{"id":53228,"date":"2023-03-22T00:58:05","date_gmt":"2023-03-22T00:58:05","guid":{"rendered":"https:\/\/www.dumpsbase.com\/freedumps\/?p=53228"},"modified":"2023-05-10T02:37:35","modified_gmt":"2023-05-10T02:37:35","slug":"master-the-dp-100-exam-with-our-updated-designing-and-implementing-a-data-science-solution-on-azure-exam-dumps","status":"publish","type":"post","link":"https:\/\/www.dumpsbase.com\/freedumps\/master-the-dp-100-exam-with-our-updated-designing-and-implementing-a-data-science-solution-on-azure-exam-dumps.html","title":{"rendered":"Master the DP-100 Exam with Our Updated Designing and Implementing a Data Science Solution on Azure Exam Dumps"},"content":{"rendered":"\n<p>To help you prepare for the DP-100 Designing and Implementing a Data Science Solution on Azure thoroughly, we have updated the Microsoft DP-100 exam dumps with 311 practice questions and answers. Our updated exam dumps cover all the key topics you need to know, including designing and implementing data storage solutions, deploying and managing data science models, and monitoring and optimizing Azure-based solutions. With the most updated DP-100 dumps, you can practice all these questions and answers regularly, allowing you to build your confidence and knowledge in the subject matter. Whether you are new to data science or a seasoned professional, this updated guide can help you prepare effectively and pass the Microsoft DP-100 exam with ease.<\/p>\n<h2><em><span style=\"background-color: #99ccff;\">Free Microsoft DP-100 Demo<\/span><\/em> Questions 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=\"submittingExam7186\" 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-7186\"><\/div>\n\n<form action=\"\" method=\"post\" class=\"quiz-form\" id=\"quiz-7186\"  enctype=\"multipart\/form-data\" >\n<div class='watu-question ' id='question-1' style=';'><div id='questionWrap-1'  class='   watupro-question-id-262188'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>1. <\/span>Topic 1, Case Study 1 <br \/>\r<br><br \/>\r<br>Overview <br \/>\r<br>You are a data scientist in a company that provides data science for professional sporting events. <br \/>\r<br>Models will be global and local market data to meet the following business goals: <br \/>\r<br>&#8226; Understand sentiment of mobile device users at sporting events based on audio from crowd reactions. <br \/>\r<br>&#8226; Access a user's tendency to respond to an advertisement. <br \/>\r<br>&#8226; Customize styles of ads served on mobile devices. <br \/>\r<br>&#8226; Use video to detect penalty events. <br \/>\r<br><br \/>\r<br>Current environment <br \/>\r<br>Requirements <br \/>\r<br>&#8226; Media used for penalty event detection will be provided by consumer devices. Media may include images and videos captured during the sporting event and snared using social media. The images and videos will have varying sizes and formats. <br \/>\r<br>&#8226; The data available for model building comprises of seven years of sporting event media. The sporting event media includes: recorded videos, transcripts of radio commentary, and logs from related social media feeds feeds captured during the sporting events. <br \/>\r<br>&#8226; Crowd sentiment will include audio recordings submitted by event attendees in both mono and stereo Formats. <br \/>\r<br><br \/>\r<br>Advertisements <br \/>\r<br>&#8226; Ad response models must be trained at the beginning of each event and applied during the sporting event. <br \/>\r<br>&#8226; Market segmentation nxxlels must optimize for similar ad resporr.r history. <br \/>\r<br>&#8226; Sampling must guarantee mutual and collective exclusivity local and global segmentation models that share the same features. <br \/>\r<br>&#8226; Local market segmentation models will be applied before determining a user\u2019s propensity to respond to an advertisement. <br \/>\r<br>&#8226; Data scientists must be able to detect model degradation and decay. <br \/>\r<br>&#8226; Ad response models must support non linear boundaries features. <br \/>\r<br>&#8226; The ad propensity model uses a cut threshold is 0.45 and retrains occur if weighted Kappa deviates from 0.1 +\/-5%. <br \/>\r<br>&#8226; The ad propensity model uses cost factors shown in the following diagram: <br \/>\r<br><br><img decoding=\"async\" width=405 height=199 id=\"\u56fe\u7247 1\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image001-6.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 id=\"\u56fe\u7247 2\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/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=649 height=209 id=\"\u56fe\u7247 3\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image003-4.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>DRAG DROP <br \/>\r<br>You need to define a process for penalty event detection. <br \/>\r<br>Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order. <br \/>\r<br><br><img decoding=\"async\" width=649 height=545 id=\"\u56fe\u7247 10\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image004-4.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_1' value='262188' \/><input type='hidden' id='answerType262188' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262188[]' id='textarea_q_262188' 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-262189'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>2. <\/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_2' value='262189' \/><input type='hidden' id='answerType262189' 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-262189[]' id='answer-id-1033685' class='answer   answerof-262189 ' value='1033685'   \/><label for='answer-id-1033685' id='answer-label-1033685' class=' answer'><span>Increase Graphic Processing Units (GPUs).<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262189[]' id='answer-id-1033686' class='answer   answerof-262189 ' value='1033686'   \/><label for='answer-id-1033686' id='answer-label-1033686' class=' answer'><span>Increase the learning rate.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262189[]' id='answer-id-1033687' class='answer   answerof-262189 ' value='1033687'   \/><label for='answer-id-1033687' id='answer-label-1033687' class=' answer'><span>Increase the training iterations,<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262189[]' id='answer-id-1033688' class='answer   answerof-262189 ' value='1033688'   \/><label for='answer-id-1033688' id='answer-label-1033688' 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-3' style=';'><div id='questionWrap-3'  class='   watupro-question-id-262190'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>3. <\/span>You need to select an environment that will meet the business and data requirements. <br \/>\r<br>Which environment should you use?<\/div><input type='hidden' name='question_id[]' id='qID_3' value='262190' \/><input type='hidden' id='answerType262190' 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-262190[]' id='answer-id-1033689' class='answer   answerof-262190 ' value='1033689'   \/><label for='answer-id-1033689' id='answer-label-1033689' class=' answer'><span>Azure HDInsight with Spark MLlib<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262190[]' id='answer-id-1033690' class='answer   answerof-262190 ' value='1033690'   \/><label for='answer-id-1033690' id='answer-label-1033690' class=' answer'><span>Azure Cognitive Services<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262190[]' id='answer-id-1033691' class='answer   answerof-262190 ' value='1033691'   \/><label for='answer-id-1033691' id='answer-label-1033691' class=' answer'><span>Azure Machine Learning Studio<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262190[]' id='answer-id-1033692' class='answer   answerof-262190 ' value='1033692'   \/><label for='answer-id-1033692' id='answer-label-1033692' class=' answer'><span>Microsoft Machine Learning Server<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-4' style=';'><div id='questionWrap-4'  class='   watupro-question-id-262191'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>4. <\/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_4' value='262191' \/><input type='hidden' id='answerType262191' 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-262191[]' id='answer-id-1033693' class='answer   answerof-262191 ' value='1033693'   \/><label for='answer-id-1033693' id='answer-label-1033693' class=' answer'><span>Streaming<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262191[]' id='answer-id-1033694' class='answer   answerof-262191 ' value='1033694'   \/><label for='answer-id-1033694' id='answer-label-1033694' class=' answer'><span>Weight<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262191[]' id='answer-id-1033695' class='answer   answerof-262191 ' value='1033695'   \/><label for='answer-id-1033695' id='answer-label-1033695' class=' answer'><span>Batch<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262191[]' id='answer-id-1033696' class='answer   answerof-262191 ' value='1033696'   \/><label for='answer-id-1033696' id='answer-label-1033696' class=' answer'><span>Cosine<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-5' style=';'><div id='questionWrap-5'  class='   watupro-question-id-262192'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>5. <\/span>DRAG DROP <br \/>\r<br>You need to modify the inputs for the global penalty event model to address the bias and variance issue. <br \/>\r<br>Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order. <br \/>\r<br><br><img decoding=\"async\" width=649 height=256 id=\"\u56fe\u7247 14\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image006-4.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_5' value='262192' \/><input type='hidden' id='answerType262192' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262192[]' id='textarea_q_262192' 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-262193'>\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 modeling strategy for ad response. <br \/>\r<br>Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order. <br \/>\r<br><br><img decoding=\"async\" width=650 height=336 id=\"\u56fe\u7247 19\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image008-4.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_6' value='262193' \/><input type='hidden' id='answerType262193' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262193[]' id='textarea_q_262193' 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-262194'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>7. <\/span>HOTSPOT <br \/>\r<br>You need to use the Python language to build a sampling strategy for the global penalty detection models. <br \/>\r<br>How should you complete the code segment? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=650 height=614 id=\"\u56fe\u7247 16\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image010-4.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_7' value='262194' \/><input type='hidden' id='answerType262194' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262194[]' id='textarea_q_262194' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-8' style=';'><div id='questionWrap-8'  class='   watupro-question-id-262195'>\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 id=\"\u56fe\u7247 12\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image012-5.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_8' value='262195' \/><input type='hidden' id='answerType262195' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262195[]' id='textarea_q_262195' 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-262196'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>9. <\/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_9' value='262196' \/><input type='hidden' id='answerType262196' 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-262196[]' id='answer-id-1033701' class='answer   answerof-262196 ' value='1033701'   \/><label for='answer-id-1033701' id='answer-label-1033701' 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-262196[]' id='answer-id-1033702' class='answer   answerof-262196 ' value='1033702'   \/><label for='answer-id-1033702' id='answer-label-1033702' 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-262196[]' id='answer-id-1033703' class='answer   answerof-262196 ' value='1033703'   \/><label for='answer-id-1033703' id='answer-label-1033703' 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-262196[]' id='answer-id-1033704' class='answer   answerof-262196 ' value='1033704'   \/><label for='answer-id-1033704' id='answer-label-1033704' 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-10' style=';'><div id='questionWrap-10'  class='   watupro-question-id-262197'>\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 process for penalty event detection. <br \/>\r<br>Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order. <br \/>\r<br><br><img decoding=\"async\" width=649 height=282 id=\"\u56fe\u7247 6\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image014-4.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_10' value='262197' \/><input type='hidden' id='answerType262197' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262197[]' id='textarea_q_262197' 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-262198'>\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=649 height=261 id=\"\u56fe\u7247 8\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image016-4.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_11' value='262198' \/><input type='hidden' id='answerType262198' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262198[]' id='textarea_q_262198' 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-262199'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>12. <\/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_12' value='262199' \/><input type='hidden' id='answerType262199' 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-262199[]' id='answer-id-1033707' class='answer   answerof-262199 ' value='1033707'   \/><label for='answer-id-1033707' id='answer-label-1033707' class=' answer'><span>Apply an analysis of variance (ANOVA).<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262199[]' id='answer-id-1033708' class='answer   answerof-262199 ' value='1033708'   \/><label for='answer-id-1033708' id='answer-label-1033708' class=' answer'><span>Apply a Pearson correlation coefficient.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262199[]' id='answer-id-1033709' class='answer   answerof-262199 ' value='1033709'   \/><label for='answer-id-1033709' id='answer-label-1033709' class=' answer'><span>Apply a Spearman correlation coefficient.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262199[]' id='answer-id-1033710' class='answer   answerof-262199 ' value='1033710'   \/><label for='answer-id-1033710' id='answer-label-1033710' 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-13' style=';'><div id='questionWrap-13'  class='   watupro-question-id-262200'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>13. <\/span>DRAG DROP <br \/>\r<br>You need to define an evaluation strategy for the crowd sentiment models. <br \/>\r<br>Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order. <br \/>\r<br><br><img decoding=\"async\" width=650 height=397 id=\"\u56fe\u7247 4\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image018-4.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_13' value='262200' \/><input type='hidden' id='answerType262200' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262200[]' id='textarea_q_262200' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-14' style=';'><div id='questionWrap-14'  class='   watupro-question-id-262201'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>14. <\/span>You need to implement a new cost factor scenario for the ad response models as illustrated in the <br \/>\r<br>performance curve exhibit. <br \/>\r<br>Which technique should you use?