{"id":64897,"date":"2023-10-07T02:44:49","date_gmt":"2023-10-07T02:44:49","guid":{"rendered":"https:\/\/www.dumpsbase.com\/freedumps\/?p=64897"},"modified":"2023-10-07T02:44:54","modified_gmt":"2023-10-07T02:44:54","slug":"aws-certified-machine-learning-specialty-mls-c01-exam-dumps-great-solution-to-make-preparation","status":"publish","type":"post","link":"https:\/\/www.dumpsbase.com\/freedumps\/aws-certified-machine-learning-specialty-mls-c01-exam-dumps-great-solution-to-make-preparation.html","title":{"rendered":"AWS Certified Machine Learning &#8211; Specialty MLS-C01 Exam Dumps &#8211; Great Solution to Make Preparation"},"content":{"rendered":"\n<p>In today&#8217;s digital era, organizations are increasingly turning to cloud initiatives to streamline their operations and stay ahead of the competition. One critical aspect of implementing cloud solutions is having the right talent with the necessary skills. The AWS Certified Machine Learning &#8211; Specialty credential plays a vital role in helping organizations identify and develop individuals with the expertise required for cloud-based machine learning projects.<\/p>\n<p>Preparing for the MLS-C01 exam can be a challenging task, considering the vast amount of knowledge and skills required. However, with the help of MLS-C01 exam dumps from DumpsBase, you can streamline your preparation process and increase your chances of success. These exam dumps provide real AWS Certified Machine Learning &#8211; Specialty MLS-C01 exam questions and answers that closely resemble the actual exam, allowing you to familiarize yourself with the format and content. Start your journey towards becoming an AWS Certified Machine Learning &#8211; Specialty professional today!<\/p>\n<h2>DumpsBase advocates <em><span style=\"background-color: #00ffff;\">MLS-C01 free demo<\/span><\/em>, enabling a comprehensive evaluation of MLS-C01 dumps:<\/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=\"submittingExam4721\" 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-4721\"><\/div>\n\n<form action=\"\" method=\"post\" class=\"quiz-form\" id=\"quiz-4721\"  enctype=\"multipart\/form-data\" >\n<div class='watu-question ' id='question-1' style=';'><div id='questionWrap-1'  class='   watupro-question-id-150767'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>1. <\/span>A large mobile network operating company is building a machine learning model to predict customers who are likely to unsubscribe from the service. The company plans to offer an incentive for these customers as the cost of churn is far greater than the cost of the incentive. <br \/>\r<br>The model produces the following confusion matrix after evaluating on a test dataset of 100 customers: <br \/>\r<br><br><img decoding=\"async\" width=610 height=106 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2020\/10\/image002-25.jpg\" v:shapes=\"_x0000_i1025\"><br><br \/>\r<br>Based on the model evaluation results, why is this a viable model for production?<\/div><input type='hidden' name='question_id[]' id='qID_1' value='150767' \/><input type='hidden' id='answerType150767' 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-150767[]' id='answer-id-613065' class='answer   answerof-150767 ' value='613065'   \/><label for='answer-id-613065' id='answer-label-613065' class=' answer'><span>The model is 86% accurate and the cost incurred by the company as a result of false negatives is less than the false positives.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150767[]' id='answer-id-613066' class='answer   answerof-150767 ' value='613066'   \/><label for='answer-id-613066' id='answer-label-613066' class=' answer'><span>The precision of the model is 86%, which is less than the accuracy of the model.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150767[]' id='answer-id-613067' class='answer   answerof-150767 ' value='613067'   \/><label for='answer-id-613067' id='answer-label-613067' class=' answer'><span>The model is 86% accurate and the cost incurred by the company as a result of false positives is less than the false negatives.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150767[]' id='answer-id-613068' class='answer   answerof-150767 ' value='613068'   \/><label for='answer-id-613068' id='answer-label-613068' class=' answer'><span>The precision of the model is 86%, which is greater than the accuracy of the model.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-2' style=';'><div id='questionWrap-2'  class='   watupro-question-id-150768'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>2. <\/span>A Machine Learning Specialist is designing a system for improving sales for a company. The objective is to use the large amount of information the company has on users\u2019 behavior and product preferences to predict which products users would like based on the users\u2019 similarity to other users. <br \/>\r<br>What should the Specialist do to meet this objective?<\/div><input type='hidden' name='question_id[]' id='qID_2' value='150768' \/><input type='hidden' id='answerType150768' 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-150768[]' id='answer-id-613069' class='answer   answerof-150768 ' value='613069'   \/><label for='answer-id-613069' id='answer-label-613069' class=' answer'><span>Build a content-based filtering recommendation engine with Apache Spark ML on Amazon EMR<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150768[]' id='answer-id-613070' class='answer   answerof-150768 ' value='613070'   \/><label for='answer-id-613070' id='answer-label-613070' class=' answer'><span>Build a collaborative filtering recommendation engine with Apache Spark ML on Amazon EM<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150768[]' id='answer-id-613071' class='answer   answerof-150768 ' value='613071'   \/><label for='answer-id-613071' id='answer-label-613071' class=' answer'><span>Build a model-based filtering recommendation engine with Apache Spark ML on Amazon EMR<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150768[]' id='answer-id-613072' class='answer   answerof-150768 ' value='613072'   \/><label for='answer-id-613072' id='answer-label-613072' class=' answer'><span>Build a combinative filtering recommendation engine with Apache Spark ML on Amazon EMR<\/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-150769'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>3. <\/span>A Mobile Network Operator is building an analytics platform to analyze and optimize a company's operations using Amazon Athena and Amazon S3. <br \/>\r<br>The source systems send data in .CSV format in real time. The Data Engineering team wants to transform the data to the Apache Parquet format before storing it on Amazon S3. <br \/>\r<br>Which solution takes the LEAST effort to implement?<\/div><input type='hidden' name='question_id[]' id='qID_3' value='150769' \/><input type='hidden' id='answerType150769' 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-150769[]' id='answer-id-613073' class='answer   answerof-150769 ' value='613073'   \/><label for='answer-id-613073' id='answer-label-613073' class=' answer'><span>Ingest .CSV data using Apache Kafka Streams on Amazon EC2 instances and use Kafka Connect S3 to serialize data as Parquet<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150769[]' id='answer-id-613074' class='answer   answerof-150769 ' value='613074'   \/><label for='answer-id-613074' id='answer-label-613074' class=' answer'><span>Ingest .CSV data from Amazon Kinesis Data Streams and use Amazon Glue to convert data into Parquet.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150769[]' id='answer-id-613075' class='answer   answerof-150769 ' value='613075'   \/><label for='answer-id-613075' id='answer-label-613075' class=' answer'><span>Ingest .CSV data using Apache Spark Structured Streaming in an Amazon EMR cluster and use Apache Spark to convert data into Parquet.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150769[]' id='answer-id-613076' class='answer   answerof-150769 ' value='613076'   \/><label for='answer-id-613076' id='answer-label-613076' class=' answer'><span>Ingest .CSV data from Amazon Kinesis Data Streams and use Amazon Kinesis Data Firehose to convert data into Parquet.<\/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-150770'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>4. <\/span>A city wants to monitor its air quality to address the consequences of air pollution. A Machine Learning Specialist needs to forecast the air quality in parts per million of contaminates for the next 2 days in the city. As this is a prototype, only daily data from the last year is available. <br \/>\r<br>Which model is MOST likely to provide the best results in Amazon SageMaker?<\/div><input type='hidden' name='question_id[]' id='qID_4' value='150770' \/><input type='hidden' id='answerType150770' 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-150770[]' id='answer-id-613077' class='answer   answerof-150770 ' value='613077'   \/><label for='answer-id-613077' id='answer-label-613077' class=' answer'><span>Use the Amazon SageMaker k-Nearest-Neighbors (kNN) algorithm on the single time series consisting of the full year of data with a predictor_typeof regressor.