{"id":32688,"date":"2021-12-17T02:08:45","date_gmt":"2021-12-17T02:08:45","guid":{"rendered":"https:\/\/www.dumpsbase.com\/freedumps\/?p=32688"},"modified":"2021-12-17T02:08:48","modified_gmt":"2021-12-17T02:08:48","slug":"updated-microsoft-azure-certification-dp-100-dumps-questions","status":"publish","type":"post","link":"https:\/\/www.dumpsbase.com\/freedumps\/updated-microsoft-azure-certification-dp-100-dumps-questions.html","title":{"rendered":"Updated Microsoft Azure Certification DP-100 Dumps Questions"},"content":{"rendered":"\n<p>To earn Microsoft Certified: Azure Data Scientist Associate certification successfully, you can choose the updated DP-100 dumps questions at DumpsBase to prepare for the Microsoft DP-100 exam well and pass finally. Updated DP-100 exam dumps, which written by the experienced team of DumpsBase, contain 247 practice exam questions and answers to make sure that you will practice DP-100 dumps questions before taking the actual DP-100 Designing and Implementing a Data Science Solution on Azure certification exam. Choosing DP-100 updated dumps questions of DumpsBase should be a perfect solution to complete DP-100 Microsoft exam and achieve Microsoft Certified: Azure Data Scientist Associate certification.<\/p>\n<h2>Microsoft Azure Certification <span style=\"color: #ff00ff;\">DP-100 Free Dumps<\/span> Are Below For Checking<\/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=\"submittingExam5876\" 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-5876\"><\/div>\n\n<form action=\"\" method=\"post\" class=\"quiz-form\" id=\"quiz-5876\"  enctype=\"multipart\/form-data\" >\n<div class='watu-question ' id='question-1' style=';'><div id='questionWrap-1'  class='   watupro-question-id-199796'>\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 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image001-5.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\/2021\/11\/image002-6.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=650 height=209 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image003-5.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>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 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image004-6.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_1' value='199796' \/><input type='hidden' id='answerType199796' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199796[]' id='textarea_q_199796' 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-2' style=';'><div id='questionWrap-2'  class='   watupro-question-id-199797'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>2. <\/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_2' value='199797' \/><input type='hidden' id='answerType199797' 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-199797[]' id='answer-id-800717' class='answer   answerof-199797 ' value='800717'   \/><label for='answer-id-800717' id='answer-label-800717' class=' answer'><span>Apply an analysis of variance (ANOVA).<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199797[]' id='answer-id-800718' class='answer   answerof-199797 ' value='800718'   \/><label for='answer-id-800718' id='answer-label-800718' class=' answer'><span>Apply a Pearson correlation coefficient.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199797[]' id='answer-id-800719' class='answer   answerof-199797 ' value='800719'   \/><label for='answer-id-800719' id='answer-label-800719' class=' answer'><span>Apply a Spearman correlation coefficient.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199797[]' id='answer-id-800720' class='answer   answerof-199797 ' value='800720'   \/><label for='answer-id-800720' id='answer-label-800720' 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-3' style=';'><div id='questionWrap-3'  class='   watupro-question-id-199798'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>3. <\/span>You need to implement a new cost factor scenario for the ad response models as illustrated in the performance curve exhibit. <br \/>\r<br>Which technique should you use?<\/div><input type='hidden' name='question_id[]' id='qID_3' value='199798' \/><input type='hidden' id='answerType199798' 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-199798[]' id='answer-id-800721' class='answer   answerof-199798 ' value='800721'   \/><label for='answer-id-800721' id='answer-label-800721' 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-199798[]' id='answer-id-800722' class='answer   answerof-199798 ' value='800722'   \/><label for='answer-id-800722' id='answer-label-800722' 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-199798[]' id='answer-id-800723' class='answer   answerof-199798 ' value='800723'   \/><label for='answer-id-800723' id='answer-label-800723' 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-199798[]' id='answer-id-800724' class='answer   answerof-199798 ' value='800724'   \/><label for='answer-id-800724' id='answer-label-800724' 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-4' style=';'><div id='questionWrap-4'  class='   watupro-question-id-199799'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>4. <\/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=650 height=256 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image007-4.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_4' value='199799' \/><input type='hidden' id='answerType199799' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199799[]' id='textarea_q_199799' 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-199800'>\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=545 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image009-4.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_5' value='199800' \/><input type='hidden' id='answerType199800' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199800[]' id='textarea_q_199800' 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-199801'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>6. <\/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 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image011-4.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_6' value='199801' \/><input type='hidden' id='answerType199801' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199801[]' id='textarea_q_199801' 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-199802'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>7. <\/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_7' value='199802' \/><input type='hidden' id='answerType199802' 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-199802[]' id='answer-id-800728' class='answer   answerof-199802 ' value='800728'   \/><label for='answer-id-800728' id='answer-label-800728' class=' answer'><span>Azure HDInsight with Spark MLlib<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199802[]' id='answer-id-800729' class='answer   answerof-199802 ' value='800729'   \/><label for='answer-id-800729' id='answer-label-800729' class=' answer'><span>Azure Cognitive Services<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199802[]' id='answer-id-800730' class='answer   answerof-199802 ' value='800730'   \/><label for='answer-id-800730' id='answer-label-800730' class=' answer'><span>Azure Machine Learning Studio<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199802[]' id='answer-id-800731' class='answer   answerof-199802 ' value='800731'   \/><label for='answer-id-800731' id='answer-label-800731' class=' answer'><span>Microsoft Machine Learning Server<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-8' style=';'><div id='questionWrap-8'  class='   watupro-question-id-199803'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>8. <\/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 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image013-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_8' value='199803' \/><input type='hidden' id='answerType199803' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199803[]' id='textarea_q_199803' 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-9' style=';'><div id='questionWrap-9'  class='   watupro-question-id-199804'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>9. <\/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=261 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image015-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_9' value='199804' \/><input type='hidden' id='answerType199804' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199804[]' id='textarea_q_199804' 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-199805'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>10. <\/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 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image017-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_10' value='199805' \/><input type='hidden' id='answerType199805' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199805[]' id='textarea_q_199805' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-11' style=';'><div id='questionWrap-11'  class='   watupro-question-id-199806'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>11. <\/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 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image019-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_11' value='199806' \/><input type='hidden' id='answerType199806' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199806[]' id='textarea_q_199806' 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-199807'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>12. <\/span>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_12' value='199807' \/><input type='hidden' id='answerType199807' 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-199807[]' id='answer-id-800736' class='answer   answerof-199807 ' value='800736'   \/><label for='answer-id-800736' id='answer-label-800736' class=' answer'><span>Increase Graphic Processing Units (GPUs).<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199807[]' id='answer-id-800737' class='answer   answerof-199807 ' value='800737'   \/><label for='answer-id-800737' id='answer-label-800737' class=' answer'><span>Increase the learning rate.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199807[]' id='answer-id-800738' class='answer   answerof-199807 ' value='800738'   \/><label for='answer-id-800738' id='answer-label-800738' class=' answer'><span>Increase the training iterations,<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199807[]' id='answer-id-800739' class='answer   answerof-199807 ' value='800739'   \/><label for='answer-id-800739' id='answer-label-800739' 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-13' style=';'><div id='questionWrap-13'  class='   watupro-question-id-199808'>\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='199808' \/><input type='hidden' id='answerType199808' 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-199808[]' id='answer-id-800740' class='answer   answerof-199808 ' value='800740'   \/><label for='answer-id-800740' id='answer-label-800740' 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-199808[]' id='answer-id-800741' class='answer   answerof-199808 ' value='800741'   \/><label for='answer-id-800741' id='answer-label-800741' 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-199808[]' id='answer-id-800742' class='answer   answerof-199808 ' value='800742'   \/><label for='answer-id-800742' id='answer-label-800742' 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-199808[]' id='answer-id-800743' class='answer   answerof-199808 ' value='800743'   \/><label for='answer-id-800743' id='answer-label-800743' 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-199809'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>14. <\/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_14' value='199809' \/><input type='hidden' id='answerType199809' 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-199809[]' id='answer-id-800744' class='answer   answerof-199809 ' value='800744'   \/><label