{"version":"1.0","provider_name":"Der GitHub Blog","provider_url":"https:\/\/github.blog\/de","author_name":"Thomas Elliott","author_url":"https:\/\/github.blog\/de\/author\/telliott27\/","title":"Aktuelles von Octoverse: Maschinelles Lernen","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"OYLzepmVPf\"><a href=\"https:\/\/github.blog\/de\/2019-01-24-the-state-of-the-octoverse\/\">The State of the Octoverse Report: Machine Learning<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/github.blog\/de\/2019-01-24-the-state-of-the-octoverse\/embed\/#?secret=OYLzepmVPf\" width=\"600\" height=\"338\" title=\"&#8222;The State of the Octoverse Report: Machine Learning&#8220; &#8212; Der GitHub Blog\" data-secret=\"OYLzepmVPf\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script type=\"text\/javascript\">\n\/* <![CDATA[ *\/\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:\/\/github.blog\/de\/wp-includes\/js\/wp-embed.min.js\n\/* ]]> *\/\n<\/script>\n","thumbnail_url":"https:\/\/github.blog\/de\/wp-content\/uploads\/sites\/3\/2019\/01\/policy-predictions-hubot.png?fit=1200%2C630","thumbnail_width":1200,"thumbnail_height":630,"description":"In unserem Bericht 2018 Octoverse stellten wir fest, dass maschinelles Lernen und Datenwissenschaft beliebte Themen auf GitHub waren. tensorflow\/tensorflow war eines der Projekte mit den meisten Beteiligungen, pytorch\/pytorch war eines der am schnellsten wachsenden Projekte, und Python war die drittpopul\u00e4rste Sprache auf GitHub. Wir haben uns entschieden, etwas tiefer in das Thema maschinelles Lernen und Datenwissenschaft auf GitHub einzutauchen."}