{"id":34650,"date":"2017-02-17T10:22:40","date_gmt":"2017-02-17T18:22:40","guid":{"rendered":"http:\/\/lifeboat.com\/blog\/2017\/02\/wide-deep-learning-memorization-generalization-with-tensorflow-tensorflow-dev-summit-2017"},"modified":"2017-06-04T07:12:34","modified_gmt":"2017-06-04T14:12:34","slug":"wide-deep-learning-memorization-generalization-with-tensorflow-tensorflow-dev-summit-2017","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2017\/02\/wide-deep-learning-memorization-generalization-with-tensorflow-tensorflow-dev-summit-2017","title":{"rendered":"Wide &amp; Deep Learning: Memorization + Generalization with TensorFlow (TensorFlow Dev Summit 2017)"},"content":{"rendered":"<p><\/p>\n<p><iframe style=\"display: block; margin: 0 auto; width: 100%; aspect-ratio: 4\/3; object-fit: contain;\" src=\"https:\/\/www.youtube.com\/embed\/NV1tkZ9Lq48?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; encrypted-media; gyroscope;\n   picture-in-picture\" allowfullscreen><\/iframe><\/p>\n<p>Wide models are great for memorization, deep models are great for generalization \u2014 why not combine them to create even better models? In this talk, Heng-Tze Cheng explains Wide and Deep networks and gives examples of how they can be used.<\/p>\n<p>Check out our blog post, paper, YouTube video, TensorFlow tutorials: <a href=\"https:\/\/goo.gl\/MwVlVa\" class=\"\" data-url=\"https:\/\/goo.gl\/MwVlVa\" data-target-new-window=\"True\" data-servicelink=\"CDEQ6TgYACITCJmwoOrfl9ICFUvHrgodZOUGGyj4HQ\" rel=\"nofollow noopener\" target=\"_blank\"><a href=\"https:\/\/goo.gl\/MwVlVa\">https:\/\/goo.gl\/MwVlVa<\/a><\/a><\/p>\n<p>Visit the TensorFlow website for all session recordings: <a href=\"https:\/\/goo.gl\/bsYmza\" class=\"\" data-url=\"https:\/\/goo.gl\/bsYmza\" data-target-new-window=\"True\" data-servicelink=\"CDEQ6TgYACITCJmwoOrfl9ICFUvHrgodZOUGGyj4HQ\" rel=\"nofollow noopener\" target=\"_blank\"><a href=\"https:\/\/goo.gl\/bsYmza\">https:\/\/goo.gl\/bsYmza<\/a><\/a><\/p>\n<p><!-- Link: <a href=\"https:\/\/www.youtube.com\/watch?v=NV1tkZ9Lq48&feature=share\">https:\/\/www.youtube.com\/watch?v=NV1tkZ9Lq48&feature=share<\/a> --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Wide models are great for memorization, deep models are great for generalization \u2014 why not combine them to create even better models? In this talk, Heng-Tze Cheng explains Wide and Deep networks and gives examples of how they can be used. Check out our blog post, paper, YouTube video, TensorFlow tutorials: https:\/\/goo.gl\/MwVlVa Visit the TensorFlow [\u2026]<\/p>\n","protected":false},"author":423,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6],"tags":[],"class_list":["post-34650","post","type-post","status-publish","format-standard","hentry","category-robotics-ai"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/34650","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/users\/423"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=34650"}],"version-history":[{"count":2,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/34650\/revisions"}],"predecessor-version":[{"id":58682,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/34650\/revisions\/58682"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=34650"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=34650"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=34650"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}