for='answer-id-800744' id='answer-label-800744' class=' answer'><span>Streaming<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199809[]' id='answer-id-800745' class='answer   answerof-199809 ' value='800745'   \/><label for='answer-id-800745' id='answer-label-800745' class=' answer'><span>Weight<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199809[]' id='answer-id-800746' class='answer   answerof-199809 ' value='800746'   \/><label for='answer-id-800746' id='answer-label-800746' class=' answer'><span>Batch<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199809[]' id='answer-id-800747' class='answer   answerof-199809 ' value='800747'   \/><label for='answer-id-800747' id='answer-label-800747' class=' answer'><span>Cosine<\/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-199810'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>15. <\/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\/2021\/11\/image022-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_15' value='199810' \/><input type='hidden' id='answerType199810' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199810[]' id='textarea_q_199810' 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-199811'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>16. <\/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 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image024-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_16' value='199811' \/><input type='hidden' id='answerType199811' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199811[]' id='textarea_q_199811' 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-199812'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>17. <\/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 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image026-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_17' value='199812' \/><input type='hidden' id='answerType199812' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199812[]' id='textarea_q_199812' 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-199813'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>18. <\/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_18' value='199813' \/><input type='hidden' id='answerType199813' 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-199813[]' id='answer-id-800751' class='answer   answerof-199813 ' value='800751'   \/><label for='answer-id-800751' id='answer-label-800751' class=' answer'><span>Spearman correlation<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199813[]' id='answer-id-800752' class='answer   answerof-199813 ' value='800752'   \/><label for='answer-id-800752' id='answer-label-800752' class=' answer'><span>Mutual information<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199813[]' id='answer-id-800753' class='answer   answerof-199813 ' value='800753'   \/><label for='answer-id-800753' id='answer-label-800753' class=' answer'><span>Mann-Whitney test<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199813[]' id='answer-id-800754' class='answer   answerof-199813 ' value='800754'   \/><label for='answer-id-800754' id='answer-label-800754' class=' answer'><span>Pearson\u2019s correlation<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-19' style=';'><div id='questionWrap-19'  class='   watupro-question-id-199814'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>19. <\/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=650 height=477 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image028-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_19' value='199814' \/><input type='hidden' id='answerType199814' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199814[]' id='textarea_q_199814' 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-199815'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>20. <\/span>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=302 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image030-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_20' value='199815' \/><input type='hidden' id='answerType199815' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199815[]' id='textarea_q_199815' 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-199816'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>21. <\/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\/2021\/11\/image032-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_21' value='199816' \/><input type='hidden' id='answerType199816' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199816[]' id='textarea_q_199816' 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-199817'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>22. <\/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 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image034-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_22' value='199817' \/><input type='hidden' id='answerType199817' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199817[]' id='textarea_q_199817' 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-199818'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>23. <\/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 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image036-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_23' value='199818' \/><input type='hidden' id='answerType199818' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199818[]' id='textarea_q_199818' 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-199819'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>24. <\/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_24' value='199819' \/><input type='hidden' id='answerType199819' 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-199819[]' id='answer-id-800760' class='answer   answerof-199819 ' value='800760'   \/><label for='answer-id-800760' id='answer-label-800760' class=' answer'><span>Mutual information<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199819[]' id='answer-id-800761' class='answer   answerof-199819 ' value='800761'   \/><label for='answer-id-800761' id='answer-label-800761' class=' answer'><span>Mood\u2019s median test<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199819[]' id='answer-id-800762' class='answer   answerof-199819 ' value='800762'   \/><label for='answer-id-800762' id='answer-label-800762' class=' answer'><span>Kendall correlation<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199819[]' id='answer-id-800763' class='answer   answerof-199819 ' value='800763'   \/><label for='answer-id-800763' id='answer-label-800763' class=' answer'><span>Permutation Feature Importance<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-25' style=';'><div id='questionWrap-25'  class='   watupro-question-id-199820'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>25. <\/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 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image038-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_25' value='199820' \/><input type='hidden' id='answerType199820' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199820[]' id='textarea_q_199820' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-26' style=';'><div id='questionWrap-26'  class='   watupro-question-id-199821'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>26. <\/span>HOTSPOT <br \/>\r<br>You need to replace the missing data in the Accessibility To High way 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 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image040-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_26' value='199821' \/><input type='hidden' id='answerType199821' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199821[]' id='textarea_q_199821' 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-199822'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>27. <\/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 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image042-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_27' value='199822' \/><input type='hidden' id='answerType199822' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199822[]' id='textarea_q_199822' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-28' style=';'><div id='questionWrap-28'  class='   watupro-question-id-199823'>\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>You train a model and register it in your Azure Machine Learning workspace. You are ready to deploy the model as a real-time web service. <br \/>\r<br>You deploy the model to an Azure Kubernetes Service (AKS) inference cluster, but the deployment fails because an error occurs when the service runs the entry script that is associated with the model deployment. <br \/>\r<br>You need to debug the error by iteratively modifying the code and reloading the service, without requiring a re-deployment of the service for each code update. <br \/>\r<br>What should you do?<\/div><input type='hidden' name='question_id[]' id='qID_28' value='199823' \/><input type='hidden' id='answerType199823' 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-199823[]' id='answer-id-800767' class='answer   answerof-199823 ' value='800767'   \/><label for='answer-id-800767' id='answer-label-800767' class=' answer'><span>Register a new version of the model and update the entry script to load the new version of the model from its registered path.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199823[]' id='answer-id-800768' class='answer   answerof-199823 ' value='800768'   \/><label for='answer-id-800768' id='answer-label-800768' class=' answer'><span>Modify the AKS service deployment configuration to enable application insights and re-deploy to AK<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199823[]' id='answer-id-800769' class='answer   answerof-199823 ' value='800769'   \/><label for='answer-id-800769' id='answer-label-800769' class=' answer'><span>Create an Azure Container Instances (ACI) web service deployment configuration and deploy the model on AC<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199823[]' id='answer-id-800770' class='answer   answerof-199823 ' value='800770'   \/><label for='answer-id-800770' id='answer-label-800770' class=' answer'><span>Add a breakpoint to the first line of the entry script and redeploy the service to AK<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199823[]' id='answer-id-800771' class='answer   answerof-199823 ' value='800771'   \/><label for='answer-id-800771' id='answer-label-800771' class=' answer'><span>Create a local web service deployment configuration and deploy the model to a local Docker container.<\/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-199824'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>29. <\/span>HOTSPOT <br \/>\r<br>You are developing a deep learning model by using TensorFlow. You plan to run the model training workload on an Azure Machine Learning Compute Instance. <br \/>\r<br>You must use CUDA-based model training. <br \/>\r<br>You need to provision the Compute Instance. <br \/>\r<br>Which two virtual machines sizes can you use? To answer, select the appropriate virtual machine sizes in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=650 height=394 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image044-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_29' value='199824' \/><input type='hidden' id='answerType199824' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199824[]' id='textarea_q_199824' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-30' style=';'><div id='questionWrap-30'  class='   watupro-question-id-199825'>\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 have a Python script named train.py in a local folder named scripts. The script trains a regression model by using scikit-learn. The script includes code to load a training data file which is also located in the scripts folder. <br \/>\r<br>You must run the script as an Azure ML experiment on a compute cluster named aml-compute. <br \/>\r<br>You need to configure the run to ensure that the environment includes the required packages for model training. You have instantiated a variable named aml-compute that references the target compute cluster. <br \/>\r<br>Solution: Run the following code: <br \/>\r<br><br><img decoding=\"async\" width=442 height=115 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image046-1.jpg\"><br><br \/>\r<br>Does the solution meet the goal?