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150770[]' id='answer-id-613078' class='answer   answerof-150770 ' value='613078'   \/><label for='answer-id-613078' id='answer-label-613078' class=' answer'><span>Use Amazon SageMaker Random Cut Forest (RCF) on the single time series consisting of the full year of data.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150770[]' id='answer-id-613079' class='answer   answerof-150770 ' value='613079'   \/><label for='answer-id-613079' id='answer-label-613079' class=' answer'><span>Use the Amazon SageMaker Linear Learner algorithm on the single time series consisting of the full year of data with a predictor_typeof regressor.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150770[]' id='answer-id-613080' class='answer   answerof-150770 ' value='613080'   \/><label for='answer-id-613080' id='answer-label-613080' class=' answer'><span>Use the Amazon SageMaker Linear Learner algorithm on the single time series consisting of the full year of data with a predictor_typeof classifier.<\/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-150771'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>5. <\/span>A Data Engineer needs to build a model using a dataset containing customer credit card information <br \/>\r<br>How can the Data Engineer ensure the data remains encrypted and the credit card information is secure?<\/div><input type='hidden' name='question_id[]' id='qID_5' value='150771' \/><input type='hidden' id='answerType150771' 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-150771[]' id='answer-id-613081' class='answer   answerof-150771 ' value='613081'   \/><label for='answer-id-613081' id='answer-label-613081' class=' answer'><span>Use a custom encryption algorithm to encrypt the data and store the data on an Amazon SageMaker instance in a VP<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150771[]' id='answer-id-613082' class='answer   answerof-150771 ' value='613082'   \/><label for='answer-id-613082' id='answer-label-613082' class=' answer'><span>Use the SageMaker DeepAR algorithm to randomize the credit card numbers.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150771[]' id='answer-id-613083' class='answer   answerof-150771 ' value='613083'   \/><label for='answer-id-613083' id='answer-label-613083' class=' answer'><span>Use an IAM policy to encrypt the data on the Amazon S3 bucket and Amazon Kinesis to automatically discard credit card numbers and insert fake credit card numbers.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150771[]' id='answer-id-613084' class='answer   answerof-150771 ' value='613084'   \/><label for='answer-id-613084' id='answer-label-613084' class=' answer'><span>Use an Amazon SageMaker launch configuration to encrypt the data once it is copied to the SageMaker instance in a VP<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150771[]' id='answer-id-613085' class='answer   answerof-150771 ' value='613085'   \/><label for='answer-id-613085' id='answer-label-613085' class=' answer'><span>Use the SageMaker principal component analysis (PCA) algorithm to reduce the length of the credit card numbers.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150771[]' id='answer-id-613086' class='answer   answerof-150771 ' value='613086'   \/><label for='answer-id-613086' id='answer-label-613086' class=' answer'><span>Use AWS KMS to encrypt the data on Amazon S3 and Amazon SageMaker, and redact the credit card numbers from the customer data with AWS Glue.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-6' style=';'><div id='questionWrap-6'  class='   watupro-question-id-150772'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>6. <\/span>A Machine Learning Specialist is using an Amazon SageMaker notebook instance in a private subnet of a corporate VPC. The ML Specialist has important data stored on the Amazon SageMaker notebook instance's Amazon EBS volume, and needs to take a snapshot of that EBS volume. However, the ML Specialist cannot find the Amazon SageMaker notebook instance\u2019s EBS volume or Amazon EC2 instance within the VPC. <br \/>\r<br>Why is the ML Specialist not seeing the instance visible in the VPC?<\/div><input type='hidden' name='question_id[]' id='qID_6' value='150772' \/><input type='hidden' id='answerType150772' 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-150772[]' id='answer-id-613087' class='answer   answerof-150772 ' value='613087'   \/><label for='answer-id-613087' id='answer-label-613087' class=' answer'><span>Amazon SageMaker notebook instances are based on the EC2 instances within the customer account, but they run outside of VPCs.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150772[]' id='answer-id-613088' class='answer   answerof-150772 ' value='613088'   \/><label for='answer-id-613088' id='answer-label-613088' class=' answer'><span>Amazon SageMaker notebook instances are based on the Amazon ECS service within customer accounts.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150772[]' id='answer-id-613089' class='answer   answerof-150772 ' value='613089'   \/><label for='answer-id-613089' id='answer-label-613089' class=' answer'><span>Amazon SageMaker notebook instances are based on EC2 instances running within AWS service accounts.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150772[]' id='answer-id-613090' class='answer   answerof-150772 ' value='613090'   \/><label for='answer-id-613090' id='answer-label-613090' class=' answer'><span>Amazon SageMaker notebook instances are based on AWS ECS instances running within AWS service accounts.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-7' style=';'><div id='questionWrap-7'  class='   watupro-question-id-150773'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>7. <\/span>A Machine Learning Specialist is building a model that will perform time series forecasting using Amazon SageMaker. The Specialist has finished training the model and is now planning to perform load testing on the endpoint so they can configure Auto Scaling for the model variant. <br \/>\r<br>Which approach will allow the Specialist to review the latency, memory utilization, and CPU utilization during the load test?<\/div><input type='hidden' name='question_id[]' id='qID_7' value='150773' \/><input type='hidden' id='answerType150773' 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-150773[]' id='answer-id-613091' class='answer   answerof-150773 ' value='613091'   \/><label for='answer-id-613091' id='answer-label-613091' class=' answer'><span>Review SageMaker logs that have been written to Amazon S3 by leveraging Amazon Athena and Amazon QuickSight to visualize logs as they are being produced.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150773[]' id='answer-id-613092' class='answer   answerof-150773 ' value='613092'   \/><label for='answer-id-613092' id='answer-label-613092' class=' answer'><span>Generate an Amazon CloudWatch dashboard to create a single view for the latency, memory utilization, and CPU utilization metrics that are outputted by Amazon SageMaker.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150773[]' id='answer-id-613093' class='answer   answerof-150773 ' value='613093'   \/><label for='answer-id-613093' id='answer-label-613093' class=' answer'><span>Build custom Amazon CloudWatch Logs and then leverage Amazon ES and Kibana to query and visualize the log data as it is generated by Amazon SageMaker.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150773[]' id='answer-id-613094' class='answer   answerof-150773 ' value='613094'   \/><label for='answer-id-613094' id='answer-label-613094' class=' answer'><span>Send Amazon CloudWatch Logs that were generated by Amazon SageMaker to Amazon ES and use Kibana to query and visualize the log data<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-8' style=';'><div id='questionWrap-8'  class='   watupro-question-id-150774'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>8. <\/span>A manufacturing company has structured and unstructured data stored in an Amazon S3 bucket. A Machine Learning Specialist wants to use SQL to run queries on this data. <br \/>\r<br>Which solution requires the LEAST effort to be able to query this data?<\/div><input type='hidden' name='question_id[]' id='qID_8' value='150774' \/><input type='hidden' id='answerType150774' 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-150774[]' id='answer-id-613095' class='answer   answerof-150774 ' value='613095'   \/><label for='answer-id-613095' id='answer-label-613095' class=' answer'><span>Use AWS Data Pipeline to transform the data and Amazon RDS to run queries.