<\/div><input type='hidden' name='question_id[]' id='qID_14' value='262201' \/><input type='hidden' id='answerType262201' 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-262201[]' id='answer-id-1033712' class='answer   answerof-262201 ' value='1033712'   \/><label for='answer-id-1033712' id='answer-label-1033712' 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-262201[]' id='answer-id-1033713' class='answer   answerof-262201 ' value='1033713'   \/><label for='answer-id-1033713' id='answer-label-1033713' 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-262201[]' id='answer-id-1033714' class='answer   answerof-262201 ' value='1033714'   \/><label for='answer-id-1033714' id='answer-label-1033714' 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-262201[]' id='answer-id-1033715' class='answer   answerof-262201 ' value='1033715'   \/><label for='answer-id-1033715' id='answer-label-1033715' class=' answer'><span>Set the threshold to 0.75 and retrain if weighted Kappa deviates +\/- 5% from 0.15.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-15' style=';'><div id='questionWrap-15'  class='   watupro-question-id-262202'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>15. <\/span>Topic 2, Case Study 2 <br \/>\r<br><br \/>\r<br>Case study <br \/>\r<br>Overview <br \/>\r<br>You are a data scientist for Fabrikam Residences, a company specializing in quality private and commercial property in the United States. Fabrikam Residences is considering expanding into Europe and has asked you to investigate prices for private residences in major European cities. You use Azure Machine Learning Studio to measure the median value of properties. You produce a regression model to predict property prices by using the Linear Regression and Bayesian Linear Regression modules. <br \/>\r<br><br \/>\r<br>Datasets <br \/>\r<br>There are two datasets in CSV format that contain property details for two cities, London and Paris, with the following columns: <br \/>\r<br><br><img decoding=\"async\" width=615 height=310 id=\"\u56fe\u7247 21\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image021-3.jpg\"><br><br \/>\r<br><br \/>\r<br>The two datasets have been added to Azure Machine Learning Studio as separate datasets and included as the starting point of the experiment. <br \/>\r<br><br \/>\r<br>Dataset issues <br \/>\r<br>The AccessibilityToHighway column in both datasets contains missing values. The missing data must be replaced with new data so that it is modeled conditionally using the other variables in the data before filling in the missing values. <br \/>\r<br>Columns in each dataset contain missing and null values. The dataset also contains many outliers. The Age column has a high proportion of outliers. You need to remove the rows that have outliers in the Age column. The MedianValue and AvgRoomsinHouse columns both hold data in numeric format. You need to select a feature selection algorithm to analyze the relationship between the two columns in more detail. <br \/>\r<br><br \/>\r<br>Model fit <br \/>\r<br>The model shows signs of overfitting. You need to produce a more refined regression model that reduces the overfitting. <br \/>\r<br><br \/>\r<br>Experiment requirements <br \/>\r<br>You must set up the experiment to cross-validate the Linear Regression and Bayesian Linear Regression modules to evaluate performance. <br \/>\r<br><br \/>\r<br>In each case, the predictor of the dataset is the column named MedianValue. An initial investigation showed that the datasets are identical in structure apart from the MedianValue column. The smaller Paris dataset contains the MedianValue in text format, whereas the larger London dataset contains the MedianValue in numerical format. You must ensure that the datatype of the MedianValue column of the Paris dataset matches the structure of the London dataset. <br \/>\r<br><br \/>\r<br>You must prioritize the columns of data for predicting the outcome. You must use non-parameters statistics to measure the relationships. <br \/>\r<br><br \/>\r<br>You must use a feature selection algorithm to analyze the relationship between the MedianValue and AvgRoomsinHouse columns. <br \/>\r<br><br \/>\r<br>Model training <br \/>\r<br>Given a trained model and a test dataset, you need to compute the permutation feature importance scores of feature variables. You need to set up the Permutation Feature Importance module to select the correct metric to investigate the model\u2019s accuracy and replicate the findings. <br \/>\r<br>You want to configure hyperparameters in the model learning process to speed the learning phase by using hyperparameters. In addition, this configuration should cancel the lowest performing runs at each evaluation interval, thereby directing effort and resources towards models that are more likely to be successful. <br \/>\r<br><br \/>\r<br>You are concerned that the model might not efficiently use compute resources in hyperparameter tuning. You also are concerned that the model might prevent an increase in the overall tuning time. Therefore, you need to implement an early stopping criterion on models that provides savings without terminating promising jobs. <br \/>\r<br><br \/>\r<br>Testing <br \/>\r<br>You must produce multiple partitions of a dataset based on sampling using the Partition and Sample module in Azure Machine Learning Studio. You must create three equal partitions for cross-validation. You must also configure the cross-validation process so that the rows in the test and training datasets are divided evenly by properties that are near each city\u2019s main river. The data that identifies that a property is near a river is held in the column named NextToRiver. You want to complete this task before the data goes through the sampling process. <br \/>\r<br><br \/>\r<br>When you train a Linear Regression module using a property dataset that shows data for property prices for a large city, you need to determine the best features to use in a model. You can choose standard metrics provided to measure performance before and after the feature importance process completes. You must ensure that the distribution of the features across multiple training models is consistent. <br \/>\r<br><br \/>\r<br>Data visualization <br \/>\r<br>You need to provide the test results to the Fabrikam Residences team. You create data visualizations to aid in presenting the results. <br \/>\r<br>You must produce a Receiver Operating Characteristic (ROC) curve to conduct a <br \/>\r<br>diagnostic test evaluation of the model. You need to select appropriate methods for producing the ROC curve in Azure Machine Learning Studio to compare the Two-Class Decision Forest and the Two-Class Decision Jungle modules with one another. <br \/>\r<br><br \/>\r<br>DRAG DROP <br \/>\r<br>You need to 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 id=\"\u56fe\u7247 40\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image022-3.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_15' value='262202' \/><input type='hidden' id='answerType262202' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262202[]' id='textarea_q_262202' 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-262203'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>16. <\/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 id=\"\u56fe\u7247 38\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image024-3.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_16' value='262203' \/><input type='hidden' id='answerType262203' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262203[]' id='textarea_q_262203' 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-262204'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>17. <\/span>HOTSPOT <br \/>\r<br>You need to identify the methods for dividing the data according to the testing requirements. <br \/>\r<br>Which properties should you select? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=443 height=888 id=\"\u56fe\u7247 42\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image026-3.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_17' value='262204' \/><input type='hidden' id='answerType262204' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262204[]' id='textarea_q_262204' 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-262205'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>18. <\/span>HOTSPOT <br \/>\r<br>You need to set up the Permutation Feature Importance module according to the model training requirements. <br \/>\r<br>Which properties should you select? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=620 height=584 id=\"\u56fe\u7247 30\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image028-3.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_18' value='262205' \/><input type='hidden' id='answerType262205' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262205[]' id='textarea_q_262205' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-19' style=';'><div id='questionWrap-19'  class='   watupro-question-id-262206'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>19. <\/span>HOTSPOT <br \/>\r<br>You need to replace the missing data in the AccessibilityToHighway columns. <br \/>\r<br>How should you configure the Clean Missing Data module? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=548 height=878 id=\"\u56fe\u7247 28\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image030-3.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_19' value='262206' \/><input type='hidden' id='answerType262206' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262206[]' id='textarea_q_262206' 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-262207'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>20. <\/span>HOTSPOT <br \/>\r<br>You need to configure the Permutation Feature Importance module for the model training requirements. <br \/>\r<br>What should you do? To answer, select the appropriate options in the dialog box in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=492 height=500 id=\"\u56fe\u7247 22\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image032-3.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_20' value='262207' \/><input type='hidden' id='answerType262207' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262207[]' id='textarea_q_262207' 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-262208'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>21. <\/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_21' value='262208' \/><input type='hidden' id='answerType262208' 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-262208[]' id='answer-id-1033722' class='answer   answerof-262208 ' value='1033722'   \/><label for='answer-id-1033722' id='answer-label-1033722' class=' answer'><span>Spearman correlation<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262208[]' id='answer-id-1033723' class='answer   answerof-262208 ' value='1033723'   \/><label for='answer-id-1033723' id='answer-label-1033723' class=' answer'><span>Mutual information<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262208[]' id='answer-id-1033724' class='answer   answerof-262208 ' value='1033724'   \/><label for='answer-id-1033724' id='answer-label-1033724' class=' answer'><span>Mann-Whitney test<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262208[]' id='answer-id-1033725' class='answer   answerof-262208 ' value='1033725'   \/><label for='answer-id-1033725' id='answer-label-1033725' class=' answer'><span>Pearson\u2019s correlation<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-22' style=';'><div id='questionWrap-22'  class='   watupro-question-id-262209'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>22. <\/span>HOTSPOT <br \/>\r<br>You need to configure the Edit Metadata module so that the structure of the datasets match. <br \/>\r<br>Which configuration options should you select? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=606 height=714 id=\"\u56fe\u7247 34\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image034-3.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_22' value='262209' \/><input type='hidden' id='answerType262209' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262209[]' id='textarea_q_262209' 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-262210'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>23. <\/span>HOTSPOT <br \/>\r<br>You need to identify the methods for dividing the data according, to the testing requirements. <br \/>\r<br>Which properties should you select? To answer, select the appropriate option-, m the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=614 height=406 id=\"\u56fe\u7247 24\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image036-3.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_23' value='262210' \/><input type='hidden' id='answerType262210' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262210[]' id='textarea_q_262210' 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-262211'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>24. <\/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=301 id=\"\u56fe\u7247 26\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image038-3.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_24' value='262211' \/><input type='hidden' id='answerType262211' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262211[]' id='textarea_q_262211' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-25' style=';'><div id='questionWrap-25'  class='   watupro-question-id-262212'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>25. <\/span>You need to select a feature extraction method. <br \/>\r<br>Which method should you use?<\/div><input type='hidden' name='question_id[]' id='qID_25' value='262212' \/><input type='hidden' id='answerType262212' 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-262212[]' id='answer-id-1033729' class='answer   answerof-262212 ' value='1033729'   \/><label for='answer-id-1033729' id='answer-label-1033729' class=' answer'><span>Mutual information<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262212[]' id='answer-id-1033730' class='answer   answerof-262212 ' value='1033730'   \/><label for='answer-id-1033730' id='answer-label-1033730' class=' answer'><span>Mood\u2019s median test<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262212[]' id='answer-id-1033731' class='answer   answerof-262212 ' value='1033731'   \/><label for='answer-id-1033731' id='answer-label-1033731' class=' answer'><span>Kendall correlation<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262212[]' id='answer-id-1033732' class='answer   answerof-262212 ' value='1033732'   \/><label for='answer-id-1033732' id='answer-label-1033732' class=' answer'><span>Permutation Feature Importance<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-26' style=';'><div id='questionWrap-26'  class='   watupro-question-id-262213'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>26. <\/span>DRAG DROP <br \/>\r<br>You need to correct the model fit issue. <br \/>\r<br>Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order. <br \/>\r<br><br><img decoding=\"async\" width=601 height=526 id=\"\u56fe\u7247 32\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image040-3.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_26' value='262213' \/><input type='hidden' id='answerType262213' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262213[]' id='textarea_q_262213' 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-262214'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>27. <\/span>DRAG DROP <br \/>\r<br>You need to produce a visualization for the diagnostic test evaluation according to the data visualization requirements. <br \/>\r<br>Which three modules should you recommend be used in sequence? To answer, move the appropriate modules from the list of modules to the answer area and arrange them in the correct order. <br \/>\r<br><br><img decoding=\"async\" width=649 height=477 id=\"\u56fe\u7247 36\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image042-3.