<\/div><input type='hidden' name='question_id[]' id='qID_30' value='199825' \/><input type='hidden' id='answerType199825' 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-199825[]' id='answer-id-800773' class='answer   answerof-199825 ' value='800773'   \/><label for='answer-id-800773' id='answer-label-800773' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199825[]' id='answer-id-800774' class='answer   answerof-199825 ' value='800774'   \/><label for='answer-id-800774' id='answer-label-800774' 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-199826'>\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 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_31' value='199826' \/><input type='hidden' id='answerType199826' 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-199826[]' id='answer-id-800775' class='answer   answerof-199826 ' value='800775'   \/><label for='answer-id-800775' id='answer-label-800775' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199826[]' id='answer-id-800776' class='answer   answerof-199826 ' value='800776'   \/><label for='answer-id-800776' id='answer-label-800776' 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-199827'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>32. <\/span>You use the following code to define the steps for a pipeline: <br \/>\r<br>from azureml.core import Workspace, Experiment, Run from azureml.pipeline.core import Pipeline <br \/>\r<br>from azureml.pipeline.steps import PythonScriptStep <br \/>\r<br>ws = Workspace.from_config() <br \/>\r<br>. . . <br \/>\r<br>step1 = PythonScriptStep(name=&quot;step1&quot;, ...) <br \/>\r<br>step2 = PythonScriptsStep(name=&quot;step2&quot;, ...) <br \/>\r<br>pipeline_steps = [step1, step2] <br \/>\r<br>You need to add code to run the steps. <br \/>\r<br>Which two code segments can you use 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_32' value='199827' \/><input type='hidden' id='answerType199827' 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-199827[]' id='answer-id-800777' class='answer   answerof-199827 ' value='800777'   \/><label for='answer-id-800777' id='answer-label-800777' class=' answer'><span>experiment = Experiment(workspace=ws, \r\nname='pipeline-experiment') \r\nrun = experiment.submit(config=pipeline_steps)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199827[]' id='answer-id-800778' class='answer   answerof-199827 ' value='800778'   \/><label for='answer-id-800778' id='answer-label-800778' class=' answer'><span>run = Run(pipeline_steps)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199827[]' id='answer-id-800779' class='answer   answerof-199827 ' value='800779'   \/><label for='answer-id-800779' id='answer-label-800779' class=' answer'><span>pipeline = Pipeline(workspace=ws, steps=pipeline_steps) \r\nexperiment = Experiment(workspace=ws, \r\nname='pipeline-experiment') \r\nrun = experiment.submit(pipeline)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199827[]' id='answer-id-800780' class='answer   answerof-199827 ' value='800780'   \/><label for='answer-id-800780' id='answer-label-800780' class=' answer'><span>pipeline = Pipeline(workspace=ws, steps=pipeline_steps) \r\nrun = pipeline.submit(experiment_name='pipeline-experiment')<\/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-199828'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>33. <\/span>You are creating a classification model for a banking company to identify possible instances of credit card fraud. You plan to create the model in Azure Machine Learning by using automated machine learning. <br \/>\r<br>The training dataset that you are using is highly unbalanced. <br \/>\r<br>You need to evaluate the classification model. <br \/>\r<br>Which primary metric should you use?<\/div><input type='hidden' name='question_id[]' id='qID_33' value='199828' \/><input type='hidden' id='answerType199828' 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-199828[]' id='answer-id-800781' class='answer   answerof-199828 ' value='800781'   \/><label for='answer-id-800781' id='answer-label-800781' class=' answer'><span>normalized_mean_absolute_error<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199828[]' id='answer-id-800782' class='answer   answerof-199828 ' value='800782'   \/><label for='answer-id-800782' id='answer-label-800782' class=' answer'><span>[spearman_correlation<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199828[]' id='answer-id-800783' class='answer   answerof-199828 ' value='800783'   \/><label for='answer-id-800783' id='answer-label-800783' class=' answer'><span>AU<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199828[]' id='answer-id-800784' class='answer   answerof-199828 ' value='800784'   \/><label for='answer-id-800784' id='answer-label-800784' class=' answer'><span>weighted<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199828[]' id='answer-id-800785' class='answer   answerof-199828 ' value='800785'   \/><label for='answer-id-800785' id='answer-label-800785' class=' answer'><span>accuracy<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199828[]' id='answer-id-800786' class='answer   answerof-199828 ' value='800786'   \/><label for='answer-id-800786' id='answer-label-800786' class=' answer'><span>normalized_root_mean_squared_error<\/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-199829'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>34. <\/span>You train a machine learning model. <br \/>\r<br>You must deploy the model as a real-time inference service for testing. The service requires low CPU utilization and less than 48 MB of RAM. The compute target for the deployed service must initialize automatically while minimizing cost and administrative overhead. <br \/>\r<br>Which compute target should you use?<\/div><input type='hidden' name='question_id[]' id='qID_34' value='199829' \/><input type='hidden' id='answerType199829' 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-199829[]' id='answer-id-800787' class='answer   answerof-199829 ' value='800787'   \/><label for='answer-id-800787' id='answer-label-800787' class=' answer'><span>Azure Kubernetes Service (AKS) inference cluster<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199829[]' id='answer-id-800788' class='answer   answerof-199829 ' value='800788'   \/><label for='answer-id-800788' id='answer-label-800788' class=' answer'><span>Azure Machine Learning compute cluster<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199829[]' id='answer-id-800789' class='answer   answerof-199829 ' value='800789'   \/><label for='answer-id-800789' id='answer-label-800789' class=' answer'><span>Azure Container Instance (ACI)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199829[]' id='answer-id-800790' class='answer   answerof-199829 ' value='800790'   \/><label for='answer-id-800790' id='answer-label-800790' class=' answer'><span>attached Azure Databricks cluster<\/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-199830'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>35. <\/span>You create an Azure Machine Learning workspace named ML-workspace. You also create an Azure Databricks workspace named DB-workspace. DB-workspace contains a cluster named DB-cluster. <br \/>\r<br>You must use DB-cluster to run experiments from notebooks that you import into DB-workspace. <br \/>\r<br>You need to use ML-workspace to track MLflow metrics and artifacts generated by experiments running on DB-cluster. The solution must minimize the need for custom code. <br \/>\r<br>What should you do?<\/div><input type='hidden' name='question_id[]' id='qID_35' value='199830' \/><input type='hidden' id='answerType199830' 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-199830[]' id='answer-id-800791' class='answer   answerof-199830 ' value='800791'   \/><label for='answer-id-800791' id='answer-label-800791' class=' answer'><span>From DB-cluster, configure the Advanced Logging option.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199830[]' id='answer-id-800792' class='answer   answerof-199830 ' value='800792'   \/><label for='answer-id-800792' id='answer-label-800792' class=' answer'><span>From DB-workspace. configure the Link Azure ML workspace option.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199830[]' id='answer-id-800793' class='answer   answerof-199830 ' value='800793'   \/><label for='answer-id-800793' id='answer-label-800793' class=' answer'><span>From ML-workspace. create an attached compute.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199830[]' id='answer-id-800794' class='answer   answerof-199830 ' value='800794'   \/><label for='answer-id-800794' id='answer-label-800794' class=' answer'><span>From ML-workspace. create a compute cluster.<\/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-199831'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>36. <\/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_36' value='199831' \/><input type='hidden' id='answerType199831' 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-199831[]' id='answer-id-800795' class='answer   answerof-199831 ' value='800795'   \/><label for='answer-id-800795' id='answer-label-800795' 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-199831[]' id='answer-id-800796' class='answer   answerof-199831 ' value='800796'   \/><label for='answer-id-800796' id='answer-label-800796' 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-199831[]' id='answer-id-800797' class='answer   answerof-199831 ' value='800797'   \/><label for='answer-id-800797' id='answer-label-800797' 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-199831[]' id='answer-id-800798' class='answer   answerof-199831 ' value='800798'   \/><label for='answer-id-800798' id='answer-label-800798' 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-37' style=';'><div id='questionWrap-37'  class='   watupro-question-id-199832'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>37. <\/span>DRAG DROP <br \/>\r<br>You have an Azure Machine Learning workspace that contains a training cluster and an inference cluster. <br \/>\r<br>You plan to create a classification model by using the Azure Machine Learning designer. <br \/>\r<br>You need to ensure that client applications can submit data as HTTP requests and receive predictions as responses. <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=231 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image048-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_37' value='199832' \/><input type='hidden' id='answerType199832' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199832[]' id='textarea_q_199832' 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-38' style=';'><div id='questionWrap-38'  class='   watupro-question-id-199833'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>38. <\/span>You are building a recurrent neural network to perform a binary classification. You review the training loss, validation loss, training accuracy, and validation accuracy for each training epoch. <br \/>\r<br>You need to analyze model performance. <br \/>\r<br>Which observation indicates that the classification model is over fitted?<\/div><input type='hidden' name='question_id[]' id='qID_38' value='199833' \/><input type='hidden' id='answerType199833' 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-199833[]' id='answer-id-800800' class='answer   answerof-199833 ' value='800800'   \/><label for='answer-id-800800' id='answer-label-800800' 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><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199833[]' id='answer-id-800801' class='answer   answerof-199833 ' value='800801'   \/><label for='answer-id-800801' id='answer-label-800801' 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-199833[]' id='answer-id-800802' class='answer   answerof-199833 ' value='800802'   \/><label for='answer-id-800802' id='answer-label-800802' 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-199833[]' id='answer-id-800803' class='answer   answerof-199833 ' value='800803'   \/><label for='answer-id-800803' id='answer-label-800803' class=' answer'><span>The training loss stays constant and the validation loss decreases when training the model.