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150774[]' id='answer-id-613096' class='answer   answerof-150774 ' value='613096'   \/><label for='answer-id-613096' id='answer-label-613096' class=' answer'><span>Use AWS Glue to catalogue the data and Amazon Athena to run queries.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150774[]' id='answer-id-613097' class='answer   answerof-150774 ' value='613097'   \/><label for='answer-id-613097' id='answer-label-613097' class=' answer'><span>Use AWS Batch to run ETL on the data and Amazon Aurora to run the queries.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150774[]' id='answer-id-613098' class='answer   answerof-150774 ' value='613098'   \/><label for='answer-id-613098' id='answer-label-613098' class=' answer'><span>Use AWS Lambda to transform the data and Amazon Kinesis Data Analytics to run queries.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-9' style=';'><div id='questionWrap-9'  class='   watupro-question-id-150775'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>9. <\/span>A Machine Learning Specialist is developing a custom video recommendation model for an application. The dataset used to train this model is very large with millions of data points and is hosted in an Amazon S3 bucket. The Specialist wants to avoid loading all of this data onto an Amazon SageMaker notebook instance because it would take hours to move and will exceed the attached 5 GB Amazon EBS volume on the notebook instance. <br \/>\r<br>Which approach allows the Specialist to use all the data to train the model?<\/div><input type='hidden' name='question_id[]' id='qID_9' value='150775' \/><input type='hidden' id='answerType150775' 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-150775[]' id='answer-id-613099' class='answer   answerof-150775 ' value='613099'   \/><label for='answer-id-613099' id='answer-label-613099' class=' answer'><span>Load a smaller subset of the data into the SageMaker notebook and train locally. Confirm that the training code is executing and the model parameters seem reasonable. Initiate a SageMaker training job using the full dataset from the S3 bucket using Pipe input mode.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150775[]' id='answer-id-613100' class='answer   answerof-150775 ' value='613100'   \/><label for='answer-id-613100' id='answer-label-613100' class=' answer'><span>Launch an Amazon EC2 instance with an AWS Deep Learning AMI and attach the S3 bucket to the instance. Train on a small amount of the data to verify the training code and hyperparameters. Go back to Amazon SageMaker and train using the full dataset<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150775[]' id='answer-id-613101' class='answer   answerof-150775 ' value='613101'   \/><label for='answer-id-613101' id='answer-label-613101' class=' answer'><span>Use AWS Glue to train a model using a small subset of the data to confirm that the data will be compatible with Amazon SageMaker. Initiate a SageMaker training job using the full dataset from the S3 bucket using Pipe input mode.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150775[]' id='answer-id-613102' class='answer   answerof-150775 ' value='613102'   \/><label for='answer-id-613102' id='answer-label-613102' class=' answer'><span>Load a smaller subset of the data into the SageMaker notebook and train locally. Confirm that the training code is executing and the model parameters seem reasonable. Launch an Amazon EC2 instance with an AWS Deep Learning AMI and attach the S3 bucket to train the full dataset.<\/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-150776'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>10. <\/span>A Machine Learning Specialist has completed a proof of concept for a company using a small data sample, and now the Specialist is ready to implement an end-to-end solution in AWS using Amazon SageMaker. The historical training data is stored in Amazon RDS. <br \/>\r<br>Which approach should the Specialist use for training a model using that data?<\/div><input type='hidden' name='question_id[]' id='qID_10' value='150776' \/><input type='hidden' id='answerType150776' 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-150776[]' id='answer-id-613103' class='answer   answerof-150776 ' value='613103'   \/><label for='answer-id-613103' id='answer-label-613103' class=' answer'><span>Write a direct connection to the SQL database within the notebook and pull data in<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150776[]' id='answer-id-613104' class='answer   answerof-150776 ' value='613104'   \/><label for='answer-id-613104' id='answer-label-613104' class=' answer'><span>Push the data from Microsoft SQL Server to Amazon S3 using an AWS Data Pipeline and provide the S3 location within the notebook.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150776[]' id='answer-id-613105' class='answer   answerof-150776 ' value='613105'   \/><label for='answer-id-613105' id='answer-label-613105' class=' answer'><span>Move the data to Amazon DynamoDB and set up a connection to DynamoDB within the notebook to pull data in.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150776[]' id='answer-id-613106' class='answer   answerof-150776 ' value='613106'   \/><label for='answer-id-613106' id='answer-label-613106' class=' answer'><span>Move the data to Amazon ElastiCache using AWS DMS and set up a connection within the notebook to pull data in for fast access.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-11' style=';'><div id='questionWrap-11'  class='   watupro-question-id-150777'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>11. <\/span>A Machine Learning Specialist receives customer data for an online shopping website. The data includes demographics, past visits, and locality information. The Specialist must develop a machine learning approach to identify the customer shopping patterns, preferences, and trends to enhance the website-for better service and smart recommendations. <br \/>\r<br>Which solution should the Specialist recommend?<\/div><input type='hidden' name='question_id[]' id='qID_11' value='150777' \/><input type='hidden' id='answerType150777' 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-150777[]' id='answer-id-613107' class='answer   answerof-150777 ' value='613107'   \/><label for='answer-id-613107' id='answer-label-613107' class=' answer'><span>Latent Dirichlet Allocation (LDA) for the given collection of discrete data to identify patterns in the customer database.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150777[]' id='answer-id-613108' class='answer   answerof-150777 ' value='613108'   \/><label for='answer-id-613108' id='answer-label-613108' class=' answer'><span>A neural network with a minimum of three layers and random initial weights to identify patterns in the customer database.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150777[]' id='answer-id-613109' class='answer   answerof-150777 ' value='613109'   \/><label for='answer-id-613109' id='answer-label-613109' class=' answer'><span>Collaborative filtering based on user interactions and correlations to identify patterns in the customer database.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150777[]' id='answer-id-613110' class='answer   answerof-150777 ' value='613110'   \/><label for='answer-id-613110' id='answer-label-613110' class=' answer'><span>Random Cut Forest (RCF) over random subsamples to identify patterns in the customer database.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-12' style=';'><div id='questionWrap-12'  class='   watupro-question-id-150778'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>12. <\/span>A Machine Learning Specialist is working with a large company to leverage machine learning within its products. The company wants to group its customers into categories based on which customers will and will not churn within the next 6 months. The company has labeled the data available to the Specialist. <br \/>\r<br>Which machine learning model type should the Specialist use to accomplish this task?<\/div><input type='hidden' name='question_id[]' id='qID_12' value='150778' \/><input type='hidden' id='answerType150778' 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-150778[]' id='answer-id-613111' class='answer   answerof-150778 ' value='613111'   \/><label for='answer-id-613111' id='answer-label-613111' class=' answer'><span>Linear regression<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150778[]' id='answer-id-613112' class='answer   answerof-150778 ' value='613112'   \/><label for='answer-id-613112' id='answer-label-613112' class=' answer'><span>Classification<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150778[]' id='answer-id-613113' class='answer   answerof-150778 ' value='613113'   \/><label for='answer-id-613113' id='answer-label-613113' class=' answer'><span>Clustering<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150778[]' id='answer-id-613114' class='answer   answerof-150778 ' value='613114'   \/><label for='answer-id-613114' id='answer-label-613114' class=' answer'><span>Reinforcement learning<\/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-150779'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>13. <\/span>The displayed graph is from a forecasting model for testing a time series. <br \/>\r<br><br><img decoding=\"async\" width=650 height=328 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2020\/10\/image004-21.jpg\" v:shapes=\"_x0000_i1026\"><br><br \/>\r<br>Considering the graph only, which conclusion should a Machine Learning Specialist make about the behavior of the model?