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_27' value='262214' \/><input type='hidden' id='answerType262214' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262214[]' id='textarea_q_262214' 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-262215'>\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 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_28' value='262215' \/><input type='hidden' id='answerType262215' 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-262215[]' id='answer-id-1033735' class='answer   answerof-262215 ' value='1033735'   \/><label for='answer-id-1033735' id='answer-label-1033735' class=' answer'><span>Grid sampling<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-262215[]' id='answer-id-1033736' class='answer   answerof-262215 ' value='1033736'   \/><label for='answer-id-1033736' id='answer-label-1033736' class=' answer'><span>No sampling<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-262215[]' id='answer-id-1033737' class='answer   answerof-262215 ' value='1033737'   \/><label for='answer-id-1033737' id='answer-label-1033737' class=' answer'><span>Bayesian sampling<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-262215[]' id='answer-id-1033738' class='answer   answerof-262215 ' value='1033738'   \/><label for='answer-id-1033738' id='answer-label-1033738' class=' answer'><span>Random sampling<\/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-262216'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>29. <\/span>DRAG DROP <br \/>\r<br>You create an Azure Machine Learning workspace and a new Azure DevOps organization. <br \/>\r<br>You register a model in the workspace and deploy the model to the target environment. <br \/>\r<br>All new versions of the model registered in the workspace must automatically be deployed to the target environment. <br \/>\r<br>You need to configure Azure Pipelines to deploy the model. <br \/>\r<br>Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order. <br \/>\r<br><br><img decoding=\"async\" width=650 height=235 id=\"\u56fe\u7247 306\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image044-3.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_29' value='262216' \/><input type='hidden' id='answerType262216' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262216[]' id='textarea_q_262216' 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-262217'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>30. <\/span>DRAG DROP <br \/>\r<br>You have several machine learning models registered in an Azure Machine Learning workspace. <br \/>\r<br>You must use the Fairlearn dashboard to assess fairness in a selected model. <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=177 id=\"\u56fe\u7247 107\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image048-3.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_30' value='262217' \/><input type='hidden' id='answerType262217' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262217[]' id='textarea_q_262217' 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-31' style=';'><div id='questionWrap-31'  class='   watupro-question-id-262218'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>31. <\/span>HOTSPOT <br \/>\r<br>You plan to implement an Azure Machine Learning solution. <br \/>\r<br>You have the following requirements: <br \/>\r<br>&#8226; Run a Jupyter notebook to interactively tram a machine learning model. <br \/>\r<br>&#8226; Deploy assets and workflows for machine learning proof of concept by using scripting rather than custom programming. <br \/>\r<br>You need to select a development technique for each requirement <br \/>\r<br>Which development technique should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=650 height=212 id=\"\u56fe\u7247 2543\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image050-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_31' value='262218' \/><input type='hidden' id='answerType262218' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262218[]' id='textarea_q_262218' 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-32' style=';'><div id='questionWrap-32'  class='   watupro-question-id-262219'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>32. <\/span>You have the following code. <br \/>\r<br>The code prepares an experiment to run a script: <br \/>\r<br><br><img decoding=\"async\" width=615 height=133 id=\"\u56fe\u7247 157\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image052-3.jpg\"><br><br \/>\r<br>The experiment must be run on local computer using the default environment. <br \/>\r<br>You need to add code to start the experiment and run the script. <br \/>\r<br>Which code segment should you use?<\/div><input type='hidden' name='question_id[]' id='qID_32' value='262219' \/><input type='hidden' id='answerType262219' 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-262219[]' id='answer-id-1033742' class='answer   answerof-262219 ' value='1033742'   \/><label for='answer-id-1033742' id='answer-label-1033742' class=' answer'><span>run = script_experiment.start_logging()<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262219[]' id='answer-id-1033743' class='answer   answerof-262219 ' value='1033743'   \/><label for='answer-id-1033743' id='answer-label-1033743' class=' answer'><span>run = Run(experiment=script_experiment)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262219[]' id='answer-id-1033744' class='answer   answerof-262219 ' value='1033744'   \/><label for='answer-id-1033744' id='answer-label-1033744' class=' answer'><span>ws.get_run(run_id=experiment.id)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262219[]' id='answer-id-1033745' class='answer   answerof-262219 ' value='1033745'   \/><label for='answer-id-1033745' id='answer-label-1033745' class=' answer'><span>run = script_experiment.submit(config=script_config)<\/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-262220'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>33. <\/span>You use the Azure Machine Learning designer to create and run a training pipeline. You then create a real-time inference pipeline. <br \/>\r<br>You must deploy the real-time inference pipeline as a web service. <br \/>\r<br>What must you do before you deploy the real-time inference pipeline?<\/div><input type='hidden' name='question_id[]' id='qID_33' value='262220' \/><input type='hidden' id='answerType262220' 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-262220[]' id='answer-id-1033746' class='answer   answerof-262220 ' value='1033746'   \/><label for='answer-id-1033746' id='answer-label-1033746' class=' answer'><span>Run the real-time inference pipeline.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262220[]' id='answer-id-1033747' class='answer   answerof-262220 ' value='1033747'   \/><label for='answer-id-1033747' id='answer-label-1033747' class=' answer'><span>Create a batch inference pipeline.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262220[]' id='answer-id-1033748' class='answer   answerof-262220 ' value='1033748'   \/><label for='answer-id-1033748' id='answer-label-1033748' class=' answer'><span>Clone the training pipeline.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262220[]' id='answer-id-1033749' class='answer   answerof-262220 ' value='1033749'   \/><label for='answer-id-1033749' id='answer-label-1033749' class=' answer'><span>Create an Azure Machine Learning compute cluster.<\/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-262221'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>34. <\/span>Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. <br \/>\r<br>After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. <br \/>\r<br>You are 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_34' value='262221' \/><input type='hidden' id='answerType262221' 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-262221[]' id='answer-id-1033750' class='answer   answerof-262221 ' value='1033750'   \/><label for='answer-id-1033750' id='answer-label-1033750' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262221[]' id='answer-id-1033751' class='answer   answerof-262221 ' value='1033751'   \/><label for='answer-id-1033751' id='answer-label-1033751' class=' answer'><span>No<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-35' style=';'><div id='questionWrap-35'  class='   watupro-question-id-262222'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>35. <\/span>Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. <br \/>\r<br>After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. <br \/>\r<br>You are 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 id=\"\u56fe\u7247 74\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image053-3.jpg\"><br><br \/>\r<br>You plan to use this configuration to run a script that trains a random forest model and then tests it with validation data. The label values for the validation data are stored in a variable named y_test variable, and the predicted probabilities from the model are stored in a variable named y_predicted. <br \/>\r<br>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 id=\"\u56fe\u7247 75\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image054-3.jpg\"><br><br \/>\r<br>Does the solution meet the goal?<\/div><input type='hidden' name='question_id[]' id='qID_35' value='262222' \/><input type='hidden' id='answerType262222' 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-262222[]' id='answer-id-1033752' class='answer   answerof-262222 ' value='1033752'   \/><label for='answer-id-1033752' id='answer-label-1033752' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262222[]' id='answer-id-1033753' class='answer   answerof-262222 ' value='1033753'   \/><label for='answer-id-1033753' id='answer-label-1033753' class=' answer'><span>No<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-36' style=';'><div id='questionWrap-36'  class='   watupro-question-id-262223'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>36. <\/span>You define a datastore named ml-data for an Azure Storage blob container. In the container, you have a folder named train that contains a file named data.csv. You plan to use the file to train a model by using the Azure Machine Learning SDK. <br \/>\r<br>You plan to train the model by using the Azure Machine Learning SDK to run an experiment on local compute. <br \/>\r<br>You define a DataReference object by running the following code: <br \/>\r<br><br><img decoding=\"async\" width=650 height=199 id=\"\u56fe\u7247 238\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image055-3.jpg\"><br><br \/>\r<br>You need to load the training data. <br \/>\r<br>Which code segment should you use? <br \/>\r<br>A) <br \/>\r<br><br><img decoding=\"async\" width=649 height=114 id=\"\u56fe\u7247 239\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image056-3.jpg\"><br><br \/>\r<br>B) <br \/>\r<br><br><img decoding=\"async\" width=649 height=135 id=\"\u56fe\u7247 240\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image057-3.jpg\"><br><br \/>\r<br>C) <br \/>\r<br><br><img decoding=\"async\" width=380 height=58 id=\"\u56fe\u7247 241\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image058-2.jpg\"><br><br \/>\r<br>D) <br \/>\r<br><br><img decoding=\"async\" width=649 height=134 id=\"\u56fe\u7247 242\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image059-2.jpg\"><br><br \/>\r<br>E) <br \/>\r<br><br><img decoding=\"async\" width=649 height=134 id=\"\u56fe\u7247 243\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image060-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_36' value='262223' \/><input type='hidden' id='answerType262223' 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-262223[]' id='answer-id-1033754' class='answer   answerof-262223 ' value='1033754'   \/><label for='answer-id-1033754' id='answer-label-1033754' class=' answer'><span>Option A<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262223[]' id='answer-id-1033755' class='answer   answerof-262223 ' value='1033755'   \/><label for='answer-id-1033755' id='answer-label-1033755' class=' answer'><span>Option B<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262223[]' id='answer-id-1033756' class='answer   answerof-262223 ' value='1033756'   \/><label for='answer-id-1033756' id='answer-label-1033756' class=' answer'><span>Option C<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262223[]' id='answer-id-1033757' class='answer   answerof-262223 ' value='1033757'   \/><label for='answer-id-1033757' id='answer-label-1033757' class=' answer'><span>Option D<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262223[]' id='answer-id-1033758' class='answer   answerof-262223 ' value='1033758'   \/><label for='answer-id-1033758' id='answer-label-1033758' class=' answer'><span>Option E<\/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-262224'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>37. <\/span>Your team is building a data engineering and data science development environment. <br \/>\r<br>The environment must support the following requirements: <br \/>\r<br>&#10001; support Python and Scala <br \/>\r<br>&#10001; compose data storage, movement, and processing services into automated data pipelines <br \/>\r<br>&#10001; the same tool should be used for the orchestration of both data engineering and data science <br \/>\r<br>&#10001; support workload isolation and interactive workloads <br \/>\r<br>&#10001; enable scaling across a cluster of machines <br \/>\r<br>You need to create the environment. <br \/>\r<br>What should you do?<\/div><input type='hidden' name='question_id[]' id='qID_37' value='262224' \/><input type='hidden' id='answerType262224' 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-262224[]' id='answer-id-1033759' class='answer   answerof-262224 ' value='1033759'   \/><label for='answer-id-1033759' id='answer-label-1033759' class=' answer'><span>Build the environment in Apache Hive for HDInsight and use Azure Data Factory for orchestration.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262224[]' id='answer-id-1033760' class='answer   answerof-262224 ' value='1033760'   \/><label for='answer-id-1033760' id='answer-label-1033760' class=' answer'><span>Build the environment in Azure Databricks and use Azure Data Factory for orchestration.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262224[]' id='answer-id-1033761' class='answer   answerof-262224 ' value='1033761'   \/><label for='answer-id-1033761' id='answer-label-1033761' class=' answer'><span>Build the environment in Apache Spark for HDInsight and use Azure Container Instances for orchestration.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262224[]' id='answer-id-1033762' class='answer   answerof-262224 ' value='1033762'   \/><label for='answer-id-1033762' id='answer-label-1033762' class=' answer'><span>Build the environment in Azure Databricks and use Azure Container Instances for orchestration.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-38' style=';'><div id='questionWrap-38'  class='   watupro-question-id-262225'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>38. <\/span>CORRECT TEXT <br \/>\r<br>You create an Azure Data Lake Storage Gen2 stowage account named storage1 containing a file system named fsi and a folder named folder1. <br \/>\r<br>The contents of folder1 must be accessible from jobs on compute targets in the Azure Machine Learning workspace. <br \/>\r<br>You need to construct a URl to reference folder1. <br \/>\r<br>How should you construct the URI? 