{"id":468,"date":"2023-01-14T11:08:30","date_gmt":"2023-01-14T11:08:30","guid":{"rendered":"https:\/\/exampracticetests.com\/aws\/Machine_Learning-Specialty_MLS-C01\/aws-certified-machine-learning-specialty-mls-c01-question069\/"},"modified":"2023-01-14T11:08:30","modified_gmt":"2023-01-14T11:08:30","slug":"aws-certified-machine-learning-specialty-mls-c01-question069","status":"publish","type":"post","link":"https:\/\/exampracticetests.com\/aws\/Machine_Learning-Specialty_MLS-C01\/aws-certified-machine-learning-specialty-mls-c01-question069\/","title":{"rendered":"AWS Certified Machine Learning &#8211; Specialty MLS-C01 &#8211; Question069"},"content":{"rendered":"<div class=\"question\">A large consumer goods manufacturer has the following products on sale:<br \/>\n&#8211; 34 different toothpaste variants<br \/>\n&#8211; 48 different toothbrush variants<br \/>\n&#8211; 43 different mouthwash variants<br \/>\nThe entire sales history of all these products is available in Amazon S3. Currently, the company is using custom-built autoregressive integrated moving average (ARIMA) models to forecast demand for these products. The company wants to predict the demand for a new product that will soon be launched.<br \/>\nWhich solution should a Machine Learning Specialist apply?<br \/><strong><br \/>A.<\/strong> Train a custom ARIMA model to forecast demand for the new product.<br \/><strong>B.<\/strong> Train an Amazon SageMaker DeepAR algorithm to forecast demand for the new product.<br \/><strong>C.<\/strong> Train an Amazon SageMaker k-means clustering algorithm to forecast demand for the new product.<br \/><strong>D.<\/strong> Train a custom XGBoost model to forecast demand for the new product.<\/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>B<\/strong><\/div>\n<p><strong>Explanation:<\/strong> <\/p>\n<div class=\"explanation\">\nExplanation:<br \/>\nThe Amazon SageMaker DeepAR forecasting algorithm is a supervised learning algorithm for forecasting scalar (one-dimensional) time series using recurrent neural networks (RNN). Classical forecasting methods, such as autoregressive integrated moving average (ARIMA) or exponential smoothing (ETS), fit a single model to each individual time series. They then use that model to extrapolate the time series into the future.<br \/>\nReference: <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/deepar.html\" title=\"External link\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/deepar.html<\/a><\/div>\n<p><\/strong><\/span> <\/div>\n","protected":false},"excerpt":{"rendered":"<p>A large consumer goods manufacturer has the following products on sale: &#8211; 34 different toothpaste variants &#8211; 48 different toothbrush variants &#8211; 43 different mouthwash variants The entire sales history of all these products is available in Amazon S3. Currently, the company is using custom-built autoregressive integrated moving average (ARIMA) models to forecast demand for [&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":[3,72],"class_list":["post-468","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-069"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/exampracticetests.com\/aws\/Machine_Learning-Specialty_MLS-C01\/wp-json\/wp\/v2\/posts\/468","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=468"}],"version-history":[{"count":0,"href":"https:\/\/exampracticetests.com\/aws\/Machine_Learning-Specialty_MLS-C01\/wp-json\/wp\/v2\/posts\/468\/revisions"}],"wp:attachment":[{"href":"https:\/\/exampracticetests.com\/aws\/Machine_Learning-Specialty_MLS-C01\/wp-json\/wp\/v2\/media?parent=468"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/exampracticetests.com\/aws\/Machine_Learning-Specialty_MLS-C01\/wp-json\/wp\/v2\/categories?post=468"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/exampracticetests.com\/aws\/Machine_Learning-Specialty_MLS-C01\/wp-json\/wp\/v2\/tags?post=468"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}