<\/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-199834'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>39. <\/span>HOTSPOT <br \/>\r<br>You plan to preprocess text from CSV files. You load the Azure Machine Learning Studio default stop words list. <br \/>\r<br>You need to configure the Preprocess Text module to meet the following requirements: <br \/>\r<br>&#10001; Ensure that multiple related words from a single canonical form. <br \/>\r<br>&#10001; Remove pipe characters from text. <br \/>\r<br>&#10001; Remove words to optimize information retrieval. <br \/>\r<br>Which three options should you select? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=396 height=690 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image050.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_39' value='199834' \/><input type='hidden' id='answerType199834' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199834[]' id='textarea_q_199834' 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-199835'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>40. <\/span>You plan to deliver a hands-on workshop to several students. The workshop will focus on creating data <br \/>\r<br>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 <br \/>\r<br>install software on their devices. Azure subscriptions are not available for students. <br \/>\r<br>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_40' value='199835' \/><input type='hidden' id='answerType199835' 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-199835[]' id='answer-id-800805' class='answer   answerof-199835 ' value='800805'   \/><label for='answer-id-800805' id='answer-label-800805' class=' answer'><span>Anaconda Data Science Platform<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199835[]' id='answer-id-800806' class='answer   answerof-199835 ' value='800806'   \/><label for='answer-id-800806' id='answer-label-800806' class=' answer'><span>Azure BatchAl<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199835[]' id='answer-id-800807' class='answer   answerof-199835 ' value='800807'   \/><label for='answer-id-800807' id='answer-label-800807' class=' answer'><span>Azure Notebooks<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199835[]' id='answer-id-800808' class='answer   answerof-199835 ' value='800808'   \/><label for='answer-id-800808' id='answer-label-800808' class=' answer'><span>Azure Machine Learning Service<\/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-199836'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>41. <\/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_41' value='199836' \/><input type='hidden' id='answerType199836' 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-199836[]' id='answer-id-800809' class='answer   answerof-199836 ' value='800809'   \/><label for='answer-id-800809' id='answer-label-800809' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199836[]' id='answer-id-800810' class='answer   answerof-199836 ' value='800810'   \/><label for='answer-id-800810' id='answer-label-800810' class=' answer'><span>No<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-42' style=';'><div id='questionWrap-42'  class='   watupro-question-id-199837'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>42. <\/span>HOTSPOT <br \/>\r<br>You plan to use Hyperdrive to optimize the hyperparameters selected when training a model. <br \/>\r<br>You create the following code to define options for the hyperparameter experiment <br \/>\r<br><br><img decoding=\"async\" width=600 height=240 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image052.gif\"><br><br \/>\r<br>For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=650 height=234 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image053.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_42' value='199837' \/><input type='hidden' id='answerType199837' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199837[]' id='textarea_q_199837' 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-199838'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>43. <\/span>You create a batch inference pipeline by using the Azure ML SDK. <br \/>\r<br>You run the pipeline by using the following code: <br \/>\r<br>from azureml.pipeline.core import Pipeline <br \/>\r<br>from azureml.core.experiment import Experiment <br \/>\r<br>pipeline = Pipeline(workspace=ws, steps=[parallelrun_step]) <br \/>\r<br>pipeline_run = Experiment(ws, 'batch_pipeline').submit(pipeline) <br \/>\r<br>You need to monitor the progress of the pipeline execution. <br \/>\r<br>What are two 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_43' value='199838' \/><input type='hidden' id='answerType199838' 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-199838[]' id='answer-id-800812' class='answer   answerof-199838 ' value='800812'   \/><label for='answer-id-800812' id='answer-label-800812' class=' answer'><span>Run the following code in a notebook: \r\n<br><img decoding=\"async\" width=650 height=118 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image055.jpg\"><br><\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199838[]' id='answer-id-800813' class='answer   answerof-199838 ' value='800813'   \/><label for='answer-id-800813' id='answer-label-800813' class=' answer'><span>Use the Inference Clusters tab in Machine Learning Studio.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199838[]' id='answer-id-800814' class='answer   answerof-199838 ' value='800814'   \/><label for='answer-id-800814' id='answer-label-800814' class=' answer'><span>Use the Activity log in the Azure portal for the Machine Learning workspace.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199838[]' id='answer-id-800815' class='answer   answerof-199838 ' value='800815'   \/><label for='answer-id-800815' id='answer-label-800815' class=' answer'><span>Run the following code in a notebook: \r\n<br><img decoding=\"async\" width=325 height=32 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image056.jpg\"><br><\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199838[]' id='answer-id-800816' class='answer   answerof-199838 ' value='800816'   \/><label for='answer-id-800816' id='answer-label-800816' class=' answer'><span>Run the following code and monitor the console output from the PipelineRun object: \r\n<br><img decoding=\"async\" width=424 height=14 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image057.jpg\"><br><\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-44' style=';'><div id='questionWrap-44'  class='   watupro-question-id-199839'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>44. <\/span>You are evaluating a completed binary classification machine. <br \/>\r<br>You need to use the precision as the evaluation metric. <br \/>\r<br>Which visualization should you use?<\/div><input type='hidden' name='question_id[]' id='qID_44' value='199839' \/><input type='hidden' id='answerType199839' 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-199839[]' id='answer-id-800817' class='answer   answerof-199839 ' value='800817'   \/><label for='answer-id-800817' id='answer-label-800817' class=' answer'><span>scatter plot<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199839[]' id='answer-id-800818' class='answer   answerof-199839 ' value='800818'   \/><label for='answer-id-800818' id='answer-label-800818' class=' answer'><span>coefficient of determination<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199839[]' id='answer-id-800819' class='answer   answerof-199839 ' value='800819'   \/><label for='answer-id-800819' id='answer-label-800819' class=' answer'><span>Receiver Operating Characteristic CROC) curve<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199839[]' id='answer-id-800820' class='answer   answerof-199839 ' value='800820'   \/><label for='answer-id-800820' id='answer-label-800820' class=' answer'><span>Gradient descent<\/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-199840'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>45. <\/span>HOTSPOT <br \/>\r<br>You publish a batch inferencing pipeline that will be used by a business application. <br \/>\r<br>The application developers need to know which information should be submitted to and returned by the REST interface for the published pipeline. <br \/>\r<br>You need to identify the information required in the REST request and returned as a response from the published pipeline. <br \/>\r<br>Which values should you use in the REST request and to expect in the response? 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=283 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image058.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_45' value='199840' \/><input type='hidden' id='answerType199840' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199840[]' id='textarea_q_199840' 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-46' style=';'><div id='questionWrap-46'  class='   watupro-question-id-199841'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>46. <\/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_46' value='199841' \/><input type='hidden' id='answerType199841' 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-199841[]' id='answer-id-800822' class='answer   answerof-199841 ' value='800822'   \/><label for='answer-id-800822' id='answer-label-800822' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199841[]' id='answer-id-800823' class='answer   answerof-199841 ' value='800823'   \/><label for='answer-id-800823' id='answer-label-800823' class=' answer'><span>No<\/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-199842'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>47. <\/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_47' value='199842' \/><input type='hidden' id='answerType199842' 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-199842[]' id='answer-id-800824' class='answer   answerof-199842 ' value='800824'   \/><label for='answer-id-800824' id='answer-label-800824' class=' answer'><span>Microsoft Hardware-Assisted Virtualization Detection Tool<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199842[]' id='answer-id-800825' class='answer   answerof-199842 ' value='800825'   \/><label for='answer-id-800825' id='answer-label-800825' class=' answer'><span>Kitematic<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199842[]' id='answer-id-800826' class='answer   answerof-199842 ' value='800826'   \/><label for='answer-id-800826' id='answer-label-800826' class=' answer'><span>BIOS-enabled virtualization<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199842[]' id='answer-id-800827' class='answer   answerof-199842 ' value='800827'   \/><label for='answer-id-800827' id='answer-label-800827' class=' answer'><span>VirtualBox<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199842[]' id='answer-id-800828' class='answer   answerof-199842 ' value='800828'   \/><label for='answer-id-800828' id='answer-label-800828' 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-48' style=';'><div id='questionWrap-48'  class='   watupro-question-id-199843'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>48. <\/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_48' value='199843' \/><input type='hidden' id='answerType199843' 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-199843[]' id='answer-id-800829' class='answer   answerof-199843 ' value='800829'   \/><label for='answer-id-800829' id='answer-label-800829' class=' answer'><span>k=0.5<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199843[]' id='answer-id-800830' class='answer   answerof-199843 ' value='800830'   \/><label for='answer-id-800830' id='answer-label-800830' class=' answer'><span>k=0<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199843[]' id='answer-id-800831' class='answer   answerof-199843 ' value='800831'   \/><label for='answer-id-800831' id='answer-label-800831' class=' answer'><span>k=5<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199843[]' id='answer-id-800832' class='answer   answerof-199843 ' value='800832'   \/><label for='answer-id-800832' id='answer-label-800832' class=' answer'><span>k=1<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-49' style=';'><div id='questionWrap-49'  class='   watupro-question-id-199844'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>49. <\/span>HOTSPOT <br \/>\r<br>A coworker registers a datastore in a Machine Learning services workspace by using the following code: <br \/>\r<br><br><img decoding=\"async\" width=540 height=150 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image061.jpg\"><br><br \/>\r<br>You need to write code to access the datastore from a notebook. <br \/>\r<br><br><img decoding=\"async\" width=649 height=167 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image062.