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=556 height=52 id=\"\u56fe\u7247 490\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image061-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_38' value='262225' \/><input type='hidden' id='answerType262225' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262225[]' id='textarea_q_262225' 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-39' style=';'><div id='questionWrap-39'  class='   watupro-question-id-262226'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>39. <\/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 id=\"\u56fe\u7247 195\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image063-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_39' value='262226' \/><input type='hidden' id='answerType262226' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262226[]' id='textarea_q_262226' 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-262227'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>40. <\/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=649 height=48 id=\"\u56fe\u7247 2547\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image065-2.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_40' value='262227' \/><input type='hidden' id='answerType262227' 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-262227[]' id='answer-id-1033765' class='answer   answerof-262227 ' value='1033765'   \/><label for='answer-id-1033765' id='answer-label-1033765' class=' answer'><span>service.get_logs()<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262227[]' id='answer-id-1033766' class='answer   answerof-262227 ' value='1033766'   \/><label for='answer-id-1033766' id='answer-label-1033766' class=' answer'><span>service.state<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262227[]' id='answer-id-1033767' class='answer   answerof-262227 ' value='1033767'   \/><label for='answer-id-1033767' id='answer-label-1033767' class=' answer'><span>service.serialize()<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262227[]' id='answer-id-1033768' class='answer   answerof-262227 ' value='1033768'   \/><label for='answer-id-1033768' id='answer-label-1033768' class=' answer'><span>service.update_deployment_state()<\/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-262228'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>41. <\/span>HOTSPOT <br \/>\r<br>You create an Azure Databricks workspace and a linked Azure Machine Learning workspace. <br \/>\r<br>You have the following Python code segment in the Azure Machine Learning workspace: <br \/>\r<br>import mlflow <br \/>\r<br>import mlflow.azureml <br \/>\r<br>import azureml.mlflow <br \/>\r<br>import azureml.core <br \/>\r<br>from azureml.core import Workspace <br \/>\r<br>subscription_id = 'subscription_id' <br \/>\r<br>resourse_group = 'resource_group_name' <br \/>\r<br>workspace_name = 'workspace_name' <br \/>\r<br>ws = Workspace.get(name=workspace_name, <br \/>\r<br>subscription_id=subscription_id, <br \/>\r<br>resource_group=resource_group) <br \/>\r<br>experimentName = &quot;\/Users\/{user_name}\/{experiment_folder}\/{experiment_name}&quot; mlflow.set_experiment(experimentName) <br \/>\r<br>uri = ws.get_mlflow_tracking_uri() <br \/>\r<br>mlflow.set_tracking_uri(uri) <br \/>\r<br>Instructions: 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=649 height=171 id=\"\u56fe\u7247 198\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image066-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_41' value='262228' \/><input type='hidden' id='answerType262228' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262228[]' id='textarea_q_262228' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-42' style=';'><div id='questionWrap-42'  class='   watupro-question-id-262229'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>42. <\/span>HOTSPOT <br \/>\r<br>You plan to preprocess text from CSV files. You load the Azure Machine Learning Studio default stop words list. <br \/>\r<br>You need to configure the Preprocess Text module to meet the following requirements: <br \/>\r<br>&#10001; Ensure that multiple related words from a single canonical form. <br \/>\r<br>&#10001; Remove pipe characters from text. <br \/>\r<br>&#10001; Remove words to optimize information retrieval. <br \/>\r<br>Which three options should you select? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=396 height=690 id=\"\u56fe\u7247 284\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image068-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_42' value='262229' \/><input type='hidden' id='answerType262229' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262229[]' id='textarea_q_262229' 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-262230'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>43. <\/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=393 height=130 id=\"\u56fe\u7247 277\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image070-2.jpg\"><br><br \/>\r<br>You plan to use this configuration to run a script that trains a random forest model and then tests it with validation data. The label values for the validation data are stored in a variable named y_test variable, and the predicted probabilities from the model are stored in a variable named y_predicted. <br \/>\r<br>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=297 height=133 id=\"\u56fe\u7247 278\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image071-2.jpg\"><br><br \/>\r<br>Does the solution meet the goal?<\/div><input type='hidden' name='question_id[]' id='qID_43' value='262230' \/><input type='hidden' id='answerType262230' 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-262230[]' id='answer-id-1033771' class='answer   answerof-262230 ' value='1033771'   \/><label for='answer-id-1033771' id='answer-label-1033771' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262230[]' id='answer-id-1033772' class='answer   answerof-262230 ' value='1033772'   \/><label for='answer-id-1033772' id='answer-label-1033772' class=' answer'><span>No<\/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-262231'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>44. <\/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_44' value='262231' \/><input type='hidden' id='answerType262231' 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-262231[]' id='answer-id-1033773' class='answer   answerof-262231 ' value='1033773'   \/><label for='answer-id-1033773' id='answer-label-1033773' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262231[]' id='answer-id-1033774' class='answer   answerof-262231 ' value='1033774'   \/><label for='answer-id-1033774' id='answer-label-1033774' class=' answer'><span>No<\/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-262232'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>45. <\/span>HOTSPOT <br \/>\r<br>A biomedical research company plans to enroll people in an experimental medical treatment trial. <br \/>\r<br>You create and train a binary classification model to support selection and admission of patients to the trial. The model includes the following features: Age, Gender, and Ethnicity. <br \/>\r<br>The model returns different performance metrics for people from different ethnic groups. <br \/>\r<br>You need to use Fairlearn to mitigate and minimize disparities for each category in the Ethnicity feature. <br \/>\r<br>Which technique and constraint should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=563 height=296 id=\"\u56fe\u7247 303\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image072-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_45' value='262232' \/><input type='hidden' id='answerType262232' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262232[]' id='textarea_q_262232' 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-262233'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>46. <\/span>You use the Azure Machine Learning SDK in a notebook to run an experiment using a script file in an experiment folder. <br \/>\r<br>The experiment fails. <br \/>\r<br>You need to troubleshoot the failed experiment. <br \/>\r<br>What are two possible ways to achieve this goal? Each correct answer presents a complete solution.<\/div><input type='hidden' name='question_id[]' id='qID_46' value='262233' \/><input type='hidden' id='answerType262233' 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-262233[]' id='answer-id-1033776' class='answer   answerof-262233 ' value='1033776'   \/><label for='answer-id-1033776' id='answer-label-1033776' class=' answer'><span>Use the get_metrics() method of the run object to retrieve the experiment run logs.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-262233[]' id='answer-id-1033777' class='answer   answerof-262233 ' value='1033777'   \/><label for='answer-id-1033777' id='answer-label-1033777' class=' answer'><span>Use the get_details_with_logs() method of the run object to display the experiment run logs.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-262233[]' id='answer-id-1033778' class='answer   answerof-262233 ' value='1033778'   \/><label for='answer-id-1033778' id='answer-label-1033778' class=' answer'><span>View the log files for the experiment run in the experiment folder.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-262233[]' id='answer-id-1033779' class='answer   answerof-262233 ' value='1033779'   \/><label for='answer-id-1033779' id='answer-label-1033779' class=' answer'><span>View the logs for the experiment run in Azure Machine Learning studio.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-262233[]' id='answer-id-1033780' class='answer   answerof-262233 ' value='1033780'   \/><label for='answer-id-1033780' id='answer-label-1033780' class=' answer'><span>Use the get_output() method of the run object to retrieve the experiment run logs.<\/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-262234'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>47. <\/span>You are developing deep learning models to analyze semi-structured, unstructured, and structured data types. <br \/>\r<br>You have the following data available for model building: <br \/>\r<br>&#10001; Video recordings of sporting events <br \/>\r<br>&#10001; Transcripts of radio commentary about events <br \/>\r<br>&#10001; Logs from related social media feeds captured during sporting events <br \/>\r<br>You need to select an environment for creating the model. <br \/>\r<br>Which environment should you use?<\/div><input type='hidden' name='question_id[]' id='qID_47' value='262234' \/><input type='hidden' id='answerType262234' 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-262234[]' id='answer-id-1033781' class='answer   answerof-262234 ' value='1033781'   \/><label for='answer-id-1033781' id='answer-label-1033781' class=' answer'><span>Azure Cognitive Services<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262234[]' id='answer-id-1033782' class='answer   answerof-262234 ' value='1033782'   \/><label for='answer-id-1033782' id='answer-label-1033782' class=' answer'><span>Azure Data Lake Analytics<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262234[]' id='answer-id-1033783' class='answer   answerof-262234 ' value='1033783'   \/><label for='answer-id-1033783' id='answer-label-1033783' class=' answer'><span>Azure HDInsight with Spark MLib<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262234[]' id='answer-id-1033784' class='answer   answerof-262234 ' value='1033784'   \/><label for='answer-id-1033784' id='answer-label-1033784' class=' answer'><span>Azure Machine Learning Studio<\/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-262235'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>48. <\/span>An organization creates and deploys a multi-class image classification deep learning model that uses a set of labeled photographs. <br \/>\r<br>The software engineering team reports there is a heavy inferencing load for the prediction web services during the summer. The production web service for the model fails to meet demand despite having a fully-utilized compute cluster where the web service is deployed. <br \/>\r<br>You need to improve performance of the image classification web service with minimal downtime and minimal administrative effort. <br \/>\r<br>What should you advise the IT Operations team to do?<\/div><input type='hidden' name='question_id[]' id='qID_48' value='262235' \/><input type='hidden' id='answerType262235' 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-262235[]' id='answer-id-1033785' class='answer   answerof-262235 ' value='1033785'   \/><label for='answer-id-1033785' id='answer-label-1033785' class=' answer'><span>Increase the minimum node count of the compute cluster where the web service is deployed.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262235[]' id='answer-id-1033786' class='answer   answerof-262235 ' value='1033786'   \/><label for='answer-id-1033786' id='answer-label-1033786' class=' answer'><span>Create a new compute cluster by using larger VM sizes for the nodes, redeploy the web service to that cluster, and update the DNS registration for the service endpoint to point to the new cluster.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262235[]' id='answer-id-1033787' class='answer   answerof-262235 ' value='1033787'   \/><label for='answer-id-1033787' id='answer-label-1033787' class=' answer'><span>Increase the VM size of nodes in the compute cluster where the web service is deployed.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262235[]' id='answer-id-1033788' class='answer   answerof-262235 ' value='1033788'   \/><label for='answer-id-1033788' id='answer-label-1033788' class=' answer'><span>Increase the node count of the compute cluster where the web service is deployed.<\/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-262236'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>49. <\/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=626 height=263 id=\"\u56fe\u7247 318\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image074-2.jpg\"><br><br \/>\r<br>Does the solution meet the goal?<\/div><input type='hidden' name='question_id[]' id='qID_49' value='262236' \/><input type='hidden' id='answerType262236' 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-262236[]' id='answer-id-1033789' class='answer   answerof-262236 ' value='1033789'   \/><label for='answer-id-1033789' id='answer-label-1033789' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262236[]' id='answer-id-1033790' class='answer   answerof-262236 ' value='1033790'   \/><label for='answer-id-1033790' id='answer-label-1033790' class=' answer'><span>No<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-50' style=';'><div id='questionWrap-50'  class='   watupro-question-id-262237'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>50. <\/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_50' value='262237' \/><input type='hidden' id='answerType262237' 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-262237[]' id='answer-id-1033791' class='answer   answerof-262237 ' value='1033791'   \/><label for='answer-id-1033791' id='answer-label-1033791' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262237[]' id='answer-id-1033792' class='answer   answerof-262237 ' value='1033792'   \/><label for='answer-id-1033792' id='answer-label-1033792' class=' answer'><span>No<\/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-262238'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>51. <\/span>You create an Azure Machine Learning pipeline named pipeline 1 with two steps that contain Python scnpts. Data processed by the first step is passed to the second step. <br \/>\r<br>You must update the content of the downstream data source of pipeline 1 and run the pipeline again. <br \/>\r<br>You need to ensure the new run of pipeline 1 fully processes the updated content. <br \/>\r<br>Solution: Change the value of the compute.target parameter of the PythonScriptStep object in the two steps. <br \/>\r<br>Does the solution meet the goal'<\/div><input type='hidden' name='question_id[]' id='qID_51' value='262238' \/><input type='hidden' id='answerType262238' 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-262238[]' id='answer-id-1033793' class='answer   answerof-262238 ' value='1033793'   \/><label for='answer-id-1033793' id='answer-label-1033793' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262238[]' id='answer-id-1033794' class='answer   answerof-262238 ' value='1033794'   \/><label for='answer-id-1033794' id='answer-label-1033794' class=' answer'><span>No<\/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-262239'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>52. <\/span>You use the following code to define the steps for a pipeline: <br \/>\r<br>from azureml.core import Workspace, Experiment, Run <br \/>\r<br>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_52' value='262239' \/><input type='hidden' id='answerType262239' 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-262239[]' id='answer-id-1033795' class='answer   answerof-262239 ' value='1033795'   \/><label for='answer-id-1033795' id='answer-label-1033795' 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-262239[]' id='answer-id-1033796' class='answer   answerof-262239 ' value='1033796'   \/><label for='answer-id-1033796' id='answer-label-1033796' class=' answer'><span>run = Run(pipeline_steps)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-262239[]' id='answer-id-1033797' class='answer   answerof-262239 ' value='1033797'   \/><label for='answer-id-1033797' id='answer-label-1033797' class=' answer'><span>pipeline = Pipeline(workspace=ws, steps=pipeline_steps) experiment = Experiment(workspace=ws, name='pipeline-experiment') run = experiment.submit(pipeline)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-262239[]' id='answer-id-1033798' class='answer   answerof-262239 ' value='1033798'   \/><label for='answer-id-1033798' id='answer-label-1033798' 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-53' style=';'><div id='questionWrap-53'  class='   watupro-question-id-262240'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>53. <\/span>You use the Azure Machine Learning designer to create and run a training pipeline. <br \/>\r<br>The pipeline must be run every night to inference predictions from a large volume of files. <br \/>\r<br>The folder where the files will be stored is defined as a dataset. <br \/>\r<br>You need to publish the pipeline as a REST service that can be used for the nightly inferencing run. <br \/>\r<br>What should you do?