' id='answer-id-1395493' class='answer   answerof-357603 ' value='1395493'   \/><label for='answer-id-1395493' id='answer-label-1395493' class=' answer'><span>Replace with mean<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357603[]' id='answer-id-1395494' class='answer   answerof-357603 ' value='1395494'   \/><label for='answer-id-1395494' id='answer-label-1395494' class=' answer'><span>Remove entire column<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357603[]' id='answer-id-1395495' class='answer   answerof-357603 ' value='1395495'   \/><label for='answer-id-1395495' id='answer-label-1395495' class=' answer'><span>Remove entire row<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357603[]' id='answer-id-1395496' class='answer   answerof-357603 ' value='1395496'   \/><label for='answer-id-1395496' id='answer-label-1395496' class=' answer'><span>Hot Deck<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-91' style=';'><div id='questionWrap-91'  class='   watupro-question-id-357604'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>91. <\/span>DRAG DROP <br \/>\r<br>You are analyzing a raw dataset that requires cleaning. <br \/>\r<br>You must perform transformations and manipulations by using Azure Machine Learning Studio. <br \/>\r<br>You need to identify the correct modules to perform the transformations. <br \/>\r<br>Which modules should you choose? To answer, drag the appropriate modules to the correct scenarios. Each module may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=649 height=266 id=\"\u56fe\u7247 193\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image087-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_91' value='357604' \/><input type='hidden' id='answerType357604' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357604[]' id='textarea_q_357604' 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-92' style=';'><div id='questionWrap-92'  class='   watupro-question-id-357605'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>92. <\/span>HOTSPOT <br \/>\r<br>You have a Python data frame named salesData in the following format: <br \/>\r<br><br><img decoding=\"async\" width=225 height=79 id=\"\u56fe\u7247 144\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image089-1.jpg\"><br><br \/>\r<br>The data frame must be unpivoted to a long data format as follows: <br \/>\r<br><br><img decoding=\"async\" width=230 height=142 id=\"\u56fe\u7247 145\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image090-1.jpg\"><br><br \/>\r<br>You need to use the pandas.melt() function in Python to perform the transformation. <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=649 height=144 id=\"\u56fe\u7247 146\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image091-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_92' value='357605' \/><input type='hidden' id='answerType357605' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357605[]' id='textarea_q_357605' 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-93' style=';'><div id='questionWrap-93'  class='   watupro-question-id-357606'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>93. <\/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\/2024\/10\/image093-1.jpg\"><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\/2024\/10\/image094-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_93' value='357606' \/><input type='hidden' id='answerType357606' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357606[]' id='textarea_q_357606' 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-94' style=';'><div id='questionWrap-94'  class='   watupro-question-id-357607'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>94. <\/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\/2024\/10\/image096-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_94' value='357607' \/><input type='hidden' id='answerType357607' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357607[]' id='textarea_q_357607' 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-95' style=';'><div id='questionWrap-95'  class='   watupro-question-id-357608'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>95. <\/span>You are performing feature engineering on a dataset. <br \/>\r<br>You must add a feature named CityName and populate the column value with the text London. <br \/>\r<br>You need to add the new feature to the dataset. <br \/>\r<br>Which Azure Machine Learning Studio module should you use?<\/div><input type='hidden' name='question_id[]' id='qID_95' value='357608' \/><input type='hidden' id='answerType357608' 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-357608[]' id='answer-id-1395501' class='answer   answerof-357608 ' value='1395501'   \/><label for='answer-id-1395501' id='answer-label-1395501' class=' answer'><span>Edit Metadata<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357608[]' id='answer-id-1395502' class='answer   answerof-357608 ' value='1395502'   \/><label for='answer-id-1395502' id='answer-label-1395502' class=' answer'><span>Preprocess Text<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357608[]' id='answer-id-1395503' class='answer   answerof-357608 ' value='1395503'   \/><label for='answer-id-1395503' id='answer-label-1395503' class=' answer'><span>Execute Python Script<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-357608[]' id='answer-id-1395504' class='answer   answerof-357608 ' value='1395504'   \/><label for='answer-id-1395504' id='answer-label-1395504' class=' answer'><span>Latent Dirichlet Allocation<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-96' style=';'><div id='questionWrap-96'  class='   watupro-question-id-357609'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>96. <\/span>HOTSPOT <br \/>\r<br>You have a dataset created for multiclass classification tasks that contains a normalized numerical feature set with 10,000 data points and 150 features. <br \/>\r<br>You use 75 percent of the data points for training and 25 percent for testing. You are using the scikit-learn machine learning library in Python. You use X to denote the feature set and Y to denote class labels. <br \/>\r<br>You create the following Python data frames: <br \/>\r<br><br><img decoding=\"async\" width=292 height=96 id=\"\u56fe\u7247 122\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image098-1.jpg\"><br><br \/>\r<br>You need to apply the Principal Component Analysis (PCA) method to reduce the dimensionality of the feature set to 10 features in both training and testing sets. <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=531 height=391 id=\"\u56fe\u7247 123\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2024\/10\/image099-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_96' value='357609' \/><input type='hidden' id='answerType357609' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-357609[]' id='textarea_q_357609' 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-97'>\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 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