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_49' value='199844' \/><input type='hidden' id='answerType199844' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199844[]' id='textarea_q_199844' 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-50' style=';'><div id='questionWrap-50'  class='   watupro-question-id-199845'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>50. <\/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. <br \/>\r<br>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_50' value='199845' \/><input type='hidden' id='answerType199845' 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-199845[]' id='answer-id-800834' class='answer   answerof-199845 ' value='800834'   \/><label for='answer-id-800834' id='answer-label-800834' class=' answer'><span>k=1<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199845[]' id='answer-id-800835' class='answer   answerof-199845 ' value='800835'   \/><label for='answer-id-800835' id='answer-label-800835' class=' answer'><span>k=10<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199845[]' id='answer-id-800836' class='answer   answerof-199845 ' value='800836'   \/><label for='answer-id-800836' id='answer-label-800836' class=' answer'><span>k=0.5<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199845[]' id='answer-id-800837' class='answer   answerof-199845 ' value='800837'   \/><label for='answer-id-800837' id='answer-label-800837' class=' answer'><span>k=0.9<\/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-199846'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>51. <\/span>You write a Python script that processes data in a comma-separated values (CSV) file. <br \/>\r<br>You plan to run this script as an Azure Machine Learning experiment. <br \/>\r<br>The script loads the data and determines the number of rows it contains using the following code: <br \/>\r<br><br><img decoding=\"async\" width=315 height=152 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image064.jpg\"><br><br \/>\r<br>You need to record the row count as a metric named row_count that can be returned using the get_metrics method of the Run object after the experiment run completes. <br \/>\r<br>Which code should you use?<\/div><input type='hidden' name='question_id[]' id='qID_51' value='199846' \/><input type='hidden' id='answerType199846' 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-199846[]' id='answer-id-800838' class='answer   answerof-199846 ' value='800838'   \/><label for='answer-id-800838' id='answer-label-800838' class=' answer'><span>run.upload_file(\u2018row_count\u2019, \u2018.\/data.csv\u2019)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199846[]' id='answer-id-800839' class='answer   answerof-199846 ' value='800839'   \/><label for='answer-id-800839' id='answer-label-800839' class=' answer'><span>run.log(\u2018row_count\u2019, rows)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199846[]' id='answer-id-800840' class='answer   answerof-199846 ' value='800840'   \/><label for='answer-id-800840' id='answer-label-800840' class=' answer'><span>run.tag(\u2018row_count\u2019, rows)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199846[]' id='answer-id-800841' class='answer   answerof-199846 ' value='800841'   \/><label for='answer-id-800841' id='answer-label-800841' class=' answer'><span>run.log_table(\u2018row_count\u2019, rows)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199846[]' id='answer-id-800842' class='answer   answerof-199846 ' value='800842'   \/><label for='answer-id-800842' id='answer-label-800842' class=' answer'><span>run.log_row(\u2018row_count\u2019, rows)<\/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-199847'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>52. <\/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 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image065.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_52' value='199847' \/><input type='hidden' id='answerType199847' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199847[]' id='textarea_q_199847' 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-53' style=';'><div id='questionWrap-53'  class='   watupro-question-id-199848'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>53. <\/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_53' value='199848' \/><input type='hidden' id='answerType199848' 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-199848[]' id='answer-id-800844' class='answer   answerof-199848 ' value='800844'   \/><label for='answer-id-800844' id='answer-label-800844' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199848[]' id='answer-id-800845' class='answer   answerof-199848 ' value='800845'   \/><label for='answer-id-800845' id='answer-label-800845' class=' answer'><span>No<\/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-199849'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>54. <\/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 create an Azure Machine Learning service datastore in a workspace. <br \/>\r<br>The datastore contains the following files: <br \/>\r<br>&#8226; \/data\/2018\/Q1 .csv <br \/>\r<br>&#8226; \/data\/2018\/Q2.csv <br \/>\r<br>&#8226; \/data\/2018\/Q3.csv <br \/>\r<br>&#8226; \/data\/2018\/Q4.csv <br \/>\r<br>&#8226; \/data\/2019\/Q1.csv <br \/>\r<br>All files store data in the following format: <br \/>\r<br>id,M,f2,l <br \/>\r<br>1,1,2,0 <br \/>\r<br>2,1,1,1 <br \/>\r<br>32,10 <br \/>\r<br>You run the following code: <br \/>\r<br><br><img decoding=\"async\" width=615 height=109 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image067.jpg\"><br><br \/>\r<br>You need to create a dataset named training_data and load the data from all files into a single data frame by using the following code: <br \/>\r<br><br><img decoding=\"async\" width=485 height=15 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image068.jpg\"><br><br \/>\r<br>Solution: Run the following code: <br \/>\r<br><br><img decoding=\"async\" width=400 height=48 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image069.jpg\"><br><br \/>\r<br>Does the solution meet the goal?<\/div><input type='hidden' name='question_id[]' id='qID_54' value='199849' \/><input type='hidden' id='answerType199849' 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-199849[]' id='answer-id-800846' class='answer   answerof-199849 ' value='800846'   \/><label for='answer-id-800846' id='answer-label-800846' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199849[]' id='answer-id-800847' class='answer   answerof-199849 ' value='800847'   \/><label for='answer-id-800847' id='answer-label-800847' class=' answer'><span>No<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-55' style=';'><div id='questionWrap-55'  class='   watupro-question-id-199850'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>55. <\/span>HOTSPOT <br \/>\r<br>You are running a training experiment on remote compute in Azure Machine Learning. <br \/>\r<br>The experiment is configured to use a conda environment that includes the mlflow and azureml-contrib-run packages. <br \/>\r<br>You must use MLflow as the logging package for tracking metrics generated in the experiment. <br \/>\r<br>You need to complete the script for the experiment. <br \/>\r<br>How should you complete the code? 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=340 height=535 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image070.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_55' value='199850' \/><input type='hidden' id='answerType199850' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199850[]' id='textarea_q_199850' 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-56' style=';'><div id='questionWrap-56'  class='   watupro-question-id-199851'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>56. <\/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 to run an experiment that trains a classification model. <br \/>\r<br>You want to use Hyperdrive to find parameters that optimize the AUC metric for the model. <br \/>\r<br>You configure a HyperDriveConfig for the experiment by running the following code: <br \/>\r<br><br><img decoding=\"async\" width=494 height=140 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image072.jpg\"><br><br \/>\r<br>variable named y_test variable, and the predicted probabilities from the model are stored in a variable named y_predicted. You need to add logging to the script to allow Hyperdrive to optimize hyperparameters for the AUC metric. <br \/>\r<br>Solution: Run the following code: <br \/>\r<br><br><img decoding=\"async\" width=363 height=102 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image073.jpg\"><br><br \/>\r<br>Does the solution meet the goal?<\/div><input type='hidden' name='question_id[]' id='qID_56' value='199851' \/><input type='hidden' id='answerType199851' 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-199851[]' id='answer-id-800849' class='answer   answerof-199851 ' value='800849'   \/><label for='answer-id-800849' id='answer-label-800849' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199851[]' id='answer-id-800850' class='answer   answerof-199851 ' value='800850'   \/><label for='answer-id-800850' id='answer-label-800850' class=' answer'><span>No<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-57' style=';'><div id='questionWrap-57'  class='   watupro-question-id-199852'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>57. <\/span>You create a Python script that runs a training experiment in Azure Machine Learning. The script uses the Azure Machine Learning SDK for Python. <br \/>\r<br>You must add a statement that retrieves the names of the logs and outputs generated by the script. <br \/>\r<br>You need to reference a Python class object from the SDK for the statement. <br \/>\r<br>Which class object should you use?