<\/div><input type='hidden' name='question_id[]' id='qID_13' value='150779' \/><input type='hidden' id='answerType150779' 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-150779[]' id='answer-id-613115' class='answer   answerof-150779 ' value='613115'   \/><label for='answer-id-613115' id='answer-label-613115' class=' answer'><span>The model predicts both the trend and the seasonality well<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150779[]' id='answer-id-613116' class='answer   answerof-150779 ' value='613116'   \/><label for='answer-id-613116' id='answer-label-613116' class=' answer'><span>The model predicts the trend well, but not the seasonality.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150779[]' id='answer-id-613117' class='answer   answerof-150779 ' value='613117'   \/><label for='answer-id-613117' id='answer-label-613117' class=' answer'><span>The model predicts the seasonality well, but not the trend.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150779[]' id='answer-id-613118' class='answer   answerof-150779 ' value='613118'   \/><label for='answer-id-613118' id='answer-label-613118' class=' answer'><span>The model does not predict the trend or the seasonality well.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-14' style=';'><div id='questionWrap-14'  class='   watupro-question-id-150780'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>14. <\/span>A company wants to classify user behavior as either fraudulent or normal. Based on internal research, a Machine Learning Specialist would like to build a binary classifier based on two features: age of account and transaction month. The class distribution for these features is illustrated in the figure provided. <br \/>\r<br><br><img decoding=\"async\" width=649 height=487 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2020\/10\/image006-16.jpg\" v:shapes=\"_x0000_i1027\"><br><br \/>\r<br>Based on this information, which model would have the HIGHEST accuracy?<\/div><input type='hidden' name='question_id[]' id='qID_14' value='150780' \/><input type='hidden' id='answerType150780' 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-150780[]' id='answer-id-613119' class='answer   answerof-150780 ' value='613119'   \/><label for='answer-id-613119' id='answer-label-613119' class=' answer'><span>Long short-term memory (LSTM) model with scaled exponential linear unit (SELU)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150780[]' id='answer-id-613120' class='answer   answerof-150780 ' value='613120'   \/><label for='answer-id-613120' id='answer-label-613120' class=' answer'><span>Logistic regression<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150780[]' id='answer-id-613121' class='answer   answerof-150780 ' value='613121'   \/><label for='answer-id-613121' id='answer-label-613121' class=' answer'><span>Support vector machine (SVM) with non-linear kernel<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150780[]' id='answer-id-613122' class='answer   answerof-150780 ' value='613122'   \/><label for='answer-id-613122' id='answer-label-613122' class=' answer'><span>Single perceptron with tanh activation function<\/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-150781'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>15. <\/span>A Machine Learning Specialist at a company sensitive to security is preparing a dataset for model training. The dataset is stored in Amazon S3 and contains Personally Identifiable Information (PII). <br \/>\r<br>The dataset: <br \/>\r<br>- Must be accessible from a VPC only. <br \/>\r<br>- Must not traverse the public internet. <br \/>\r<br>How can these requirements be satisfied?<\/div><input type='hidden' name='question_id[]' id='qID_15' value='150781' \/><input type='hidden' id='answerType150781' 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-150781[]' id='answer-id-613123' class='answer   answerof-150781 ' value='613123'   \/><label for='answer-id-613123' id='answer-label-613123' class=' answer'><span>Create a VPC endpoint and apply a bucket access policy that restricts access to the given VPC endpoint and the VP<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150781[]' id='answer-id-613124' class='answer   answerof-150781 ' value='613124'   \/><label for='answer-id-613124' id='answer-label-613124' class=' answer'><span>Create a VPC endpoint and apply a bucket access policy that allows access from the given VPC endpoint and an Amazon EC2 instance.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150781[]' id='answer-id-613125' class='answer   answerof-150781 ' value='613125'   \/><label for='answer-id-613125' id='answer-label-613125' class=' answer'><span>Create a VPC endpoint and use Network Access Control Lists (NACLs) to allow traffic between only the given VPC endpoint and an Amazon EC2 instance.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150781[]' id='answer-id-613126' class='answer   answerof-150781 ' value='613126'   \/><label for='answer-id-613126' id='answer-label-613126' class=' answer'><span>Create a VPC endpoint and use security groups to restrict access to the given VPC endpoint and an Amazon EC2 instance<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-16' style=';'><div id='questionWrap-16'  class='   watupro-question-id-150782'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>16. <\/span>During mini-batch training of a neural network for a classification problem, a Data Scientist notices that training accuracy oscillates. <br \/>\r<br>What is the MOST likely cause of this issue?<\/div><input type='hidden' name='question_id[]' id='qID_16' value='150782' \/><input type='hidden' id='answerType150782' 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-150782[]' id='answer-id-613127' class='answer   answerof-150782 ' value='613127'   \/><label for='answer-id-613127' id='answer-label-613127' class=' answer'><span>The class distribution in the dataset is imbalanced.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150782[]' id='answer-id-613128' class='answer   answerof-150782 ' value='613128'   \/><label for='answer-id-613128' id='answer-label-613128' class=' answer'><span>Dataset shuffling is disabled.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150782[]' id='answer-id-613129' class='answer   answerof-150782 ' value='613129'   \/><label for='answer-id-613129' id='answer-label-613129' class=' answer'><span>The batch size is too big.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150782[]' id='answer-id-613130' class='answer   answerof-150782 ' value='613130'   \/><label for='answer-id-613130' id='answer-label-613130' class=' answer'><span>The learning rate is very high.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-17' style=';'><div id='questionWrap-17'  class='   watupro-question-id-150783'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>17. <\/span>An employee found a video clip with audio on a company's social media feed. The language used in the video is Spanish. English is the employee's first language, and they do not understand Spanish. The employee wants to do a sentiment analysis. <br \/>\r<br>What combination of services is the MOST efficient to accomplish the task?<\/div><input type='hidden' name='question_id[]' id='qID_17' value='150783' \/><input type='hidden' id='answerType150783' 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-150783[]' id='answer-id-613131' class='answer   answerof-150783 ' value='613131'   \/><label for='answer-id-613131' id='answer-label-613131' class=' answer'><span>Amazon Transcribe, Amazon Translate, and Amazon Comprehend<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150783[]' id='answer-id-613132' class='answer   answerof-150783 ' value='613132'   \/><label for='answer-id-613132' id='answer-label-613132' class=' answer'><span>Amazon Transcribe, Amazon Comprehend, and Amazon SageMaker seq2seq<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150783[]' id='answer-id-613133' class='answer   answerof-150783 ' value='613133'   \/><label for='answer-id-613133' id='answer-label-613133' class=' answer'><span>Amazon Transcribe, Amazon Translate, and Amazon SageMaker Neural Topic Model (NTM)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150783[]' id='answer-id-613134' class='answer   answerof-150783 ' value='613134'   \/><label for='answer-id-613134' id='answer-label-613134' class=' answer'><span>Amazon Transcribe, Amazon Translate and Amazon SageMaker BlazingText<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-18' style=';'><div id='questionWrap-18'  class='   watupro-question-id-150784'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>18. <\/span>A Machine Learning Specialist is packaging a custom ResNet model into a Docker container so the company can leverage Amazon SageMaker for training. The Specialist is using Amazon EC2 P3 instances to train the model and needs to properly configure the Docker container to leverage the NVIDIA GPUs. <br \/>\r<br>What does the Specialist need to do?