<\/div><input type='hidden' name='question_id[]' id='qID_53' value='262240' \/><input type='hidden' id='answerType262240' 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-262240[]' id='answer-id-1033799' class='answer   answerof-262240 ' value='1033799'   \/><label for='answer-id-1033799' id='answer-label-1033799' class=' answer'><span>Create a batch inference pipeline<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262240[]' id='answer-id-1033800' class='answer   answerof-262240 ' value='1033800'   \/><label for='answer-id-1033800' id='answer-label-1033800' class=' answer'><span>Set the compute target for the pipeline to an inference cluster<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262240[]' id='answer-id-1033801' class='answer   answerof-262240 ' value='1033801'   \/><label for='answer-id-1033801' id='answer-label-1033801' class=' answer'><span>Create a real-time inference pipeline<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262240[]' id='answer-id-1033802' class='answer   answerof-262240 ' value='1033802'   \/><label for='answer-id-1033802' id='answer-label-1033802' class=' answer'><span>Clone the pipeline<\/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-262241'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>54. <\/span>You create an Azure Machine Learning workspace. <br \/>\r<br>You must create a custom role named DataScientist that meets the following requirements: <br \/>\r<br>&#10001; Role members must not be able to delete the workspace. <br \/>\r<br>&#10001; Role members must not be able to create, update, or delete compute resource in the workspace. <br \/>\r<br>&#10001; Role members must not be able to add new users to the workspace. <br \/>\r<br>You need to create a JSON file for the DataScientist role in the Azure Machine Learning workspace. <br \/>\r<br>The custom role must enforce the restrictions specified by the IT Operations team. <br \/>\r<br>Which JSON code segment should you use? <br \/>\r<br>A) <br \/>\r<br><br><img decoding=\"async\" width=649 height=189 id=\"\u56fe\u7247 54\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image075-2.jpg\"><br><br \/>\r<br>B) <br \/>\r<br><br><img decoding=\"async\" width=650 height=133 id=\"\u56fe\u7247 55\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image076-2.jpg\"><br><br \/>\r<br>C) <br \/>\r<br><br><img decoding=\"async\" width=649 height=177 id=\"\u56fe\u7247 56\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image077-2.jpg\"><br><br \/>\r<br>D) <br \/>\r<br><br><img decoding=\"async\" width=649 height=135 id=\"\u56fe\u7247 57\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image078-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_54' value='262241' \/><input type='hidden' id='answerType262241' 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-262241[]' id='answer-id-1033803' class='answer   answerof-262241 ' value='1033803'   \/><label for='answer-id-1033803' id='answer-label-1033803' class=' answer'><span>Option A<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262241[]' id='answer-id-1033804' class='answer   answerof-262241 ' value='1033804'   \/><label for='answer-id-1033804' id='answer-label-1033804' class=' answer'><span>Option B<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262241[]' id='answer-id-1033805' class='answer   answerof-262241 ' value='1033805'   \/><label for='answer-id-1033805' id='answer-label-1033805' class=' answer'><span>Option C<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262241[]' id='answer-id-1033806' class='answer   answerof-262241 ' value='1033806'   \/><label for='answer-id-1033806' id='answer-label-1033806' class=' answer'><span>Option D<\/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-262242'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>55. <\/span>HOTSPOT <br \/>\r<br>You are preparing to build a deep learning convolutional neural network model for image classification. You create a script to train the model using CUDA devices. <br \/>\r<br>You must submit an experiment that runs this script in the Azure Machine Learning workspace. <br \/>\r<br>The following compute resources are available: <br \/>\r<br>&#10001; a Microsoft Surface device on which Microsoft Office has been installed. Corporate IT policies prevent the installation of additional software <br \/>\r<br>&#10001; a Compute Instance named ds-workstation in the workspace with 2 CPUs and 8 GB of memory <br \/>\r<br>&#10001; an Azure Machine Learning compute target named cpu-cluster with eight CPU-based nodes <br \/>\r<br>&#10001; an Azure Machine Learning compute target named gpu-cluster with four CPU and GPU-based nodes <br \/>\r<br>You need to specify the compute resources to be used for running the code to submit the experiment, and for running the script in order to minimize model training time. <br \/>\r<br>Which resources should the data scientist use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=523 height=333 id=\"\u56fe\u7247 325\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image079-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_55' value='262242' \/><input type='hidden' id='answerType262242' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262242[]' id='textarea_q_262242' 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-262243'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>56. <\/span>DRAG DROP <br \/>\r<br>You are producing a multiple linear regression model in Azure Machine Learning Studio. <br \/>\r<br>Several independent variables are highly correlated. <br \/>\r<br>You need to select appropriate methods for conducting effective feature engineering on all the data. <br \/>\r<br>Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order. <br \/>\r<br><br><img decoding=\"async\" width=649 height=318 id=\"\u56fe\u7247 46\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image081-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_56' value='262243' \/><input type='hidden' id='answerType262243' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262243[]' id='textarea_q_262243' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-57' style=';'><div id='questionWrap-57'  class='   watupro-question-id-262244'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>57. <\/span>HOTSPOT <br \/>\r<br>You collect data from a nearby weather station. <br \/>\r<br>You have a pandas dataframe named weather_df that includes the following data: <br \/>\r<br><br><img decoding=\"async\" width=618 height=105 id=\"\u56fe\u7247 76\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image083-2.jpg\"><br><br \/>\r<br>The data is collected every 12 hours: noon and midnight. <br \/>\r<br>You plan to use automated machine learning to create a time-series model that predicts temperature over the next seven days. For the initial round of training, you want to train a <br \/>\r<br>maximum of 50 different models. <br \/>\r<br>You must use the Azure Machine Learning SDK to run an automated machine learning experiment to train these models. <br \/>\r<br>You need to configure the automated machine learning run. <br \/>\r<br>How should you complete the AutoMLConfig definition? 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=832 id=\"\u56fe\u7247 77\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image084-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_57' value='262244' \/><input type='hidden' id='answerType262244' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262244[]' id='textarea_q_262244' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-58' style=';'><div id='questionWrap-58'  class='   watupro-question-id-262245'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>58. <\/span>You are profiling mltabte data assets by using Azure Machine Learning studio. You need to detect columns with odd or missing values. <br \/>\r<br>Which statistic should you analyze?<\/div><input type='hidden' name='question_id[]' id='qID_58' value='262245' \/><input type='hidden' id='answerType262245' 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-262245[]' id='answer-id-1033810' class='answer   answerof-262245 ' value='1033810'   \/><label for='answer-id-1033810' id='answer-label-1033810' class=' answer'><span>Profile<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262245[]' id='answer-id-1033811' class='answer   answerof-262245 ' value='1033811'   \/><label for='answer-id-1033811' id='answer-label-1033811' class=' answer'><span>Std deviation<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262245[]' id='answer-id-1033812' class='answer   answerof-262245 ' value='1033812'   \/><label for='answer-id-1033812' id='answer-label-1033812' class=' answer'><span>Error count<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262245[]' id='answer-id-1033813' class='answer   answerof-262245 ' value='1033813'   \/><label for='answer-id-1033813' id='answer-label-1033813' class=' answer'><span>Type<\/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-262246'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>59. <\/span>DRAG DROP <br \/>\r<br>You train and register a model by using the Azure Machine Learning SDK on a local workstation. Python 3.6 and Visual Studio Code are installed on the workstation. <br \/>\r<br>When you try to deploy the model into production as an Azure Kubernetes Service (AKS)-based web service, you experience an error in the scoring script that causes deployment to fail. <br \/>\r<br>You need to debug the service on the local workstation before deploying the service to production. <br \/>\r<br>Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order. <br \/>\r<br><br><img decoding=\"async\" width=649 height=196 id=\"\u56fe\u7247 65\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image086-2.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_59' value='262246' \/><input type='hidden' id='answerType262246' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262246[]' id='textarea_q_262246' 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-262247'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>60. <\/span>You create and register a model in an Azure Machine Learning workspace. <br \/>\r<br>You must use the Azure Machine Learning SDK to implement a batch inference pipeline that uses a ParallelRunStep to score input data using the model. You must specify a value for the ParallelRunConfig compute_target setting of the pipeline step. <br \/>\r<br>You need to create the compute target. <br \/>\r<br>Which class should you use?<\/div><input type='hidden' name='question_id[]' id='qID_60' value='262247' \/><input type='hidden' id='answerType262247' 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-262247[]' id='answer-id-1033815' class='answer   answerof-262247 ' value='1033815'   \/><label for='answer-id-1033815' id='answer-label-1033815' class=' answer'><span>BatchCompute<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262247[]' id='answer-id-1033816' class='answer   answerof-262247 ' value='1033816'   \/><label for='answer-id-1033816' id='answer-label-1033816' class=' answer'><span>AdlaCompute<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262247[]' id='answer-id-1033817' class='answer   answerof-262247 ' value='1033817'   \/><label for='answer-id-1033817' id='answer-label-1033817' class=' answer'><span>AmlCompute<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262247[]' id='answer-id-1033818' class='answer   answerof-262247 ' value='1033818'   \/><label for='answer-id-1033818' id='answer-label-1033818' class=' answer'><span>Aks Compute<\/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-262248'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>61. <\/span>Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. <br \/>\r<br>After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. <br \/>\r<br>You are creating a new experiment in Azure Machine Learning Studio. <br \/>\r<br>One class has a much smaller number of observations than tin- other classes in the training set. <br \/>\r<br>You need to select an appropriate data sampling strategy to compensate for the class imbalance. <br \/>\r<br>Solution: You use the Principal Components Analysis (PCA) sampling mode. <br \/>\r<br>Does the solution meet the goal?<\/div><input type='hidden' name='question_id[]' id='qID_61' value='262248' \/><input type='hidden' id='answerType262248' 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-262248[]' id='answer-id-1033819' class='answer   answerof-262248 ' value='1033819'   \/><label for='answer-id-1033819' id='answer-label-1033819' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262248[]' id='answer-id-1033820' class='answer   answerof-262248 ' value='1033820'   \/><label for='answer-id-1033820' id='answer-label-1033820' class=' answer'><span>No<\/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-262249'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>62. <\/span>You must store data in Azure Blob Storage to support Azure Machine Learning. <br \/>\r<br>You need to transfer the data into Azure Blob Storage. <br \/>\r<br>What are three possible ways to achieve the goal? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.