<\/div><input type='hidden' name='question_id[]' id='qID_57' value='199852' \/><input type='hidden' id='answerType199852' 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-199852[]' id='answer-id-800851' class='answer   answerof-199852 ' value='800851'   \/><label for='answer-id-800851' id='answer-label-800851' class=' answer'><span>Run<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199852[]' id='answer-id-800852' class='answer   answerof-199852 ' value='800852'   \/><label for='answer-id-800852' id='answer-label-800852' class=' answer'><span>ScripcRunConfig<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199852[]' id='answer-id-800853' class='answer   answerof-199852 ' value='800853'   \/><label for='answer-id-800853' id='answer-label-800853' class=' answer'><span>Workspace<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199852[]' id='answer-id-800854' class='answer   answerof-199852 ' value='800854'   \/><label for='answer-id-800854' id='answer-label-800854' class=' answer'><span>Experiment<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-58' style=';'><div id='questionWrap-58'  class='   watupro-question-id-199853'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>58. <\/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_58' value='199853' \/><input type='hidden' id='answerType199853' 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-199853[]' id='answer-id-800855' class='answer   answerof-199853 ' value='800855'   \/><label for='answer-id-800855' id='answer-label-800855' class=' answer'><span>M<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199853[]' id='answer-id-800856' class='answer   answerof-199853 ' value='800856'   \/><label for='answer-id-800856' id='answer-label-800856' class=' answer'><span>NET Library on a local environment<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199853[]' id='answer-id-800857' class='answer   answerof-199853 ' value='800857'   \/><label for='answer-id-800857' id='answer-label-800857' class=' answer'><span>Azure Machine Learning Studio<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199853[]' id='answer-id-800858' class='answer   answerof-199853 ' value='800858'   \/><label for='answer-id-800858' id='answer-label-800858' class=' answer'><span>Data Science Virtual Machine (OSVM)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199853[]' id='answer-id-800859' class='answer   answerof-199853 ' value='800859'   \/><label for='answer-id-800859' id='answer-label-800859' class=' answer'><span>Azure Data bricks<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199853[]' id='answer-id-800860' class='answer   answerof-199853 ' value='800860'   \/><label for='answer-id-800860' id='answer-label-800860' class=' answer'><span>Azure Cognitive Services<\/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-199854'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>59. <\/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 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image074.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_59' value='199854' \/><input type='hidden' id='answerType199854' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199854[]' id='textarea_q_199854' 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-60' style=';'><div id='questionWrap-60'  class='   watupro-question-id-199855'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>60. <\/span>You write five Python scripts that must be processed in the order specified in Exhibit A C which allows the same modules to run in parallel, but will wait for modules with dependencies. <br \/>\r<br>You must create an Azure Machine Learning pipeline using the Python SDK, because you want to script to create the pipeline to be tracked in your version control system. You have created five PythonScriptSteps and have named the variables to match the module names. <br \/>\r<br><br><img decoding=\"async\" width=649 height=254 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image076.jpg\"><br><br \/>\r<br>You need to create the pipeline shown. Assume all relevant imports have been done. <br \/>\r<br>Which Python code segment should you use? <br \/>\r<br>A) <br \/>\r<br><br><img decoding=\"async\" width=650 height=16 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image077.jpg\"><br><br \/>\r<br>B) <br \/>\r<br><br><img decoding=\"async\" width=388 height=305 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image078.jpg\"><br><br \/>\r<br>C) <br \/>\r<br><br><img decoding=\"async\" width=317 height=107 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image079.jpg\"><br><br \/>\r<br>D) <br \/>\r<br><br><img decoding=\"async\" width=650 height=17 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image080.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_60' value='199855' \/><input type='hidden' id='answerType199855' 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-199855[]' id='answer-id-800862' class='answer   answerof-199855 ' value='800862'   \/><label for='answer-id-800862' id='answer-label-800862' class=' answer'><span>Option A<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199855[]' id='answer-id-800863' class='answer   answerof-199855 ' value='800863'   \/><label for='answer-id-800863' id='answer-label-800863' class=' answer'><span>Option B<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199855[]' id='answer-id-800864' class='answer   answerof-199855 ' value='800864'   \/><label for='answer-id-800864' id='answer-label-800864' class=' answer'><span>Option C<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199855[]' id='answer-id-800865' class='answer   answerof-199855 ' value='800865'   \/><label for='answer-id-800865' id='answer-label-800865' class=' answer'><span>Option D<\/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-199856'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>61. <\/span>You create a script that trains a convolutional neural network model over multiple epochs and logs the validation loss after each epoch. The script includes arguments for batch size and learning rate. <br \/>\r<br>You identify a set of batch size and learning rate values that you want to try. <br \/>\r<br>You need to use Azure Machine Learning to find the combination of batch size and learning rate that results in the model with the lowest validation loss. <br \/>\r<br>What should you do?<\/div><input type='hidden' name='question_id[]' id='qID_61' value='199856' \/><input type='hidden' id='answerType199856' 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-199856[]' id='answer-id-800866' class='answer   answerof-199856 ' value='800866'   \/><label for='answer-id-800866' id='answer-label-800866' class=' answer'><span>Run the script in an experiment based on an AutoMLConfig object<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199856[]' id='answer-id-800867' class='answer   answerof-199856 ' value='800867'   \/><label for='answer-id-800867' id='answer-label-800867' class=' answer'><span>Create a PythonScriptStep object for the script and run it in a pipeline<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199856[]' id='answer-id-800868' class='answer   answerof-199856 ' value='800868'   \/><label for='answer-id-800868' id='answer-label-800868' class=' answer'><span>Use the Automated Machine Learning interface in Azure Machine Learning studio<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199856[]' id='answer-id-800869' class='answer   answerof-199856 ' value='800869'   \/><label for='answer-id-800869' id='answer-label-800869' class=' answer'><span>Run the script in an experiment based on a ScriptRunConfig object<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199856[]' id='answer-id-800870' class='answer   answerof-199856 ' value='800870'   \/><label for='answer-id-800870' id='answer-label-800870' class=' answer'><span>Run the script in an experiment based on a HyperDriveConfig object<\/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-199857'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>62. <\/span>You create a deep learning model for image recognition on Azure Machine Learning service using GPU-based training. <br \/>\r<br>You must deploy the model to a context that allows for real-time GPU-based inferencing. <br \/>\r<br>You need to configure compute resources for model inferencing. <br \/>\r<br>Which compute type should you use?<\/div><input type='hidden' name='question_id[]' id='qID_62' value='199857' \/><input type='hidden' id='answerType199857' 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-199857[]' id='answer-id-800871' class='answer   answerof-199857 ' value='800871'   \/><label for='answer-id-800871' id='answer-label-800871' class=' answer'><span>Azure Container Instance<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199857[]' id='answer-id-800872' class='answer   answerof-199857 ' value='800872'   \/><label for='answer-id-800872' id='answer-label-800872' class=' answer'><span>Azure Kubernetes Service<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199857[]' id='answer-id-800873' class='answer   answerof-199857 ' value='800873'   \/><label for='answer-id-800873' id='answer-label-800873' class=' answer'><span>Field Programmable Gate Array<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199857[]' id='answer-id-800874' class='answer   answerof-199857 ' value='800874'   \/><label for='answer-id-800874' id='answer-label-800874' class=' answer'><span>Machine Learning Compute<\/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-199858'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>63. <\/span>You are a lead data scientist for a project that tracks the health and migration of birds. You create a multi-class image classification deep learning model that uses a set of labeled bird photographs collected by experts. <br \/>\r<br>You have 100,000 photographs of birds. All photographs use the JPG format and are stored in an Azure blob container in an Azure subscription. <br \/>\r<br>You need to access the bird photograph files in the Azure blob container from the Azure Machine Learning service workspace that will be used for deep learning model training. You must minimize data movement. <br \/>\r<br>What should you do?<\/div><input type='hidden' name='question_id[]' id='qID_63' value='199858' \/><input type='hidden' id='answerType199858' 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-199858[]' id='answer-id-800875' class='answer   answerof-199858 ' value='800875'   \/><label for='answer-id-800875' id='answer-label-800875' class=' answer'><span>Create an Azure Data Lake store and move the bird photographs to the store.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199858[]' id='answer-id-800876' class='answer   answerof-199858 ' value='800876'   \/><label for='answer-id-800876' id='answer-label-800876' class=' answer'><span>Create an Azure Cosmos DB database and attach the Azure Blob containing bird photographs storage to the database.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199858[]' id='answer-id-800877' class='answer   answerof-199858 ' value='800877'   \/><label for='answer-id-800877' id='answer-label-800877' class=' answer'><span>Create and register a dataset by using TabularDataset class that references the Azure blob storage \r\ncontaining bird photographs.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199858[]' id='answer-id-800878' class='answer   answerof-199858 ' value='800878'   \/><label for='answer-id-800878' id='answer-label-800878' class=' answer'><span>Register the Azure blob storage containing the bird photographs as a datastore in Azure Machine Learning service.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199858[]' id='answer-id-800879' class='answer   answerof-199858 ' value='800879'   \/><label for='answer-id-800879' id='answer-label-800879' class=' answer'><span>Copy the bird photographs to the blob datastore that was created with your Azure Machine Learning service workspace.<\/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-199859'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>64. <\/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_64' value='199859' \/><input type='hidden' id='answerType199859' 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-199859[]' id='answer-id-800880' class='answer   answerof-199859 ' value='800880'   \/><label for='answer-id-800880' id='answer-label-800880' class=' answer'><span>Split Data<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199859[]' id='answer-id-800881' class='answer   answerof-199859 ' value='800881'   \/><label for='answer-id-800881' id='answer-label-800881' class=' answer'><span>Load Trained Model<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199859[]' id='answer-id-800882' class='answer   answerof-199859 ' value='800882'   \/><label for='answer-id-800882' id='answer-label-800882' class=' answer'><span>Assign Data to Clusters<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199859[]' id='answer-id-800883' class='answer   answerof-199859 ' value='800883'   \/><label for='answer-id-800883' id='answer-label-800883' class=' answer'><span>Group Data into Bins<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-65' style=';'><div id='questionWrap-65'  class='   watupro-question-id-199860'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>65. <\/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>An IT department creates the following Azure resource groups and resources: <br \/>\r<br><br><img decoding=\"async\" width=650 height=185 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image081.jpg\"><br><br \/>\r<br>The IT department creates an Azure Kubernetes Service (AKS)-based inference compute target named aks-cluster in the Azure Machine Learning workspace. <br \/>\r<br>You have a Microsoft Surface Book computer with a GPU. Python 3.6 and Visual Studio Code are installed. <br \/>\r<br>You need to run a script that trains a deep neural network (DNN) model and logs the loss and accuracy metrics. <br \/>\r<br>Solution: Attach the mlvm virtual machine as a compute target in the Azure Machine Learning workspace. Install the Azure ML SDK on the Surface Book and run Python code to connect to the workspace. Run the training script as an experiment on the mlvm remote compute resource.