<\/div><input type='hidden' name='question_id[]' id='qID_18' value='150784' \/><input type='hidden' id='answerType150784' 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-150784[]' id='answer-id-613135' class='answer   answerof-150784 ' value='613135'   \/><label for='answer-id-613135' id='answer-label-613135' class=' answer'><span>Bundle the NVIDIA drivers with the Docker image.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150784[]' id='answer-id-613136' class='answer   answerof-150784 ' value='613136'   \/><label for='answer-id-613136' id='answer-label-613136' class=' answer'><span>Build the Docker container to be NVIDIA-Docker compatible.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150784[]' id='answer-id-613137' class='answer   answerof-150784 ' value='613137'   \/><label for='answer-id-613137' id='answer-label-613137' class=' answer'><span>Organize the Docker container's file structure to execute on GPU instances.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150784[]' id='answer-id-613138' class='answer   answerof-150784 ' value='613138'   \/><label for='answer-id-613138' id='answer-label-613138' class=' answer'><span>Set the GPU flag in the Amazon SageMaker CreateTrainingJob request body.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-19' style=';'><div id='questionWrap-19'  class='   watupro-question-id-150785'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>19. <\/span>A Machine Learning Specialist is building a logistic regression model that will predict whether or not a person will order a pizza. The Specialist is trying to build the optimal model with an ideal classification threshold. <br \/>\r<br>What model evaluation technique should the Specialist use to understand how different classification thresholds will impact the model's performance?<\/div><input type='hidden' name='question_id[]' id='qID_19' value='150785' \/><input type='hidden' id='answerType150785' 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-150785[]' id='answer-id-613139' class='answer   answerof-150785 ' value='613139'   \/><label for='answer-id-613139' id='answer-label-613139' class=' answer'><span>Receiver operating characteristic (ROC) curve<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150785[]' id='answer-id-613140' class='answer   answerof-150785 ' value='613140'   \/><label for='answer-id-613140' id='answer-label-613140' class=' answer'><span>Misclassification rate<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150785[]' id='answer-id-613141' class='answer   answerof-150785 ' value='613141'   \/><label for='answer-id-613141' id='answer-label-613141' class=' answer'><span>Root Mean Square Error (RMSE)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150785[]' id='answer-id-613142' class='answer   answerof-150785 ' value='613142'   \/><label for='answer-id-613142' id='answer-label-613142' class=' answer'><span>L1 norm<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-20' style=';'><div id='questionWrap-20'  class='   watupro-question-id-150786'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>20. <\/span>An interactive online dictionary wants to add a widget that displays words used in similar contexts. A Machine Learning Specialist is asked to provide word features for the downstream nearest neighbor model powering the widget. <br \/>\r<br>What should the Specialist do to meet these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_20' value='150786' \/><input type='hidden' id='answerType150786' 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-150786[]' id='answer-id-613143' class='answer   answerof-150786 ' value='613143'   \/><label for='answer-id-613143' id='answer-label-613143' class=' answer'><span>Create one-hot word encoding vectors.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150786[]' id='answer-id-613144' class='answer   answerof-150786 ' value='613144'   \/><label for='answer-id-613144' id='answer-label-613144' class=' answer'><span>Produce a set of synonyms for every word using Amazon Mechanical Turk.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150786[]' id='answer-id-613145' class='answer   answerof-150786 ' value='613145'   \/><label for='answer-id-613145' id='answer-label-613145' class=' answer'><span>Create word embedding vectors that store edit distance with every other word.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150786[]' id='answer-id-613146' class='answer   answerof-150786 ' value='613146'   \/><label for='answer-id-613146' id='answer-label-613146' class=' answer'><span>Download word embeddings pre-trained on a large corpus.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-21' style=';'><div id='questionWrap-21'  class='   watupro-question-id-150787'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>21. <\/span>A Machine Learning Specialist is configuring Amazon SageMaker so multiple Data Scientists can access notebooks, train models, and deploy endpoints. To ensure the best operational performance, the Specialist needs to be able to track how often the Scientists are deploying models, GPU and CPU utilization on the deployed SageMaker endpoints, and all errors that are generated when an endpoint is invoked. <br \/>\r<br>Which services are integrated with Amazon SageMaker to track this information? (Choose two.)<\/div><input type='hidden' name='question_id[]' id='qID_21' value='150787' \/><input type='hidden' id='answerType150787' 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-150787[]' id='answer-id-613147' class='answer   answerof-150787 ' value='613147'   \/><label for='answer-id-613147' id='answer-label-613147' class=' answer'><span>AWS CloudTrail<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150787[]' id='answer-id-613148' class='answer   answerof-150787 ' value='613148'   \/><label for='answer-id-613148' id='answer-label-613148' class=' answer'><span>AWS Health<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150787[]' id='answer-id-613149' class='answer   answerof-150787 ' value='613149'   \/><label for='answer-id-613149' id='answer-label-613149' class=' answer'><span>AWS Trusted Advisor<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150787[]' id='answer-id-613150' class='answer   answerof-150787 ' value='613150'   \/><label for='answer-id-613150' id='answer-label-613150' class=' answer'><span>Amazon CloudWatch<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150787[]' id='answer-id-613151' class='answer   answerof-150787 ' value='613151'   \/><label for='answer-id-613151' id='answer-label-613151' class=' answer'><span>AWS Config<\/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-150788'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>22. <\/span>A retail chain has been ingesting purchasing records from its network of 20,000 stores to Amazon S3 using Amazon Kinesis Data Firehose. To support training an improved machine learning model, training records will require new but simple transformations, and some attributes will be combined. The model needs to be retrained daily. <br \/>\r<br>Given the large number of stores and the legacy data ingestion, which change will require the LEAST amount of development effort?<\/div><input type='hidden' name='question_id[]' id='qID_22' value='150788' \/><input type='hidden' id='answerType150788' 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-150788[]' id='answer-id-613152' class='answer   answerof-150788 ' value='613152'   \/><label for='answer-id-613152' id='answer-label-613152' class=' answer'><span>Require that the stores to switch to capturing their data locally on AWS Storage Gateway for loading into Amazon S3, then use AWS Glue to do the transformation.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150788[]' id='answer-id-613153' class='answer   answerof-150788 ' value='613153'   \/><label for='answer-id-613153' id='answer-label-613153' class=' answer'><span>Deploy an Amazon EMR cluster running Apache Spark with the transformation logic, and have the cluster run each day on the accumulating records in Amazon S3, outputting new\/transformed records to Amazon S3.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150788[]' id='answer-id-613154' class='answer   answerof-150788 ' value='613154'   \/><label for='answer-id-613154' id='answer-label-613154' class=' answer'><span>Spin up a fleet of Amazon EC2 instances with the transformation logic, have them transform the data records accumulating on Amazon S3, and output the transformed records to Amazon S3.