<\/div><input type='hidden' name='question_id[]' id='qID_62' value='262249' \/><input type='hidden' id='answerType262249' 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-262249[]' id='answer-id-1033821' class='answer   answerof-262249 ' value='1033821'   \/><label for='answer-id-1033821' id='answer-label-1033821' class=' answer'><span>Bulk Insert SQL Query<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-262249[]' id='answer-id-1033822' class='answer   answerof-262249 ' value='1033822'   \/><label for='answer-id-1033822' id='answer-label-1033822' class=' answer'><span>AzCopy<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-262249[]' id='answer-id-1033823' class='answer   answerof-262249 ' value='1033823'   \/><label for='answer-id-1033823' id='answer-label-1033823' class=' answer'><span>Python script<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-262249[]' id='answer-id-1033824' class='answer   answerof-262249 ' value='1033824'   \/><label for='answer-id-1033824' id='answer-label-1033824' class=' answer'><span>Azure Storage Explorer<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-262249[]' id='answer-id-1033825' class='answer   answerof-262249 ' value='1033825'   \/><label for='answer-id-1033825' id='answer-label-1033825' class=' answer'><span>Bulk Copy Program (BCP)<\/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-262250'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>63. <\/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_63' value='262250' \/><input type='hidden' id='answerType262250' 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-262250[]' id='answer-id-1033826' class='answer   answerof-262250 ' value='1033826'   \/><label for='answer-id-1033826' id='answer-label-1033826' class=' answer'><span>Split Data<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262250[]' id='answer-id-1033827' class='answer   answerof-262250 ' value='1033827'   \/><label for='answer-id-1033827' id='answer-label-1033827' class=' answer'><span>Load Trained Model<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262250[]' id='answer-id-1033828' class='answer   answerof-262250 ' value='1033828'   \/><label for='answer-id-1033828' id='answer-label-1033828' class=' answer'><span>Assign Data to Clusters<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262250[]' id='answer-id-1033829' class='answer   answerof-262250 ' value='1033829'   \/><label for='answer-id-1033829' id='answer-label-1033829' class=' answer'><span>Group Data into Bins<\/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-262251'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>64. <\/span>HOTSPOT <br \/>\r<br>You train a machine learning model by using Aunt Machine Learning. <br \/>\r<br>You use the following training script m Python to log an accuracy value. <br \/>\r<br><br><img decoding=\"async\" width=247 height=39 id=\"\u56fe\u7247 541\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image088-2.jpg\"><br><br \/>\r<br>You must use a Python script to define a sweep job. <br \/>\r<br>You need to provide the primary metric and goal you want hyper parameter tuning to optimize. <br \/>\r<br>How should you complete the Python script? 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=363 height=188 id=\"\u56fe\u7247 543\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image089-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_64' value='262251' \/><input type='hidden' id='answerType262251' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262251[]' id='textarea_q_262251' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-65' style=';'><div id='questionWrap-65'  class='   watupro-question-id-262252'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>65. <\/span>You are planning to register a trained model in an Azure Machine Learning workspace. <br \/>\r<br>You must store additional metadata about the model in a key-value format. You must be able to add new metadata and modify or delete metadata after creation. <br \/>\r<br>You need to register the model. <br \/>\r<br>Which parameter should you use?<\/div><input type='hidden' name='question_id[]' id='qID_65' value='262252' \/><input type='hidden' id='answerType262252' 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-262252[]' id='answer-id-1033831' class='answer   answerof-262252 ' value='1033831'   \/><label for='answer-id-1033831' id='answer-label-1033831' class=' answer'><span>description<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262252[]' id='answer-id-1033832' class='answer   answerof-262252 ' value='1033832'   \/><label for='answer-id-1033832' id='answer-label-1033832' class=' answer'><span>model_framework<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262252[]' id='answer-id-1033833' class='answer   answerof-262252 ' value='1033833'   \/><label for='answer-id-1033833' id='answer-label-1033833' class=' answer'><span>cags<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262252[]' id='answer-id-1033834' class='answer   answerof-262252 ' value='1033834'   \/><label for='answer-id-1033834' id='answer-label-1033834' class=' answer'><span>properties<\/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-262253'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>66. <\/span>HOTSPOT <br \/>\r<br>You are analyzing the asymmetry in a statistical distribution. <br \/>\r<br>The following image contains two density curves that show the probability distribution of two datasets. <br \/>\r<br><br><img decoding=\"async\" width=649 height=214 id=\"\u56fe\u7247 212\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image091-1.jpg\"><br><br \/>\r<br>Use the drop-down menus to select the answer choice that answers each question based on the information presented in the graphic. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=632 height=308 id=\"\u56fe\u7247 213\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image092-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_66' value='262253' \/><input type='hidden' id='answerType262253' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262253[]' id='textarea_q_262253' 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-67' style=';'><div id='questionWrap-67'  class='   watupro-question-id-262254'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>67. <\/span>You have a dataset that includes confidential data. You use the dataset to train a model. <br \/>\r<br>You must use a differential privacy parameter to keep the data of individuals safe and private. <br \/>\r<br>You need to reduce the effect of user data on aggregated results. <br \/>\r<br>What should you do?<\/div><input type='hidden' name='question_id[]' id='qID_67' value='262254' \/><input type='hidden' id='answerType262254' 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-262254[]' id='answer-id-1033836' class='answer   answerof-262254 ' value='1033836'   \/><label for='answer-id-1033836' id='answer-label-1033836' class=' answer'><span>Decrease the value of the epsilon parameter to reduce the amount of noise added to the data<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262254[]' id='answer-id-1033837' class='answer   answerof-262254 ' value='1033837'   \/><label for='answer-id-1033837' id='answer-label-1033837' class=' answer'><span>Increase the value of the epsilon parameter to decrease privacy and increase accuracy<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262254[]' id='answer-id-1033838' class='answer   answerof-262254 ' value='1033838'   \/><label for='answer-id-1033838' id='answer-label-1033838' class=' answer'><span>Decrease the value of the epsilon parameter to increase privacy and reduce accuracy<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262254[]' id='answer-id-1033839' class='answer   answerof-262254 ' value='1033839'   \/><label for='answer-id-1033839' id='answer-label-1033839' class=' answer'><span>Set the value of the epsilon parameter to 1 to ensure maximum privacy<\/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-262255'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>68. <\/span>You create a batch inference pipeline by using the Azure ML SDK. <br \/>\r<br>You configure the pipeline parameters by executing the following code: <br \/>\r<br><br><img decoding=\"async\" width=601 height=215 id=\"\u56fe\u7247 121\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image094-1.jpg\"><br><br \/>\r<br>You need to obtain the output from the pipeline execution. <br \/>\r<br>Where will you find the output?<\/div><input type='hidden' name='question_id[]' id='qID_68' value='262255' \/><input type='hidden' id='answerType262255' 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-262255[]' id='answer-id-1033840' class='answer   answerof-262255 ' value='1033840'   \/><label for='answer-id-1033840' id='answer-label-1033840' class=' answer'><span>the Activity Log in the Azure portal for the Machine Learning workspace<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262255[]' id='answer-id-1033841' class='answer   answerof-262255 ' value='1033841'   \/><label for='answer-id-1033841' id='answer-label-1033841' class=' answer'><span>a file named parallel_run_step.txt located in the output folder<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262255[]' id='answer-id-1033842' class='answer   answerof-262255 ' value='1033842'   \/><label for='answer-id-1033842' id='answer-label-1033842' class=' answer'><span>the digitjdentification.py script<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262255[]' id='answer-id-1033843' class='answer   answerof-262255 ' value='1033843'   \/><label for='answer-id-1033843' id='answer-label-1033843' class=' answer'><span>the Inference Clusters tab in Machine Learning studio<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262255[]' id='answer-id-1033844' class='answer   answerof-262255 ' value='1033844'   \/><label for='answer-id-1033844' id='answer-label-1033844' class=' answer'><span>the debug log<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-69' style=';'><div id='questionWrap-69'  class='   watupro-question-id-262256'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>69. <\/span>You create a binary classification model by using Azure Machine Learning Studio. <br \/>\r<br>You must tune hyperparameters by performing a parameter sweep of the model. <br \/>\r<br>The parameter sweep must meet the following requirements: <br \/>\r<br>&#10001; iterate all possible combinations of hyperparameters <br \/>\r<br>&#10001; minimize computing resources required to perform the sweep <br \/>\r<br>&#10001; You need to perform a parameter sweep of the model. <br \/>\r<br>Which parameter sweep mode should you use?<\/div><input type='hidden' name='question_id[]' id='qID_69' value='262256' \/><input type='hidden' id='answerType262256' 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-262256[]' id='answer-id-1033845' class='answer   answerof-262256 ' value='1033845'   \/><label for='answer-id-1033845' id='answer-label-1033845' class=' answer'><span>Random sweep<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262256[]' id='answer-id-1033846' class='answer   answerof-262256 ' value='1033846'   \/><label for='answer-id-1033846' id='answer-label-1033846' class=' answer'><span>Sweep clustering<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262256[]' id='answer-id-1033847' class='answer   answerof-262256 ' value='1033847'   \/><label for='answer-id-1033847' id='answer-label-1033847' class=' answer'><span>Entire grid<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262256[]' id='answer-id-1033848' class='answer   answerof-262256 ' value='1033848'   \/><label for='answer-id-1033848' id='answer-label-1033848' class=' answer'><span>Random grid<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262256[]' id='answer-id-1033849' class='answer   answerof-262256 ' value='1033849'   \/><label for='answer-id-1033849' id='answer-label-1033849' class=' answer'><span>Random seed<\/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-262257'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>70. <\/span>HOTSPOT <br \/>\r<br>The finance team asks you to train a model using data in an Azure Storage blob container named finance-data. <br \/>\r<br>You need to register the container as a datastore in an Azure Machine Learning workspace and ensure that an error will be raised if the container does not exist. <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=341 id=\"\u56fe\u7247 63\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image095-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_70' value='262257' \/><input type='hidden' id='answerType262257' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262257[]' id='textarea_q_262257' 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-71' style=';'><div id='questionWrap-71'  class='   watupro-question-id-262258'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>71. <\/span>DRAG DROP <br \/>\r<br>You are using a Git repository to track work in an Azure Machine Learning workspace. <br \/>\r<br>You need to authenticate a Git account by using SSH. <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=270 id=\"\u56fe\u7247 296\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image097-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_71' value='262258' \/><input type='hidden' id='answerType262258' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262258[]' id='textarea_q_262258' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-72' style=';'><div id='questionWrap-72'  class='   watupro-question-id-262259'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>72. <\/span>HOTSPOT <br \/>\r<br>You are hired as a data scientist at a winery. The previous data scientist used Azure Machine Learning. <br \/>\r<br>You need to review the models and explain how each model makes decisions. <br \/>\r<br>Which explainer modules should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=563 height=424 id=\"\u56fe\u7247 294\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image099-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_72' value='262259' \/><input type='hidden' id='answerType262259' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262259[]' id='textarea_q_262259' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-73' style=';'><div id='questionWrap-73'  class='   watupro-question-id-262260'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>73. <\/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=615 height=180 id=\"\u56fe\u7247 211\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image101-1.jpg\"><br><br \/>\r<br>Does the solution meet the goal?<\/div><input type='hidden' name='question_id[]' id='qID_73' value='262260' \/><input type='hidden' id='answerType262260' 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-262260[]' id='answer-id-1033853' class='answer   answerof-262260 ' value='1033853'   \/><label for='answer-id-1033853' id='answer-label-1033853' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262260[]' id='answer-id-1033854' class='answer   answerof-262260 ' value='1033854'   \/><label for='answer-id-1033854' id='answer-label-1033854' class=' answer'><span>No<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-74' style=';'><div id='questionWrap-74'  class='   watupro-question-id-262261'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>74. <\/span>DRAG DROP <br \/>\r<br>You have an existing GitHub repository containing Azure Machine Learning project files. <br \/>\r<br>You need to clone the repository to your Azure Machine Learning shared workspace file system. <br \/>\r<br>Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order. 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=158 id=\"\u56fe\u7247 548\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image102-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_74' value='262261' \/><input type='hidden' id='answerType262261' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262261[]' id='textarea_q_262261' 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-262262'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>75. <\/span>You plan to use a Data Science Virtual Machine (DSVM) with the open source deep learning frameworks Caffe2 and Theano. You need to select a pre configured DSVM to support the framework. <br \/>\r<br>What should you create?