{"id":575,"date":"2023-01-14T11:10:21","date_gmt":"2023-01-14T11:10:21","guid":{"rendered":"https:\/\/exampracticetests.com\/aws\/Machine_Learning-Specialty_MLS-C01\/aws-certified-machine-learning-specialty-mls-c01-question176\/"},"modified":"2023-01-14T11:10:21","modified_gmt":"2023-01-14T11:10:21","slug":"aws-certified-machine-learning-specialty-mls-c01-question176","status":"publish","type":"post","link":"https:\/\/exampracticetests.com\/aws\/Machine_Learning-Specialty_MLS-C01\/aws-certified-machine-learning-specialty-mls-c01-question176\/","title":{"rendered":"AWS Certified Machine Learning &#8211; Specialty MLS-C01 &#8211; Question176"},"content":{"rendered":"<div class=\"question\">A machine learning (ML) specialist needs to extract embedding vectors from a text series. The goal is to provide a ready-to-ingest feature space for a data scientist to develop downstream ML predictive models. The text consists of curated sentences in English. Many sentences use similar words but in different contexts. There are questions and answers among the sentences, and the embedding space must differentiate between them.<br \/>\nWhich options can produce the required embedding vectors that capture word context and sequential QA information? (Choose two.)<br \/><strong><br \/>A.<\/strong> Amazon SageMaker seq2seq algorithm<br \/><strong>B.<\/strong> Amazon SageMaker BlazingText algorithm in Skip-gram mode<br \/><strong>C.<\/strong> Amazon SageMaker Object2Vec algorithm<br \/><strong>D.<\/strong> Amazon SageMaker BlazingText algorithm in continuous bag-of-words (CBOW) mode<br \/><strong>E.<\/strong> Combination of the Amazon SageMaker BlazingText algorithm in Batch Skip-gram mode with a custom recurrent neural network (RNN)<\/div>\n<p><\/p>\n<style> .hidden-div{ display:none } <\/style>\n<p>\t\t\t\t\t\t\t<button onclick=\"getElementById('hidden-div').style.display = 'block'\"> Show Answer <\/button> <button onclick=\"getElementById('hidden-div').style.display = 'none'\">Hide Answer<\/button><\/p>\n<div class=\"hidden-div\" id=\"hidden-div\"><span style=\"\"><\/p>\n<div class=\"answer\">Correct Answer: <strong>AC<\/strong><\/div>\n<p><strong>Explanation:<\/strong> <\/p>\n<div class=\"explanation\">\nReference: <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/create-a-word-pronunciation-sequence-to-sequence-model-using-amazon-sagemaker\/\" title=\"External link\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/aws.amazon.com\/blogs\/machine-learning\/create-a-word-pronunc&#8230;<\/a><br \/>\n<a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/object2vec.html\" title=\"External link\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/object2vec.html<\/a><\/div>\n<p><\/strong><\/span> <\/div>\n","protected":false},"excerpt":{"rendered":"<p>A machine learning (ML) specialist needs to extract embedding vectors from a text series. The goal is to provide a ready-to-ingest feature space for a data scientist to develop downstream ML predictive models. The text consists of curated sentences in English. Many sentences use similar words but in different contexts. There are questions and answers [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[3,179],"class_list":["post-575","post","type-post","status-publish","format-standard","hentry","category-aws-certified-machine-learning-specialty-mls-c01","tag-aws-certified-machine-learning-specialty-mls-c01","tag-question-176"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/exampracticetests.com\/aws\/Machine_Learning-Specialty_MLS-C01\/wp-json\/wp\/v2\/posts\/575","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/exampracticetests.com\/aws\/Machine_Learning-Specialty_MLS-C01\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/exampracticetests.com\/aws\/Machine_Learning-Specialty_MLS-C01\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/exampracticetests.com\/aws\/Machine_Learning-Specialty_MLS-C01\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/exampracticetests.com\/aws\/Machine_Learning-Specialty_MLS-C01\/wp-json\/wp\/v2\/comments?post=575"}],"version-history":[{"count":0,"href":"https:\/\/exampracticetests.com\/aws\/Machine_Learning-Specialty_MLS-C01\/wp-json\/wp\/v2\/posts\/575\/revisions"}],"wp:attachment":[{"href":"https:\/\/exampracticetests.com\/aws\/Machine_Learning-Specialty_MLS-C01\/wp-json\/wp\/v2\/media?parent=575"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/exampracticetests.com\/aws\/Machine_Learning-Specialty_MLS-C01\/wp-json\/wp\/v2\/categories?post=575"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/exampracticetests.com\/aws\/Machine_Learning-Specialty_MLS-C01\/wp-json\/wp\/v2\/tags?post=575"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}