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150788[]' id='answer-id-613155' class='answer   answerof-150788 ' value='613155'   \/><label for='answer-id-613155' id='answer-label-613155' class=' answer'><span>Insert an Amazon Kinesis Data Analytics stream downstream of the Kinesis Data Firehose stream that transforms raw record attributes into simple transformed values using SQ<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-23' style=';'><div id='questionWrap-23'  class='   watupro-question-id-150789'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>23. <\/span>A Machine Learning Specialist is building a convolutional neural network (CNN) that will classify 10 types of animals. The Specialist has built a series of layers in a neural network that will take an input image of an animal, pass it through a series of convolutional and pooling layers, and then finally pass it through a dense and fully connected layer with 10 nodes. The Specialist would like to get an output from the neural network that is a probability distribution of how likely it is that the input image belongs to each of the 10 classes. <br \/>\r<br>Which function will produce the desired output?<\/div><input type='hidden' name='question_id[]' id='qID_23' value='150789' \/><input type='hidden' id='answerType150789' 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-150789[]' id='answer-id-613156' class='answer   answerof-150789 ' value='613156'   \/><label for='answer-id-613156' id='answer-label-613156' class=' answer'><span>Dropout<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150789[]' id='answer-id-613157' class='answer   answerof-150789 ' value='613157'   \/><label for='answer-id-613157' id='answer-label-613157' class=' answer'><span>Smooth L1 loss<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150789[]' id='answer-id-613158' class='answer   answerof-150789 ' value='613158'   \/><label for='answer-id-613158' id='answer-label-613158' class=' answer'><span>Softmax<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150789[]' id='answer-id-613159' class='answer   answerof-150789 ' value='613159'   \/><label for='answer-id-613159' id='answer-label-613159' class=' answer'><span>Rectified linear units (ReLU)<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-24' style=';'><div id='questionWrap-24'  class='   watupro-question-id-150790'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>24. <\/span>A Machine Learning Specialist trained a regression model, but the first iteration needs optimizing. The Specialist needs to understand whether the model is more frequently overestimating or underestimating the target. <br \/>\r<br>What option can the Specialist use to determine whether it is overestimating or underestimating the target value?<\/div><input type='hidden' name='question_id[]' id='qID_24' value='150790' \/><input type='hidden' id='answerType150790' 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-150790[]' id='answer-id-613160' class='answer   answerof-150790 ' value='613160'   \/><label for='answer-id-613160' id='answer-label-613160' class=' answer'><span>Root Mean Square Error (RMSE)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150790[]' id='answer-id-613161' class='answer   answerof-150790 ' value='613161'   \/><label for='answer-id-613161' id='answer-label-613161' class=' answer'><span>Residual plots<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150790[]' id='answer-id-613162' class='answer   answerof-150790 ' value='613162'   \/><label for='answer-id-613162' id='answer-label-613162' class=' answer'><span>Area under the curve<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150790[]' id='answer-id-613163' class='answer   answerof-150790 ' value='613163'   \/><label for='answer-id-613163' id='answer-label-613163' class=' answer'><span>Confusion matrix<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-25' style=';'><div id='questionWrap-25'  class='   watupro-question-id-150791'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>25. <\/span>A company wants to classify user behavior as either fraudulent or normal. Based on internal research, a Machine Learning Specialist would like to build a binary classifier based on two features: age of account and transaction month. The class distribution for these features is illustrated in the figure provided. <br \/>\r<br><br><img decoding=\"async\" width=649 height=488 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2020\/10\/image008-15.jpg\" v:shapes=\"_x0000_i1028\"><br><br \/>\r<br>Based on this information, which model would have the HIGHEST recall with respect to the fraudulent class?<\/div><input type='hidden' name='question_id[]' id='qID_25' value='150791' \/><input type='hidden' id='answerType150791' 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-150791[]' id='answer-id-613164' class='answer   answerof-150791 ' value='613164'   \/><label for='answer-id-613164' id='answer-label-613164' class=' answer'><span>Decision tree<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150791[]' id='answer-id-613165' class='answer   answerof-150791 ' value='613165'   \/><label for='answer-id-613165' id='answer-label-613165' class=' answer'><span>Linear support vector machine (SVM)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150791[]' id='answer-id-613166' class='answer   answerof-150791 ' value='613166'   \/><label for='answer-id-613166' id='answer-label-613166' class=' answer'><span>Naive Bayesian classifier<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150791[]' id='answer-id-613167' class='answer   answerof-150791 ' value='613167'   \/><label for='answer-id-613167' id='answer-label-613167' class=' answer'><span>Single Perceptron with sigmoidal activation function<\/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-150792'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>26. <\/span>A Machine Learning Specialist kicks off a hyperparameter tuning job for a tree-based ensemble model using Amazon SageMaker with Area Under the ROC Curve (AUC) as the objective metric. This workflow will eventually be deployed in a pipeline that retrains and tunes hyperparameters each night to model click-through on data that goes stale every 24 hours. <br \/>\r<br>With the goal of decreasing the amount of time it takes to train these models, and ultimately to decrease costs, the Specialist wants to reconfigure the input hyperparameter range(s). <br \/>\r<br>Which visualization will accomplish this?<\/div><input type='hidden' name='question_id[]' id='qID_26' value='150792' \/><input type='hidden' id='answerType150792' 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-150792[]' id='answer-id-613168' class='answer   answerof-150792 ' value='613168'   \/><label for='answer-id-613168' id='answer-label-613168' class=' answer'><span>A histogram showing whether the most important input feature is Gaussian.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150792[]' id='answer-id-613169' class='answer   answerof-150792 ' value='613169'   \/><label for='answer-id-613169' id='answer-label-613169' class=' answer'><span>A scatter plot with points colored by target variable that uses t-Distributed Stochastic Neighbor Embedding (t-SNE) to visualize the large number of input variables in an easier-to-read dimension.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150792[]' id='answer-id-613170' class='answer   answerof-150792 ' value='613170'   \/><label for='answer-id-613170' id='answer-label-613170' class=' answer'><span>A scatter plot showing the performance of the objective metric over each training iteration.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150792[]' id='answer-id-613171' class='answer   answerof-150792 ' value='613171'   \/><label for='answer-id-613171' id='answer-label-613171' class=' answer'><span>A scatter plot showing the correlation between maximum tree depth and the objective metric.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-27' style=';'><div id='questionWrap-27'  class='   watupro-question-id-150793'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>27. <\/span>A Machine Learning Specialist is creating a new natural language processing application that processes a dataset comprised of 1 million sentences. The aim is to then run Word2Vec to generate embeddings of the sentences and enable different types of predictions. <br \/>\r<br>Here is an example from the dataset: <br \/>\r<br>&quot;The quck BROWN FOX jumps over the lazy dog.\u201d <br \/>\r<br>Which of the following are the operations the Specialist needs to perform to correctly sanitize and prepare the data in a repeatable manner? (Choose three.)<\/div><input type='hidden' name='question_id[]' id='qID_27' value='150793' \/><input type='hidden' id='answerType150793' 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-150793[]' id='answer-id-613172' class='answer   answerof-150793 ' value='613172'   \/><label for='answer-id-613172' id='answer-label-613172' class=' answer'><span>Perform part-of-speech tagging and keep the action verb and the nouns only.