<\/div><input type='hidden' name='question_id[]' id='qID_65' value='199860' \/><input type='hidden' id='answerType199860' 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-199860[]' id='answer-id-800884' class='answer   answerof-199860 ' value='800884'   \/><label for='answer-id-800884' id='answer-label-800884' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199860[]' id='answer-id-800885' class='answer   answerof-199860 ' value='800885'   \/><label for='answer-id-800885' id='answer-label-800885' class=' answer'><span>No<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-66' style=';'><div id='questionWrap-66'  class='   watupro-question-id-199861'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>66. <\/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_66' value='199861' \/><input type='hidden' id='answerType199861' 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-199861[]' id='answer-id-800886' class='answer   answerof-199861 ' value='800886'   \/><label for='answer-id-800886' id='answer-label-800886' class=' answer'><span>an F1 score that is high<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199861[]' id='answer-id-800887' class='answer   answerof-199861 ' value='800887'   \/><label for='answer-id-800887' id='answer-label-800887' 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-199861[]' id='answer-id-800888' class='answer   answerof-199861 ' value='800888'   \/><label for='answer-id-800888' id='answer-label-800888' 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-199861[]' id='answer-id-800889' class='answer   answerof-199861 ' value='800889'   \/><label for='answer-id-800889' id='answer-label-800889' 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-199861[]' id='answer-id-800890' class='answer   answerof-199861 ' value='800890'   \/><label for='answer-id-800890' id='answer-label-800890' 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-199861[]' id='answer-id-800891' class='answer   answerof-199861 ' value='800891'   \/><label for='answer-id-800891' id='answer-label-800891' 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-67' style=';'><div id='questionWrap-67'  class='   watupro-question-id-199862'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>67. <\/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_67' value='199862' \/><input type='hidden' id='answerType199862' 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-199862[]' id='answer-id-800892' class='answer   answerof-199862 ' value='800892'   \/><label for='answer-id-800892' id='answer-label-800892' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199862[]' id='answer-id-800893' class='answer   answerof-199862 ' value='800893'   \/><label for='answer-id-800893' id='answer-label-800893' class=' answer'><span>No<\/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-199863'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>68. <\/span>DRAG DROP <br \/>\r<br>You previously deployed a model that was trained using a tabular dataset named training-dataset, which is based on a folder of CSV files. <br \/>\r<br>Over time, you have collected the features and predicted labels generated by the model in a folder containing a CSV file for each month. You have created two tabular datasets based on the folder containing the inference data: one named predictions-dataset with a schema that matches the training data exactly, including the predicted label; and another named features-dataset with a schema containing all of the feature columns and a timestamp column based on the filename, which includes the day, month, and year. <br \/>\r<br>You need to create a data drift monitor to identify any changing trends in the feature data since the model was trained. To accomplish this, you must define the required datasets for the data drift monitor. <br \/>\r<br>Which datasets should you use to configure the data drift monitor? To answer, drag the appropriate datasets to the correct data drift monitor options. Each source 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=647 height=146 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image082.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_68' value='199863' \/><input type='hidden' id='answerType199863' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199863[]' id='textarea_q_199863' 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-199864'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>69. <\/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 plan to use a Python script to run an Azure Machine Learning experiment. <br \/>\r<br>The script creates a reference to the experiment run context, loads data from a file, identifies the set of unique values for the label column, and completes the experiment run: <br \/>\r<br>from azureml.core import Run <br \/>\r<br>import pandas as pd <br \/>\r<br>run = Run.get_context() <br \/>\r<br>data = pd.read_csv('data.csv') <br \/>\r<br>label_vals = data['label'].unique() <br \/>\r<br># Add code to record metrics here run.complete() <br \/>\r<br>The experiment must record the unique labels in the data as metrics for the run that can be reviewed later. <br \/>\r<br>You must add code to the script to record the unique label values as run metrics at the point indicated by the comment. <br \/>\r<br>Solution: Replace the comment with the following code: <br \/>\r<br>for label_val in label_vals: <br \/>\r<br>run.log('Label Values', label_val) <br \/>\r<br>Does the solution meet the goal?<\/div><input type='hidden' name='question_id[]' id='qID_69' value='199864' \/><input type='hidden' id='answerType199864' 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-199864[]' id='answer-id-800895' class='answer   answerof-199864 ' value='800895'   \/><label for='answer-id-800895' id='answer-label-800895' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199864[]' id='answer-id-800896' class='answer   answerof-199864 ' value='800896'   \/><label for='answer-id-800896' id='answer-label-800896' class=' answer'><span>No<\/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-199865'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>70. <\/span>You register a model that you plan to use in a batch inference pipeline. <br \/>\r<br>The batch inference pipeline must use a ParallelRunStep step to process files in a file dataset. The script has the ParallelRunStep step runs must process six input files each time the inferencing function is called. <br \/>\r<br>You need to configure the pipeline. <br \/>\r<br>Which configuration setting should you specify in the ParallelRunConfig object for the PrallelRunStep step?<\/div><input type='hidden' name='question_id[]' id='qID_70' value='199865' \/><input type='hidden' id='answerType199865' 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-199865[]' id='answer-id-800897' class='answer   answerof-199865 ' value='800897'   \/><label for='answer-id-800897' id='answer-label-800897' class=' answer'><span>process_count_per_node= &quot;6&quot;<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199865[]' id='answer-id-800898' class='answer   answerof-199865 ' value='800898'   \/><label for='answer-id-800898' id='answer-label-800898' class=' answer'><span>node_count= &quot;6&quot;<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199865[]' id='answer-id-800899' class='answer   answerof-199865 ' value='800899'   \/><label for='answer-id-800899' id='answer-label-800899' class=' answer'><span>mini_batch_size= &quot;6&quot;<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199865[]' id='answer-id-800900' class='answer   answerof-199865 ' value='800900'   \/><label for='answer-id-800900' id='answer-label-800900' class=' answer'><span>error_threshold= &quot;6&quot;<\/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-199866'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>71. <\/span>You are a data scientist working for a bank and have used Azure ML to train and register a machine learning model that predicts whether a customer is likely to repay a loan. <br \/>\r<br>You want to understand how your model is making selections and must be sure that the model does not violate government regulations such as denying loans based on where an applicant lives. <br \/>\r<br>You need to determine the extent to which each feature in the customer data is influencing predictions. <br \/>\r<br>What should you do?<\/div><input type='hidden' name='question_id[]' id='qID_71' value='199866' \/><input type='hidden' id='answerType199866' 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-199866[]' id='answer-id-800901' class='answer   answerof-199866 ' value='800901'   \/><label for='answer-id-800901' id='answer-label-800901' class=' answer'><span>Enable data drift monitoring for the model and its training dataset.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199866[]' id='answer-id-800902' class='answer   answerof-199866 ' value='800902'   \/><label for='answer-id-800902' id='answer-label-800902' class=' answer'><span>Score the model against some test data with known label values and use the results to calculate a confusion matrix.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199866[]' id='answer-id-800903' class='answer   answerof-199866 ' value='800903'   \/><label for='answer-id-800903' id='answer-label-800903' class=' answer'><span>Use the Hyperdrive library to test the model with multiple hyperparameter values.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199866[]' id='answer-id-800904' class='answer   answerof-199866 ' value='800904'   \/><label for='answer-id-800904' id='answer-label-800904' class=' answer'><span>Use the interpretability package to generate an explainer for the model.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199866[]' id='answer-id-800905' class='answer   answerof-199866 ' value='800905'   \/><label for='answer-id-800905' id='answer-label-800905' class=' answer'><span>Add tags to the model registration indicating the names of the features in the training dataset.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-72' style=';'><div id='questionWrap-72'  class='   watupro-question-id-199867'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>72. <\/span>You deploy a model as an Azure Machine Learning real-time web service using the following code. <br \/>\r<br><br><img decoding=\"async\" width=650 height=58 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image084.jpg\"><br><br \/>\r<br>The deployment fails. <br \/>\r<br>You need to troubleshoot the deployment failure by determining the actions that were performed during deployment and identifying the specific action that failed. <br \/>\r<br>Which code segment should you run?