{"id":8666,"date":"2022-04-28T21:15:51","date_gmt":"2022-04-28T21:15:51","guid":{"rendered":"https:\/\/www.tun.com\/courses\/2019\/12\/23\/introduction-to-recommender-systems-non-personalized-and-content-based\/"},"modified":"2022-04-28T21:15:51","modified_gmt":"2022-04-28T21:15:51","slug":"introduction-to-recommender-systems-non-personalized-and-content-based","status":"publish","type":"post","link":"https:\/\/www.tun.com\/courses\/introduction-to-recommender-systems-non-personalized-and-content-based\/university-of-minnesota\/","title":{"rendered":"Introduction to Recommender Systems:  Non-Personalized and Content-Based"},"content":{"rendered":"<div class=\"single_post\" style=\"margin-top:16px;\";>\n<div class=\"post-single-content box mark-links entry-content\">\n<div class=\"thecontent\">\n<h2>Description<\/h2>\n<p>This course, which is designed to serve as the first course in the Recommender Systems specialization, introduces the concept of recommender systems, reviews several examples in detail, and leads you through non-personalized recommendation using summary statistics and product associations, basic stereotype-based or demographic recommendations, and content-based filtering recommendations. <\/p>\n<p>After completing this course, you will be able to compute a variety of recommendations from datasets using basic spreadsheet tools, and if you complete the honors track you will also have programmed these recommendations using the open source LensKit recommender toolkit.  <\/p>\n<p>In addition to detailed lectures and interactive exercises, this course features interviews with several leaders in research and practice on advanced topics and current directions in recommender systems.<\/p>\n<div style=\"height:45px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n<h2 class=\"has-text-align-center\">Price: Enroll For Free!<\/h2>\n<div style=\"height:45px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n<div class=\"wp-block-button aligncenter\"><a class=\"wp-block-button__link has-text-color has-very-light-gray-color has-background has-vivid-red-background-color\" href=\"https:\/\/www.coursera.org\/learn\/recommender-systems-introduction\">View Class<\/a><\/div>\n<div style=\"height:55px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n<div class=\"wp-block-columns\">\n<div class=\"wp-block-column\">\n<p class=\"has-text-align-center\"><em><strong>Language:<\/strong> <\/em>English<\/p>\n<\/div>\n<div class=\"wp-block-column\">\n<p class=\"has-text-align-center\"><em><strong>Subtitles<\/strong>: <\/em>English<\/p>\n<\/div>\n<\/div>\n<p style=\"background-color:#496d89\" class=\"has-text-color has-background has-text-align-center has-very-light-gray-color\"><a href=\"https:\/\/www.coursera.org\/learn\/recommender-systems-introduction\">Introduction to Recommender Systems:  Non-Personalized and Content-Based<strong> &#8211; University of Minnesota<\/strong><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Description This course, which is designed to serve as the first course in the Recommender Systems specialization, introduces the concept of recommender systems, reviews several examples in detail, and leads you through non-personalized recommendation using summary statistics and product associations, basic stereotype-based or demographic recommendations, and content-based filtering recommendations. After completing this course, you will [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":19402,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_uag_custom_page_level_css":"","_monsterinsights_skip_tracking":false,"_uf_show_specific_survey":0,"_uf_disable_surveys":false,"footnotes":""},"categories":[263],"tags":[],"class_list":["post-8666","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-university-of-minnesota"],"aioseo_notices":[],"uagb_featured_image_src":{"full":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/University-of-Minnesotaonline-education.png",378,224,false],"thumbnail":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/University-of-Minnesotaonline-education-150x150.png",150,150,true],"medium":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/University-of-Minnesotaonline-education-300x178.png",300,178,true],"medium_large":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/University-of-Minnesotaonline-education.png",378,224,false],"large":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/University-of-Minnesotaonline-education.png",378,224,false],"1536x1536":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/University-of-Minnesotaonline-education.png",378,224,false],"2048x2048":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/University-of-Minnesotaonline-education.png",378,224,false]},"uagb_author_info":{"display_name":"Axiom Pegasus","author_link":"https:\/\/www.tun.com\/courses\/author\/magic\/"},"uagb_comment_info":0,"uagb_excerpt":"Description This course, which is designed to serve as the first course in the Recommender Systems specialization, introduces the concept of recommender systems, reviews several examples in detail, and leads you through non-personalized recommendation using summary statistics and product associations, basic stereotype-based or demographic recommendations, and content-based filtering recommendations. After completing this course, you will&hellip;","featured_media_src_url":"https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/University-of-Minnesotaonline-education.png","_links":{"self":[{"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/posts\/8666","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/comments?post=8666"}],"version-history":[{"count":0,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/posts\/8666\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/media\/19402"}],"wp:attachment":[{"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/media?parent=8666"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/categories?post=8666"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/tags?post=8666"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}