{"version":"1.0","provider_name":"Abonnieren","provider_url":"https:\/\/aisuperior.com\/de\/","title":"Machine Learning and Data Preparation for Underwriting - aisuperior","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"mdFHaVVeOF\"><a href=\"https:\/\/aisuperior.com\/de\/experts\/machine-learning-and-data-preparation-for-underwriting\/\">Maschinelles Lernen und Datenaufbereitung f\u00fcr das Underwriting<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/aisuperior.com\/de\/experts\/machine-learning-and-data-preparation-for-underwriting\/embed\/#?secret=mdFHaVVeOF\" width=\"600\" height=\"338\" title=\"\u201eMaschinelles Lernen und Datenaufbereitung f\u00fcr das Underwriting\u201c \u2013 aisuperior\" data-secret=\"mdFHaVVeOF\" 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:\/\/aisuperior.com\/wp-includes\/js\/wp-embed.min.js\n<\/script>","thumbnail_url":"https:\/\/aisuperior.com\/wp-content\/uploads\/2023\/09\/aidata.jpeg","thumbnail_width":1024,"thumbnail_height":683,"description":"Practical experience and theoretical background allow us to properly represent various types of heterogeneous data into ready to use machine learning data sets. We perfect the art of feature engineering for time-series data, financial transactions, spatiotemporal information, behavioral patterns and many more. A high-quality risk scoring model is one of the key success factors in [&hellip;]"}