<\/div><input type='hidden' name='question_id[]' id='qID_72' value='199867' \/><input type='hidden' id='answerType199867' 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-199867[]' id='answer-id-800906' class='answer   answerof-199867 ' value='800906'   \/><label for='answer-id-800906' id='answer-label-800906' class=' answer'><span>service.get_logs()<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199867[]' id='answer-id-800907' class='answer   answerof-199867 ' value='800907'   \/><label for='answer-id-800907' id='answer-label-800907' class=' answer'><span>service.state<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199867[]' id='answer-id-800908' class='answer   answerof-199867 ' value='800908'   \/><label for='answer-id-800908' id='answer-label-800908' class=' answer'><span>service.serialize()<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199867[]' id='answer-id-800909' class='answer   answerof-199867 ' value='800909'   \/><label for='answer-id-800909' id='answer-label-800909' class=' answer'><span>service.update_deployment_state()<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-73' style=';'><div id='questionWrap-73'  class='   watupro-question-id-199868'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>73. <\/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 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image085.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 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image086.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_73' value='199868' \/><input type='hidden' id='answerType199868' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199868[]' id='textarea_q_199868' 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-199869'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>74. <\/span>HOTSPOT <br \/>\r<br>You write code to retrieve an experiment that is run from your Azure Machine Learning workspace. <br \/>\r<br>The run used the model interpretation support in Azure Machine Learning to generate and upload a model explanation. <br \/>\r<br>Business managers in your organization want to see the importance of the features in the model. <br \/>\r<br>You need to print out the model features and their relative importance in an output that looks similar to the following. <br \/>\r<br><br><img decoding=\"async\" width=362 height=129 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image088.jpg\"><br><br \/>\r<br>How should you complete the code? 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=362 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image089.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_74' value='199869' \/><input type='hidden' id='answerType199869' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199869[]' id='textarea_q_199869' 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-75' style=';'><div id='questionWrap-75'  class='   watupro-question-id-199870'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>75. <\/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_75' value='199870' \/><input type='hidden' id='answerType199870' 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-199870[]' id='answer-id-800912' class='answer   answerof-199870 ' value='800912'   \/><label for='answer-id-800912' id='answer-label-800912' 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-199870[]' id='answer-id-800913' class='answer   answerof-199870 ' value='800913'   \/><label for='answer-id-800913' id='answer-label-800913' class=' answer'><span>Solid State Drives (SSD)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199870[]' id='answer-id-800914' class='answer   answerof-199870 ' value='800914'   \/><label for='answer-id-800914' id='answer-label-800914' class=' answer'><span>Graphic Processing Unit (GPU)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199870[]' id='answer-id-800915' class='answer   answerof-199870 ' value='800915'   \/><label for='answer-id-800915' id='answer-label-800915' 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-199870[]' id='answer-id-800916' class='answer   answerof-199870 ' value='800916'   \/><label for='answer-id-800916' id='answer-label-800916' 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-76' style=';'><div id='questionWrap-76'  class='   watupro-question-id-199871'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>76. <\/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 create a model to forecast weather conditions based on historical data. <br \/>\r<br>You need to create a pipeline that runs a processing script to load data from a datastore and pass the processed data to a machine learning model training script. <br \/>\r<br>Solution: Run the following code: <br \/>\r<br><br><img decoding=\"async\" width=620 height=256 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image091.jpg\"><br><br \/>\r<br>Does the solution meet the goal?<\/div><input type='hidden' name='question_id[]' id='qID_76' value='199871' \/><input type='hidden' id='answerType199871' 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-199871[]' id='answer-id-800917' class='answer   answerof-199871 ' value='800917'   \/><label for='answer-id-800917' id='answer-label-800917' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199871[]' id='answer-id-800918' class='answer   answerof-199871 ' value='800918'   \/><label for='answer-id-800918' id='answer-label-800918' class=' answer'><span>No<\/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-199872'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>77. <\/span>You plan to use the Hyperdrive feature of Azure Machine Learning to determine the optimal hyperparameter values when training a model. <br \/>\r<br>You must use Hyperdrive to try combinations of the following hyperparameter values. You must not apply an early termination policy. <br \/>\r<br>learning_rate: any value between 0.001 and 0.1 <br \/>\r<br>&#8226; batch_size: 16, 32, or 64 <br \/>\r<br>You need to configure the sampling method for the Hyperdrive experiment <br \/>\r<br>Which two sampling methods can you use? Each correct answer is a complete solution. NOTE: Each correct selection is worth one point.<\/div><input type='hidden' name='question_id[]' id='qID_77' value='199872' \/><input type='hidden' id='answerType199872' 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-199872[]' id='answer-id-800919' class='answer   answerof-199872 ' value='800919'   \/><label for='answer-id-800919' id='answer-label-800919' class=' answer'><span>Grid sampling<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199872[]' id='answer-id-800920' class='answer   answerof-199872 ' value='800920'   \/><label for='answer-id-800920' id='answer-label-800920' class=' answer'><span>No sampling<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199872[]' id='answer-id-800921' class='answer   answerof-199872 ' value='800921'   \/><label for='answer-id-800921' id='answer-label-800921' class=' answer'><span>Bayesian sampling<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199872[]' id='answer-id-800922' class='answer   answerof-199872 ' value='800922'   \/><label for='answer-id-800922' id='answer-label-800922' class=' answer'><span>Random sampling<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-78' style=';'><div id='questionWrap-78'  class='   watupro-question-id-199873'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>78. <\/span>HOTSPOT <br \/>\r<br>You are using a decision tree algorithm. You have trained a model that generalizes well at a tree depth equal to 10. <br \/>\r<br>You need to select the bias and variance properties of the model with varying tree depth values. <br \/>\r<br>Which properties should you select for each tree depth? To answer, select the appropriate options in the answer area. <br \/>\r<br><br><img decoding=\"async\" width=583 height=282 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image092.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_78' value='199873' \/><input type='hidden' id='answerType199873' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-199873[]' id='textarea_q_199873' 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-79' style=';'><div id='questionWrap-79'  class='   watupro-question-id-199874'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>79. <\/span>You plan to use the Hyperdrive feature of Azure Machine Learning to determine the optimal hyperparameter values when training a model. <br \/>\r<br>You must use Hyperdrive to try combinations of the following hyperparameter values: <br \/>\r<br>&#8226; learning_rate: any value between 0.001 and 0.1 <br \/>\r<br>&#8226; batch_size: 16, 32, or 64 <br \/>\r<br>You need to configure the search space for the Hyperdrive experiment. <br \/>\r<br>Which two parameter expressions should you use? 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_79' value='199874' \/><input type='hidden' id='answerType199874' 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-199874[]' id='answer-id-800924' class='answer   answerof-199874 ' value='800924'   \/><label for='answer-id-800924' id='answer-label-800924' class=' answer'><span>a choice expression for learning_rate<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199874[]' id='answer-id-800925' class='answer   answerof-199874 ' value='800925'   \/><label for='answer-id-800925' id='answer-label-800925' class=' answer'><span>a uniform expression for learning_rate<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199874[]' id='answer-id-800926' class='answer   answerof-199874 ' value='800926'   \/><label for='answer-id-800926' id='answer-label-800926' class=' answer'><span>a normal expression for batch_size<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199874[]' id='answer-id-800927' class='answer   answerof-199874 ' value='800927'   \/><label for='answer-id-800927' id='answer-label-800927' class=' answer'><span>a choice expression for batch_size<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199874[]' id='answer-id-800928' class='answer   answerof-199874 ' value='800928'   \/><label for='answer-id-800928' id='answer-label-800928' class=' answer'><span>a uniform expression for batch_size<\/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-199875'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>80. <\/span>You create a multi-class image classification deep learning model that uses a set of labeled images. You create a script file named train.py that uses the PyTorch 1.3 framework to train the model. <br \/>\r<br>You must run the script by using an estimator. The code must not require any additional Python libraries to be installed in the environment for the estimator. The time required for model training must be minimized. <br \/>\r<br>You need to define the estimator that will be used to run the script. <br \/>\r<br>Which estimator type should you use?<\/div><input type='hidden' name='question_id[]' id='qID_80' value='199875' \/><input type='hidden' id='answerType199875' 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-199875[]' id='answer-id-800929' class='answer   answerof-199875 ' value='800929'   \/><label for='answer-id-800929' id='answer-label-800929' class=' answer'><span>TensorFlow<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199875[]' id='answer-id-800930' class='answer   answerof-199875 ' value='800930'   \/><label for='answer-id-800930' id='answer-label-800930' class=' answer'><span>PyTorch<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199875[]' id='answer-id-800931' class='answer   answerof-199875 ' value='800931'   \/><label for='answer-id-800931' id='answer-label-800931' class=' answer'><span>SKLearn<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199875[]' id='answer-id-800932' class='answer   answerof-199875 ' value='800932'   \/><label for='answer-id-800932' id='answer-label-800932' class=' answer'><span>Estimator<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div style='display:none' id='question-81'>\n\t<div class='question-content'>\n\t\t<img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/plugins\/watupro\/img\/loading.gif\" width=\"16\" height=\"16\" alt=\"Loading...\" title=\"Loading...\" \/>&nbsp;Loading...\t<\/div>\n<\/div>\n\n<br \/>\n\t\n\t\t\t<div class=\"watupro_buttons flex \" id=\"watuPROButtons5876\" >\n\t\t  <div id=\"prev-question\" style=\"display:none;\"><input type=\"button\" value=\"&lt; 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