<\/div><input type='hidden' name='question_id[]' id='qID_75' value='262262' \/><input type='hidden' id='answerType262262' 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-262262[]' id='answer-id-1033856' class='answer   answerof-262262 ' value='1033856'   \/><label for='answer-id-1033856' id='answer-label-1033856' class=' answer'><span>Data Science Virtual Machine for Linux (CentOS)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262262[]' id='answer-id-1033857' class='answer   answerof-262262 ' value='1033857'   \/><label for='answer-id-1033857' id='answer-label-1033857' class=' answer'><span>Data Science Virtual Machine for Windows 2012<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262262[]' id='answer-id-1033858' class='answer   answerof-262262 ' value='1033858'   \/><label for='answer-id-1033858' id='answer-label-1033858' class=' answer'><span>Data Science Virtual Machine for Windows 2016<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262262[]' id='answer-id-1033859' class='answer   answerof-262262 ' value='1033859'   \/><label for='answer-id-1033859' id='answer-label-1033859' class=' answer'><span>Geo AI Data Science Virtual Machine with ArcGIS<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262262[]' id='answer-id-1033860' class='answer   answerof-262262 ' value='1033860'   \/><label for='answer-id-1033860' id='answer-label-1033860' class=' answer'><span>Data Science Virtual Machine for Linux (Ubuntu)<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-76' style=';'><div id='questionWrap-76'  class='   watupro-question-id-262263'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>76. <\/span>HOTSPOT <br \/>\r<br>You have a dataset created for multiclass classification tasks that contains a normalized numerical feature set with 10,000 data points and 150 features. <br \/>\r<br>You use 75 percent of the data points for training and 25 percent for testing. You are using the scikit-learn machine learning library in Python. You use X to denote the feature set and Y to denote class labels. <br \/>\r<br>You create the following Python data frames: <br \/>\r<br><br><img decoding=\"async\" width=292 height=96 id=\"\u56fe\u7247 122\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image104-1.jpg\"><br><br \/>\r<br>You need to apply the Principal Component Analysis (PCA) method to reduce the dimensionality of the feature set to 10 features in both training and testing sets. <br \/>\r<br>How should you complete the code segment? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=531 height=391 id=\"\u56fe\u7247 123\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image105-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_76' value='262263' \/><input type='hidden' id='answerType262263' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262263[]' id='textarea_q_262263' 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-77' style=';'><div id='questionWrap-77'  class='   watupro-question-id-262264'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>77. <\/span>You are performing clustering by using the K-means algorithm. <br \/>\r<br>You need to define the possible termination conditions. <br \/>\r<br>Which three conditions can you use? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.<\/div><input type='hidden' name='question_id[]' id='qID_77' value='262264' \/><input type='hidden' id='answerType262264' 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-262264[]' id='answer-id-1033862' class='answer   answerof-262264 ' value='1033862'   \/><label for='answer-id-1033862' id='answer-label-1033862' class=' answer'><span>A fixed number of iterations is executed.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-262264[]' id='answer-id-1033863' class='answer   answerof-262264 ' value='1033863'   \/><label for='answer-id-1033863' id='answer-label-1033863' class=' answer'><span>The residual sum of squares (RSS) rises above a threshold.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-262264[]' id='answer-id-1033864' class='answer   answerof-262264 ' value='1033864'   \/><label for='answer-id-1033864' id='answer-label-1033864' class=' answer'><span>The sum of distances between centroids reaches a maximum.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-262264[]' id='answer-id-1033865' class='answer   answerof-262264 ' value='1033865'   \/><label for='answer-id-1033865' id='answer-label-1033865' class=' answer'><span>The residual sum of squares (RSS) falls below a threshold.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-262264[]' id='answer-id-1033866' class='answer   answerof-262264 ' value='1033866'   \/><label for='answer-id-1033866' id='answer-label-1033866' class=' answer'><span>Centroids do not change between iterations.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-78' style=';'><div id='questionWrap-78'  class='   watupro-question-id-262265'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>78. <\/span>You create a datastore named training_data that references a blob container in an Azure Storage account. The blob container contains a folder named csv_files in which multiple comma-separated values (CSV) files are stored. <br \/>\r<br>You have a script named train.py in a local folder named .\/script that you plan to run as an experiment using an estimator. <br \/>\r<br>The script includes the following code to read data from the csv_files folder: <br \/>\r<br><br><img decoding=\"async\" width=649 height=322 id=\"\u56fe\u7247 82\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image107-1.jpg\"><br><br \/>\r<br>You have the following script. <br \/>\r<br><br><img decoding=\"async\" width=586 height=243 id=\"\u56fe\u7247 83\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image108-1.jpg\"><br><br \/>\r<br>You need to configure the estimator for the experiment so that the script can read the data from a data reference named data_ref that references the csv_files folder in the training_data datastore. <br \/>\r<br>Which code should you use to configure the estimator? <br \/>\r<br>A) <br \/>\r<br><br><img decoding=\"async\" width=649 height=70 id=\"\u56fe\u7247 84\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image109-1.jpg\"><br><br \/>\r<br>B) <br \/>\r<br><br><img decoding=\"async\" width=526 height=151 id=\"\u56fe\u7247 85\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image110-1.jpg\"><br><br \/>\r<br>C) <br \/>\r<br><br><img decoding=\"async\" width=649 height=86 id=\"\u56fe\u7247 86\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image111-1.jpg\"><br><br \/>\r<br>D) <br \/>\r<br><br><img decoding=\"async\" width=650 height=128 id=\"\u56fe\u7247 87\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image112-1.jpg\"><br><br \/>\r<br>E) <br \/>\r<br><br><img decoding=\"async\" width=649 height=65 id=\"\u56fe\u7247 88\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image113-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_78' value='262265' \/><input type='hidden' id='answerType262265' 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-262265[]' id='answer-id-1033867' class='answer   answerof-262265 ' value='1033867'   \/><label for='answer-id-1033867' id='answer-label-1033867' class=' answer'><span>Option A<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262265[]' id='answer-id-1033868' class='answer   answerof-262265 ' value='1033868'   \/><label for='answer-id-1033868' id='answer-label-1033868' class=' answer'><span>Option B<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262265[]' id='answer-id-1033869' class='answer   answerof-262265 ' value='1033869'   \/><label for='answer-id-1033869' id='answer-label-1033869' class=' answer'><span>Option C<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262265[]' id='answer-id-1033870' class='answer   answerof-262265 ' value='1033870'   \/><label for='answer-id-1033870' id='answer-label-1033870' class=' answer'><span>Option D<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262265[]' id='answer-id-1033871' class='answer   answerof-262265 ' value='1033871'   \/><label for='answer-id-1033871' id='answer-label-1033871' class=' answer'><span>Option E<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-79' style=';'><div id='questionWrap-79'  class='   watupro-question-id-262266'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>79. <\/span>HOTSPOT <br \/>\r<br>You are performing a classification task in Azure Machine Learning Studio. <br \/>\r<br>You must prepare balanced testing and training samples based on a provided data set. <br \/>\r<br>You need to split the data with a 0.75:0.25 ratio. <br \/>\r<br>Which value should you use for each parameter? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=537 height=571 id=\"\u56fe\u7247 160\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image114.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_79' value='262266' \/><input type='hidden' id='answerType262266' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262266[]' id='textarea_q_262266' 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-80' style=';'><div id='questionWrap-80'  class='   watupro-question-id-262267'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>80. <\/span>HOTSPOT <br \/>\r<br>You manage an Azure Machine Learning workspace. You create an experiment named experiment1 by using the Azure Machine Learning Python SDK v2 and MLflow. <br \/>\r<br><br><img decoding=\"async\" width=296 height=125 id=\"\u56fe\u7247 2556\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image116.jpg\"><br><br \/>\r<br>For each of the following statements, select Yes if the statement rs true. Otherwise, select No. <br \/>\r<br><br><img decoding=\"async\" width=649 height=161 id=\"\u56fe\u7247 2558\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image117.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_80' value='262267' \/><input type='hidden' id='answerType262267' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262267[]' id='textarea_q_262267' 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-81' style=';'><div id='questionWrap-81'  class='   watupro-question-id-262268'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>81. <\/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=599 height=240 id=\"\u56fe\u7247 91\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image119.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=649 height=234 id=\"\u56fe\u7247 92\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image120.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_81' value='262268' \/><input type='hidden' id='answerType262268' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262268[]' id='textarea_q_262268' 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-82' style=';'><div id='questionWrap-82'  class='   watupro-question-id-262269'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>82. <\/span>HOTSPOT <br \/>\r<br>You have a multi-class image classification deep learning model that uses a set of labeled photographs. <br \/>\r<br>You create the following code to select hyperparameter values when training the model. <br \/>\r<br><br><img decoding=\"async\" width=597 height=122 id=\"\u56fe\u7247 99\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image122.jpg\"><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=649 height=187 id=\"\u56fe\u7247 100\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image123.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_82' value='262269' \/><input type='hidden' id='answerType262269' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262269[]' id='textarea_q_262269' 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-83' style=';'><div id='questionWrap-83'  class='   watupro-question-id-262270'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>83. <\/span>You train and register an Azure Machine Learning model <br \/>\r<br>You plan to deploy the model to an online endpoint <br \/>\r<br>You need to ensure that applications will be able to use the authentication method with a non-expiring artifact to access the model. <br \/>\r<br>Solution: <br \/>\r<br>Create a managed online endpoint and set the value of its auth.mode parameter to aml.token. Deploy the model to the online endpoint. <br \/>\r<br>Does the solution meet the goal?<\/div><input type='hidden' name='question_id[]' id='qID_83' value='262270' \/><input type='hidden' id='answerType262270' 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-262270[]' id='answer-id-1033876' class='answer   answerof-262270 ' value='1033876'   \/><label for='answer-id-1033876' id='answer-label-1033876' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262270[]' id='answer-id-1033877' class='answer   answerof-262270 ' value='1033877'   \/><label for='answer-id-1033877' id='answer-label-1033877' class=' answer'><span>No<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-84' style=';'><div id='questionWrap-84'  class='   watupro-question-id-262271'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>84. <\/span>HOTSPOT <br \/>\r<br>You use Data Science Virtual Machines (DSVMs) for Windows and Linux in Azure. <br \/>\r<br>You need to access the DSVMs. <br \/>\r<br>Which utilities should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=503 height=354 id=\"\u56fe\u7247 558\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image125.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_84' value='262271' \/><input type='hidden' id='answerType262271' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262271[]' id='textarea_q_262271' 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-85' style=';'><div id='questionWrap-85'  class='   watupro-question-id-262272'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>85. <\/span>Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. <br \/>\r<br>After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. <br \/>\r<br>You are creating a model to predict the price of a student\u2019s artwork depending on the following variables: the student\u2019s length of education, degree type, and art form. <br \/>\r<br>You start by creating a linear regression model. <br \/>\r<br>You need to evaluate the linear regression model. <br \/>\r<br>Solution: Use the following metrics: Relative Squared Error, Coefficient of Determination, Accuracy, Precision, Recall, F1 score, and AUC. <br \/>\r<br>Does the solution meet the goal?<\/div><input type='hidden' name='question_id[]' id='qID_85' value='262272' \/><input type='hidden' id='answerType262272' 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-262272[]' id='answer-id-1033879' class='answer   answerof-262272 ' value='1033879'   \/><label for='answer-id-1033879' id='answer-label-1033879' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262272[]' id='answer-id-1033880' class='answer   answerof-262272 ' value='1033880'   \/><label for='answer-id-1033880' id='answer-label-1033880' class=' answer'><span>No<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-86' style=';'><div id='questionWrap-86'  class='   watupro-question-id-262273'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>86. <\/span>HOTSPOT <br \/>\r<br>You create an experiment in Azure Machine Learning Studio- You add a training dataset that contains 10.000 rows. The first 9.000 rows represent class 0 (90 percent). The first 1.000 rows represent class 1 (10 percent). <br \/>\r<br>The training set is unbalanced between two Classes. You must increase the number of training examples for class 1 to 4,000 by using data rows. You add the Synthetic Minority Oversampling Technique (SMOTE) module to the experiment. <br \/>\r<br>You need to configure the module. <br \/>\r<br>Which values should you use? To answer, select the appropriate options in the dialog box in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=619 height=236 id=\"\u56fe\u7247 187\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image127.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_86' value='262273' \/><input type='hidden' id='answerType262273' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262273[]' id='textarea_q_262273' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-87' style=';'><div id='questionWrap-87'  class='   watupro-question-id-262274'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>87. <\/span>HOTSPOT <br \/>\r<br>You are using C-Support Vector classification to do a multi-class classification with an unbalanced training dataset. <br \/>\r<br>The C-Support Vector classification using Python code shown below: <br \/>\r<br><br><img decoding=\"async\" width=650 height=92 id=\"\u56fe\u7247 315\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image129.jpg\"><br><br \/>\r<br>You need to evaluate the C-Support Vector classification code. <br \/>\r<br>Which evaluation statement should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=649 height=225 id=\"\u56fe\u7247 316\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image130.