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Topics include accelerating training on large datasets in Amazon S3, computing tf–idf matrix dimensions, automating S3 dataset transformations and metadata cataloging with minimal setup, improving training stability when loss converges to different stable values, selecting confusion matrices under business-cost constraints, addressing fraud detection recall with class imbalance techniques and thresholding, and mitigating bias from missing feature values in supervised learning workflows.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":20,"@type":76,"position":81},"https://docshare.wps.com/document/exam/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/aws-certified-machine-learning-specialty-sample-exam-questions/317425/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/aws-certified-machine-learning-specialty-sample-exam-questions/317425.png","ImageObject",300,407,{"name":92,"@type":93},"Đào","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-28","2026-09-20",true,{"@type":102,"interactionType":103,"userInteractionCount":39},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What can a machine learning specialist do to accelerate training on large CSV datasets in Amazon S3?","Question",{"text":112,"@type":113},"Choose an option that speeds up training by streaming or efficiently handling data ingestion for SageMaker, rather than switching to unrelated services.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How are the dimensions of a tf–idf matrix determined when using both unigrams and bigrams?",{"text":117,"@type":113},"They depend on the corpus-derived vocabulary size for unigrams and bigrams used in the tf–idf representation.",{"name":119,"@type":110,"acceptedAnswer":120},"Which approach helps a fraud detection model detect more than 10% of fraud cases when accuracy is high but most fraud is missed?",{"text":121,"@type":113},"Apply a method that improves recall under class imbalance, such as oversampling to balance the dataset or adjusting decision thresholds appropriately.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},317425,1790437467,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":19,"category_name":20,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":39,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":29,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":143,"read_time":144,"preview_page_count":4},1374402968488,"https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0","Machine Learning – Specialty (MLS-C01)  \n Sample Exam Questions  \n1) A machine learning team has several large CSV datasets in Amazon S3 . Historically, models built with the Amazon SageMaker Linear Learner algorithm have taken hours to train on similar-sized datasets. The team’s leaders need to accelerate the training process.  \nWhat can a machine learning specialist do to address this concern?  \nA) Use Amazon SageMaker Pipe mode.  \nB) Use Amazon Machine Learning to train the models.  \nC) Use Amazon Kinesis to stream the data to Amazon SageMaker.  \nD) Use AWS Glue to transform the CSV dataset to the JSON format.  \n2) A term frequency–inverse document frequency (tf–idf) matrix using both unigrams and bigrams is built from a text corpus consisting of the following two sentences:  \n1. Please call the number below.  \n2. Please do not call us.  \nWhat are the dimensions of the tf–idf matrix?  \nA) (2, 16)  \nB) (2, 8)  \nC) (2, 10)  \nD) (8, 10)  \n3) A company is setting up a system to manage all of the datasets it stores in Amazon S3 . The company would like to automate running transformation jobs on the data and maintaining a catalog of the metadata concerning the datasets. The solution should require the least amount of setup and maintenance.  \nWhich solution will allow the company to achieve its goals?  \nA) Create an Amazon EMR cluster with Apache Hive installed. Then, create a Hive metastore and a script to run transformation jobs on a schedule.  \nB) Create an AWS Glue crawler to populate the AWS Glue Data Catalog. Then, author an AWS Glue ETL job, and set up a schedule for data transformation jobs.  \nC) Create an Amazon EMR cluster with Apache Spark installed. Then, create an Apache Hive metastore and a script to run transformation jobs on a schedule.  \nD) Create an Amazon SageMaker Jupyter notebook instance that transforms the data. Then, create an Apache Hive metastore and a script to run transformation jobs on a schedule.  \n© 2020, Amazon Web Services, Inc. or its affiliates. All rights [reserved | aws.amazon.com](reserved | aws.amazon.com) 1 | P a g e  \nMachine Learning – Specialty (MLS-C01)  \n Sample Exam Questions  \n4) A data scientist is working on optimizing a model during the training process by varying multiple parameters. The data scientist observes that, during multiple runs with identical parameters, the loss function converges to different, yet stable, values.  \nWhat should the data scientist do to improve the training process?  \nA) Increase the learning rate. Keep the batch size the same.  \nB) Decrease the learning rate. Reduce the batch size.  \nC) Decrease the learning rate. Keep the batch size the same.  \nD) Do not change the learning rate. Increase the batch size.  \n5) A data scientist is evaluating different binary classification models. A false positive result is 5 times more expensive (from a business perspective) than a false negative result.  \nThe models should be evaluated based on the following criteria:  \n1) Must have a recall rate of at least 80%  \n2) Must have a false positive rate of 10% or less  \n3) Must minimize business costs  \nAfter creating each binary classification model, the data scientist generates the corresponding confusion matrix.  \nWhich confusion matrix represents the model that satisfies the requirements?  \nA) TN = 91, FP = 9 FN = 22, TP = 78  \nB) TN = 99, FP = 1 FN = 21, TP = 79  \nC) TN = 96, FP = 4 FN = 10, TP = 90  \nD) TN = 98, FP = 2 FN = 18, TP = 82  \n6) A data scientist uses logistic regression to build a fraud detection model. While the model accuracy is 99%, 90% of the fraud cases are not detected by the model.  \nWhat action will definitively help the model detect more than 10% of fraud cases?  \nA) Using undersampling to balance the dataset  \nB) Decreasing the class probability threshold  \nC) Using regularization to reduce overfitting  \nD) Using oversampling to balance the dataset  \n© 2020, Amazon Web Services, Inc. or its affiliates. All rights [reserved | aws.amazon.com](reser","cbCair21hDxwI0ID","https://ap.wps.com/l/cbCair21hDxwI0ID","pdf",444738,"English","# Machine Learning – Specialty (MLS-C01)\n## Sample Exam Questions\n### Question 1\n### Question 2\n### Question 3\n### Question 4\n### Question 5\n### Question 6\n### Question 7\n### Question 8\n### Question 9","[{\"question\":\"What can a machine learning specialist do to accelerate training on large CSV datasets in Amazon S3?\",\"answer\":\"Choose an option that speeds up training by streaming or efficiently handling data ingestion for SageMaker, rather than switching to unrelated services.\"},{\"question\":\"How are the dimensions of a tf–idf matrix determined when using both unigrams and bigrams?\",\"answer\":\"They depend on the corpus-derived vocabulary size for unigrams and bigrams used in the tf–idf representation.\"},{\"question\":\"Which approach helps a fraud detection model detect more than 10% of fraud cases when accuracy is high but most fraud is missed?\",\"answer\":\"Apply a method that improves recall under class imbalance, such as oversampling to balance the dataset or adjusting decision thresholds appropriately.\"}]","AWS-Certified-Machine-Learning-Specialty - Sample Exam Questions | PDF",1789932714,15]