{"version":"1.0","provider_name":"Glosarix","provider_url":"https:\/\/glosarix.com\/en\/","author_name":"Team Glosarix","author_url":"https:\/\/glosarix.com\/en\/author\/adm_glosarix\/","title":"Recurrent Loss Function - Glosarix","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"x165ehLwW9\"><a href=\"https:\/\/glosarix.com\/en\/glossary\/recurrent-loss-function-en\/\">Recurrent Loss Function<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/glosarix.com\/en\/glossary\/recurrent-loss-function-en\/embed\/#?secret=x165ehLwW9\" width=\"600\" height=\"338\" title=\"&#8220;Recurrent Loss Function&#8221; &#8212; Glosarix\" data-secret=\"x165ehLwW9\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script>\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),o=l.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),c=new RegExp(\"^https?:$\",\"i\"),i=0;i<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener(\"message\",d.wp.receiveEmbedMessage,!1),l.addEventListener(\"DOMContentLoaded\",function(){for(var e,t,s=l.querySelectorAll(\"iframe.wp-embedded-content\"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute(\"data-secret\"))||(t=Math.random().toString(36).substring(2,12),e.src+=\"#?secret=\"+t,e.setAttribute(\"data-secret\",t)),e.contentWindow.postMessage({message:\"ready\",secret:t},\"*\")},!1)))}(window,document);\n\/\/# sourceURL=https:\/\/glosarix.com\/wp-includes\/js\/wp-embed.min.js\n<\/script>\n","description":"Description: The recurrent loss function is a crucial component in the training of recurrent neural networks (RNNs), which are architectures designed to process sequences of data. This function measures the discrepancy between the predictions made by the network and the actual values in a dataset, allowing for the adjustment of the network&#8217;s weights to improve [&hellip;]"}