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150793[]' id='answer-id-613173' class='answer   answerof-150793 ' value='613173'   \/><label for='answer-id-613173' id='answer-label-613173' class=' answer'><span>Normalize all words by making the sentence lowercase.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150793[]' id='answer-id-613174' class='answer   answerof-150793 ' value='613174'   \/><label for='answer-id-613174' id='answer-label-613174' class=' answer'><span>Remove stop words using an English stopword dictionary.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150793[]' id='answer-id-613175' class='answer   answerof-150793 ' value='613175'   \/><label for='answer-id-613175' id='answer-label-613175' class=' answer'><span>Correct the typography on &quot;quck&quot; to &quot;quick.\u201d<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150793[]' id='answer-id-613176' class='answer   answerof-150793 ' value='613176'   \/><label for='answer-id-613176' id='answer-label-613176' class=' answer'><span>One-hot encode all words in the sentence.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150793[]' id='answer-id-613177' class='answer   answerof-150793 ' value='613177'   \/><label for='answer-id-613177' id='answer-label-613177' class=' answer'><span>Tokenize the sentence into words.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-28' style=';'><div id='questionWrap-28'  class='   watupro-question-id-150794'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>28. <\/span>A company is using Amazon Polly to translate plaintext documents to speech for automated company announcements. However, company acronyms are being mispronounced in the current documents. <br \/>\r<br>How should a Machine Learning Specialist address this issue for future documents?<\/div><input type='hidden' name='question_id[]' id='qID_28' value='150794' \/><input type='hidden' id='answerType150794' 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-150794[]' id='answer-id-613178' class='answer   answerof-150794 ' value='613178'   \/><label for='answer-id-613178' id='answer-label-613178' class=' answer'><span>Convert current documents to SSML with pronunciation tags.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150794[]' id='answer-id-613179' class='answer   answerof-150794 ' value='613179'   \/><label for='answer-id-613179' id='answer-label-613179' class=' answer'><span>Create an appropriate pronunciation lexicon.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150794[]' id='answer-id-613180' class='answer   answerof-150794 ' value='613180'   \/><label for='answer-id-613180' id='answer-label-613180' class=' answer'><span>Output speech marks to guide in pronunciation.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150794[]' id='answer-id-613181' class='answer   answerof-150794 ' value='613181'   \/><label for='answer-id-613181' id='answer-label-613181' class=' answer'><span>Use Amazon Lex to preprocess the text files for pronunciation<\/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-150795'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>29. <\/span>An insurance company is developing a new device for vehicles that uses a camera to observe drivers\u2019 behavior and alert them when they appear distracted. The company created approximately 10,000 training images in a controlled environment that a Machine Learning Specialist will use to train and evaluate machine learning models. <br \/>\r<br>During the model evaluation, the Specialist notices that the training error rate diminishes faster as the number of epochs increases and the model is not accurately inferring on the unseen test images. <br \/>\r<br>Which of the following should be used to resolve this issue? (Choose two.)<\/div><input type='hidden' name='question_id[]' id='qID_29' value='150795' \/><input type='hidden' id='answerType150795' 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-150795[]' id='answer-id-613182' class='answer   answerof-150795 ' value='613182'   \/><label for='answer-id-613182' id='answer-label-613182' class=' answer'><span>Add vanishing gradient to the model.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150795[]' id='answer-id-613183' class='answer   answerof-150795 ' value='613183'   \/><label for='answer-id-613183' id='answer-label-613183' class=' answer'><span>Perform data augmentation on the training data.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150795[]' id='answer-id-613184' class='answer   answerof-150795 ' value='613184'   \/><label for='answer-id-613184' id='answer-label-613184' class=' answer'><span>Make the neural network architecture complex.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150795[]' id='answer-id-613185' class='answer   answerof-150795 ' value='613185'   \/><label for='answer-id-613185' id='answer-label-613185' class=' answer'><span>Use gradient checking in the model.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150795[]' id='answer-id-613186' class='answer   answerof-150795 ' value='613186'   \/><label for='answer-id-613186' id='answer-label-613186' class=' answer'><span>Add L2 regularization to the model.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-30' style=';'><div id='questionWrap-30'  class='   watupro-question-id-150796'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>30. <\/span>When submitting Amazon SageMaker training jobs using one of the built-in algorithms, which common parameters MUST be specified? (Choose three.)<\/div><input type='hidden' name='question_id[]' id='qID_30' value='150796' \/><input type='hidden' id='answerType150796' 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-150796[]' id='answer-id-613187' class='answer   answerof-150796 ' value='613187'   \/><label for='answer-id-613187' id='answer-label-613187' class=' answer'><span>The training channel identifying the location of training data on an Amazon S3 bucket.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150796[]' id='answer-id-613188' class='answer   answerof-150796 ' value='613188'   \/><label for='answer-id-613188' id='answer-label-613188' class=' answer'><span>The validation channel identifying the location of validation data on an Amazon S3 bucket.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150796[]' id='answer-id-613189' class='answer   answerof-150796 ' value='613189'   \/><label for='answer-id-613189' id='answer-label-613189' class=' answer'><span>The IAM role that Amazon SageMaker can assume to perform tasks on behalf of the users.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150796[]' id='answer-id-613190' class='answer   answerof-150796 ' value='613190'   \/><label for='answer-id-613190' id='answer-label-613190' class=' answer'><span>Hyperparameters in a JSON array as documented for the algorithm used.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150796[]' id='answer-id-613191' class='answer   answerof-150796 ' value='613191'   \/><label for='answer-id-613191' id='answer-label-613191' class=' answer'><span>The Amazon EC2 instance class specifying whether training will be run using CPU or GP<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150796[]' id='answer-id-613192' class='answer   answerof-150796 ' value='613192'   \/><label for='answer-id-613192' id='answer-label-613192' class=' answer'><span>The output path specifying where on an Amazon S3 bucket the trained model will persist.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-31' style=';'><div id='questionWrap-31'  class='   watupro-question-id-150797'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>31. <\/span>A monitoring service generates 1 TB of scale metrics record data every minute. A Research team performs queries on this data using Amazon Athena. The queries run slowly due to the large volume of data, and the team requires better performance. <br \/>\r<br>How should the records be stored in Amazon S3 to improve query performance?<\/div><input type='hidden' name='question_id[]' id='qID_31' value='150797' \/><input type='hidden' id='answerType150797' 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-150797[]' id='answer-id-613193' class='answer   answerof-150797 ' value='613193'   \/><label for='answer-id-613193' id='answer-label-613193' class=' answer'><span>CSV files<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150797[]' id='answer-id-613194' class='answer   answerof-150797 ' value='613194'   \/><label for='answer-id-613194' id='answer-label-613194' class=' answer'><span>Parquet files<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150797[]' id='answer-id-613195' class='answer   answerof-150797 ' value='613195'   \/><label for='answer-id-613195' id='answer-label-613195' class=' answer'><span>Compressed JSON<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150797[]' id='answer-id-613196' class='answer   answerof-150797 ' value='613196'   \/><label for='answer-id-613196' id='answer-label-613196' class=' answer'><span>RecordIO<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-32' style=';'><div id='questionWrap-32'  class='   watupro-question-id-150798'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>32. <\/span>Machine Learning Specialist is working with a media company to perform classification on popular articles from the company's website. The company is using random forests to classify how popular an article will be before it is published. <br \/>\r<br>A sample of the data being used is below. <br \/>\r<br><br><img decoding=\"async\" width=650 height=266 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2020\/10\/image010-15.jpg\" v:shapes=\"_x0000_i1029\"><br><br \/>\r<br>Given the dataset, the Specialist wants to convert the Day_Of_Week column to binary values. <br \/>\r<br>What technique should be used to convert this column to binary values?