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_87' value='262274' \/><input type='hidden' id='answerType262274' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262274[]' id='textarea_q_262274' 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-88' style=';'><div id='questionWrap-88'  class='   watupro-question-id-262275'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>88. <\/span>You create a new Azure subscription. No resources are provisioned in the subscription. <br \/>\r<br>You need to create an Azure Machine Learning workspace. <br \/>\r<br>What are three possible ways to achieve this goal? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.<\/div><input type='hidden' name='question_id[]' id='qID_88' value='262275' \/><input type='hidden' id='answerType262275' 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-262275[]' id='answer-id-1033883' class='answer   answerof-262275 ' value='1033883'   \/><label for='answer-id-1033883' id='answer-label-1033883' class=' answer'><span>Run Python code that uses the Azure ML SDK library and calls the Workspace.create method with name, subscription_id, resource_group, and location parameters.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-262275[]' id='answer-id-1033884' class='answer   answerof-262275 ' value='1033884'   \/><label for='answer-id-1033884' id='answer-label-1033884' class=' answer'><span>Use an Azure Resource Management template that includes a Microsoft.MachineLearningServices\/ workspaces resource and its dependencies.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-262275[]' id='answer-id-1033885' class='answer   answerof-262275 ' value='1033885'   \/><label for='answer-id-1033885' id='answer-label-1033885' class=' answer'><span>Use the Azure Command Line Interface (CLI) with the Azure Machine Learning extension to call the az \r\ngroup create function with --name and --location parameters, and then the az ml workspace create \r\nfunction, specifying Cw and Cg parameters for the workspace name and resource group.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-262275[]' id='answer-id-1033886' class='answer   answerof-262275 ' value='1033886'   \/><label for='answer-id-1033886' id='answer-label-1033886' class=' answer'><span>Navigate to Azure Machine Learning studio and create a workspace.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-262275[]' id='answer-id-1033887' class='answer   answerof-262275 ' value='1033887'   \/><label for='answer-id-1033887' id='answer-label-1033887' class=' answer'><span>Run Python code that uses the Azure ML SDK library and calls the Workspace.get method with name, \r\nsubscription_id, and resource_group parameters.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-89' style=';'><div id='questionWrap-89'  class='   watupro-question-id-262276'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>89. <\/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 model to predict the price of a student\u2019s artwork depending on the following variables: the student\u2019s length of education, degree type, and art form. <br \/>\r<br>You start by creating a linear regression model. <br \/>\r<br>You need to evaluate the linear regression model. <br \/>\r<br>Solution: Use the following metrics: Mean Absolute Error, Root Mean Absolute Error, Relative Absolute Error, Relative Squared Error, and the Coefficient of Determination. <br \/>\r<br>Does the solution meet the goal?<\/div><input type='hidden' name='question_id[]' id='qID_89' value='262276' \/><input type='hidden' id='answerType262276' 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-262276[]' id='answer-id-1033888' class='answer   answerof-262276 ' value='1033888'   \/><label for='answer-id-1033888' id='answer-label-1033888' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262276[]' id='answer-id-1033889' class='answer   answerof-262276 ' value='1033889'   \/><label for='answer-id-1033889' id='answer-label-1033889' class=' answer'><span>No<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-90' style=';'><div id='questionWrap-90'  class='   watupro-question-id-262277'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>90. <\/span>HOTSPOT <br \/>\r<br>You are developing code to analyse a dataset that includes age information for a large group of diabetes patients. You create an Azure Machine Learning workspace and install all required libraries. You set the privacy budget to 1.0). <br \/>\r<br>You must analyze the dataset and preserve data privacy. The code must run twice before the privacy budget is depleted. <br \/>\r<br>You need to complete the code. <br \/>\r<br>Which values should you use? To answer, select the appropriate options m the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=408 height=225 id=\"\u56fe\u7247 405\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image133.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_90' value='262277' \/><input type='hidden' id='answerType262277' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262277[]' id='textarea_q_262277' 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-91' style=';'><div id='questionWrap-91'  class='   watupro-question-id-262278'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>91. <\/span>CORRECT TEXT <br \/>\r<br>You train classification and regression models by using automated machine learning. <br \/>\r<br>You must evaluate automated machine learning experiment results. The results include how a classification model is making systematic errors in its predictions and the relationship between the target feature and the regression model's predictions. You must use charts generated by automated machine learning. <br \/>\r<br>You need to choose a chart type for each model type. <br \/>\r<br>Which chart types should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=393 height=109 id=\"\u56fe\u7247 540\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image135.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_91' value='262278' \/><input type='hidden' id='answerType262278' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262278[]' id='textarea_q_262278' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-92' style=';'><div id='questionWrap-92'  class='   watupro-question-id-262279'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>92. <\/span>You create a pipeline in designer to train a model that predicts automobile prices. <br \/>\r<br>Because of non-linear relationships in the data, the pipeline calculates the natural log (Ln) of the prices in the training data, trains a model to predict this natural log of price value, and then calculates the exponential of the scored label to get the predicted price. <br \/>\r<br>The training pipeline is shown in the exhibit. (Click the Training pipeline tab.) <br \/>\r<br><br \/>\r<br>Training pipeline <br \/>\r<br><br><img decoding=\"async\" width=650 height=614 id=\"\u56fe\u7247 319\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image137.jpg\"><br><br \/>\r<br>You create a real-time inference pipeline from the training pipeline, as shown in the exhibit. (Click the Real-time pipeline tab.) <br \/>\r<br><br \/>\r<br>Real-time pipeline <br \/>\r<br><br><img decoding=\"async\" width=650 height=459 id=\"\u56fe\u7247 320\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image138.jpg\"><br><br \/>\r<br>You need to modify the inference pipeline to ensure that the web service returns the exponential of the scored label as the predicted automobile price and that client applications are not required to include a price value in the input values. <br \/>\r<br>Which three modifications must you make to the inference pipeline? 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_92' value='262279' \/><input type='hidden' id='answerType262279' 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-262279[]' id='answer-id-1033892' class='answer   answerof-262279 ' value='1033892'   \/><label for='answer-id-1033892' id='answer-label-1033892' class=' answer'><span>Connect the output of the Apply SQL Transformation to the Web Service Output module.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-262279[]' id='answer-id-1033893' class='answer   answerof-262279 ' value='1033893'   \/><label for='answer-id-1033893' id='answer-label-1033893' class=' answer'><span>Replace the Web Service Input module with a data input that does not include the price column.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-262279[]' id='answer-id-1033894' class='answer   answerof-262279 ' value='1033894'   \/><label for='answer-id-1033894' id='answer-label-1033894' class=' answer'><span>Add a Select Columns module before the Score Model module to select all columns other than price.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-262279[]' id='answer-id-1033895' class='answer   answerof-262279 ' value='1033895'   \/><label for='answer-id-1033895' id='answer-label-1033895' class=' answer'><span>Replace the training dataset module with a data input that does not include the price column.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-262279[]' id='answer-id-1033896' class='answer   answerof-262279 ' value='1033896'   \/><label for='answer-id-1033896' id='answer-label-1033896' class=' answer'><span>Remove the Apply Math Operation module that replaces price with its natural log from the data flow.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-262279[]' id='answer-id-1033897' class='answer   answerof-262279 ' value='1033897'   \/><label for='answer-id-1033897' id='answer-label-1033897' class=' answer'><span>Remove the Apply SQL Transformation module from the data flow.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-93' style=';'><div id='questionWrap-93'  class='   watupro-question-id-262280'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>93. <\/span>HOTSPOT <br \/>\r<br>You create an Azure Machine Learning dataset. You use the Azure Machine Learning designer to transform the dataset by using an Execute Python Script component and custom code. <br \/>\r<br>You must upload the script and associated libraries as a script bundle. <br \/>\r<br>You need to configure the Execute Python Script component. <br \/>\r<br>Which configurations should you use? To answer, select the appropriate options in the answer area. NOTE Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=493 height=272 id=\"\u56fe\u7247 2565\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image139.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_93' value='262280' \/><input type='hidden' id='answerType262280' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262280[]' id='textarea_q_262280' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-94' style=';'><div id='questionWrap-94'  class='   watupro-question-id-262281'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>94. <\/span>You are performing a filter based feature selection for a dataset 10 build a multi class <br \/>\r<br>classifies by using Azure Machine Learning Studio. <br \/>\r<br>The dataset contains categorical features that are highly correlated to the output label column. <br \/>\r<br>You need to select the appropriate feature scoring statistical method to identify the key predictors. <br \/>\r<br>Which method should you use?<\/div><input type='hidden' name='question_id[]' id='qID_94' value='262281' \/><input type='hidden' id='answerType262281' 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-262281[]' id='answer-id-1033899' class='answer   answerof-262281 ' value='1033899'   \/><label for='answer-id-1033899' id='answer-label-1033899' class=' answer'><span>Chi-squared<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262281[]' id='answer-id-1033900' class='answer   answerof-262281 ' value='1033900'   \/><label for='answer-id-1033900' id='answer-label-1033900' class=' answer'><span>Spearman correlation<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262281[]' id='answer-id-1033901' class='answer   answerof-262281 ' value='1033901'   \/><label for='answer-id-1033901' id='answer-label-1033901' class=' answer'><span>Kendall correlation<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262281[]' id='answer-id-1033902' class='answer   answerof-262281 ' value='1033902'   \/><label for='answer-id-1033902' id='answer-label-1033902' class=' answer'><span>Person correlation<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-95' style=';'><div id='questionWrap-95'  class='   watupro-question-id-262282'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>95. <\/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 <br \/>\r<br>question sets might have more than one correct solution, while others might not have a correct solution. <br \/>\r<br>After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. <br \/>\r<br>You are analyzing a numerical dataset which contains missing values in several columns. <br \/>\r<br>You must clean the missing values using an appropriate operation without affecting the dimensionality of the feature set. <br \/>\r<br>You need to analyze a full dataset to include all values. <br \/>\r<br>Solution: Remove the entire column that contains the missing data point. <br \/>\r<br>Does the solution meet the goal?<\/div><input type='hidden' name='question_id[]' id='qID_95' value='262282' \/><input type='hidden' id='answerType262282' 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-262282[]' id='answer-id-1033903' class='answer   answerof-262282 ' value='1033903'   \/><label for='answer-id-1033903' id='answer-label-1033903' class=' answer'><span>Yes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-262282[]' id='answer-id-1033904' class='answer   answerof-262282 ' value='1033904'   \/><label for='answer-id-1033904' id='answer-label-1033904' class=' answer'><span>No<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-96' style=';'><div id='questionWrap-96'  class='   watupro-question-id-262283'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>96. <\/span>CORRECT TEXT <br \/>\r<br>You create an Azure Machine Learning dataset containing automobile price data. The dataset includes 10.000 rows and 10 columns. You use the Azure Machine Learning designer to transform the dataset by using an Execute Python Script component and custom code. <br \/>\r<br>The code must combine three columns to create a new column. <br \/>\r<br>You need to configure the code function. <br \/>\r<br>Which configurations should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. <br \/>\r<br><br><img decoding=\"async\" width=379 height=92 id=\"\u56fe\u7247 456\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2023\/05\/image141.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_96' value='262283' \/><input type='hidden' id='answerType262283' value='textarea'><!-- end question-content--><\/div><div class='question-choices '><p><textarea name='answer-262283[]' id='textarea_q_262283' class='watupro-textarea-medium' rows='5' cols='80'><\/textarea>\n<\/p><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div style='display:none' id='question-97'>\n\t<div class='question-content'>\n\t\t<img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/plugins\/watupro\/img\/loading.gif\" width=\"16\" height=\"16\" alt=\"Loading...\" title=\"Loading...\" \/>&nbsp;Loading...\t<\/div>\n<\/div>\n\n<br \/>\n\t\n\t\t\t<div class=\"watupro_buttons flex \" id=\"watuPROButtons7186\" >\n\t\t  <div id=\"prev-question\" style=\"display:none;\"><input type=\"button\" value=\"&lt; 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