<\/div><input type='hidden' name='question_id[]' id='qID_32' value='150798' \/><input type='hidden' id='answerType150798' 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-150798[]' id='answer-id-613197' class='answer   answerof-150798 ' value='613197'   \/><label for='answer-id-613197' id='answer-label-613197' class=' answer'><span>Binarization<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150798[]' id='answer-id-613198' class='answer   answerof-150798 ' value='613198'   \/><label for='answer-id-613198' id='answer-label-613198' class=' answer'><span>One-hot encoding<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150798[]' id='answer-id-613199' class='answer   answerof-150798 ' value='613199'   \/><label for='answer-id-613199' id='answer-label-613199' class=' answer'><span>Tokenization<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150798[]' id='answer-id-613200' class='answer   answerof-150798 ' value='613200'   \/><label for='answer-id-613200' id='answer-label-613200' class=' answer'><span>Normalization transformation<\/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-150799'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>33. <\/span>A gaming company has launched an online game where people can start playing for free, but they need to pay if they choose to use certain features. The company needs to build an automated system to predict whether or not a new user will become a paid user within 1 year. The company has gathered a labeled dataset from 1 million users. <br \/>\r<br>The training dataset consists of 1,000 positive samples (from users who ended up paying within 1 year) and 999,000 negative samples (from users who did not use any paid features). Each data sample consists of 200 features including user age, device, location, and play patterns. <br \/>\r<br>Using this dataset for training, the Data Science team trained a random forest model that converged with over 99% accuracy on the training set. However, the prediction results on a test dataset were not satisfactory <br \/>\r<br>Which of the following approaches should the Data Science team take to mitigate this issue? (Choose two.)<\/div><input type='hidden' name='question_id[]' id='qID_33' value='150799' \/><input type='hidden' id='answerType150799' 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-150799[]' id='answer-id-613201' class='answer   answerof-150799 ' value='613201'   \/><label for='answer-id-613201' id='answer-label-613201' class=' answer'><span>Add more deep trees to the random forest to enable the model to learn more features.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150799[]' id='answer-id-613202' class='answer   answerof-150799 ' value='613202'   \/><label for='answer-id-613202' id='answer-label-613202' class=' answer'><span>Include a copy of the samples in the test dataset in the training dataset.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150799[]' id='answer-id-613203' class='answer   answerof-150799 ' value='613203'   \/><label for='answer-id-613203' id='answer-label-613203' class=' answer'><span>Generate more positive samples by duplicating the positive samples and adding a small amount of noise to the duplicated data.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150799[]' id='answer-id-613204' class='answer   answerof-150799 ' value='613204'   \/><label for='answer-id-613204' id='answer-label-613204' class=' answer'><span>Change the cost function so that false negatives have a higher impact on the cost value than false positives.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-150799[]' id='answer-id-613205' class='answer   answerof-150799 ' value='613205'   \/><label for='answer-id-613205' id='answer-label-613205' class=' answer'><span>Change the cost function so that false positives have a higher impact on the cost value than false negatives.<\/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-150800'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>34. <\/span>A Data Scientist is developing a machine learning model to predict future patient outcomes based on information collected about each patient and their treatment plans. The model should output a continuous value as its prediction. The data available includes labeled outcomes for a set of 4,000 patients. The study was conducted on a group of individuals over the age of 65 who have a particular disease that is known to worsen with age. <br \/>\r<br>Initial models have performed poorly. While reviewing the underlying data, the Data Scientist notices that, out of 4,000 patient observations, there are 450 where the patient age has been input as 0. The other features for these observations appear normal compared to the rest of the sample population <br \/>\r<br>How should the Data Scientist correct this issue?<\/div><input type='hidden' name='question_id[]' id='qID_34' value='150800' \/><input type='hidden' id='answerType150800' 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-150800[]' id='answer-id-613206' class='answer   answerof-150800 ' value='613206'   \/><label for='answer-id-613206' id='answer-label-613206' class=' answer'><span>Drop all records from the dataset where age has been set to 0.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150800[]' id='answer-id-613207' class='answer   answerof-150800 ' value='613207'   \/><label for='answer-id-613207' id='answer-label-613207' class=' answer'><span>Replace the age field value for records with a value of 0 with the mean or median value from the dataset<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150800[]' id='answer-id-613208' class='answer   answerof-150800 ' value='613208'   \/><label for='answer-id-613208' id='answer-label-613208' class=' answer'><span>Drop the age feature from the dataset and train the model using the rest of the features.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150800[]' id='answer-id-613209' class='answer   answerof-150800 ' value='613209'   \/><label for='answer-id-613209' id='answer-label-613209' class=' answer'><span>Use k-means clustering to handle missing features<\/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-150801'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>35. <\/span>A Data Science team is designing a dataset repository where it will store a large amount of training data commonly used in its machine learning models. As Data Scientists may create an arbitrary number of new datasets every day, the solution has to scale automatically and be cost-effective. Also, it must be possible to explore the data using SQL. <br \/>\r<br>Which storage scheme is MOST adapted to this scenario?<\/div><input type='hidden' name='question_id[]' id='qID_35' value='150801' \/><input type='hidden' id='answerType150801' 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-150801[]' id='answer-id-613210' class='answer   answerof-150801 ' value='613210'   \/><label for='answer-id-613210' id='answer-label-613210' class=' answer'><span>Store datasets as files in Amazon S3.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150801[]' id='answer-id-613211' class='answer   answerof-150801 ' value='613211'   \/><label for='answer-id-613211' id='answer-label-613211' class=' answer'><span>Store datasets as files in an Amazon EBS volume attached to an Amazon EC2 instance.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150801[]' id='answer-id-613212' class='answer   answerof-150801 ' value='613212'   \/><label for='answer-id-613212' id='answer-label-613212' class=' answer'><span>Store datasets as tables in a multi-node Amazon Redshift cluster.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-150801[]' id='answer-id-613213' class='answer   answerof-150801 ' value='613213'   \/><label for='answer-id-613213' id='answer-label-613213' class=' answer'><span>Store datasets as global tables in Amazon DynamoD<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div style='display:none' id='question-36'>\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=\"watuPROButtons4721\" >\n\t\t  <div id=\"prev-question\" style=\"display:none;\"><input type=\"button\" value=\"&lt; 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