{"version":"1.0","provider_name":".NET Blog","provider_url":"https:\/\/devblogs.microsoft.com\/dotnet","author_name":"Bri Achtman","author_url":"https:\/\/devblogs.microsoft.com\/dotnet\/author\/brachtma\/","title":"Hey .NET! Have you tried ML.NET? - .NET Blog","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"TiPTyqDKbf\"><a href=\"https:\/\/devblogs.microsoft.com\/dotnet\/hey-net-have-you-tried-ml-net\/\">Hey .NET! Have you tried ML.NET?<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/devblogs.microsoft.com\/dotnet\/hey-net-have-you-tried-ml-net\/embed\/#?secret=TiPTyqDKbf\" width=\"600\" height=\"338\" title=\"&#8220;Hey .NET! Have you tried ML.NET?&#8221; &#8212; .NET Blog\" data-secret=\"TiPTyqDKbf\" 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:\/\/devblogs.microsoft.com\/dotnet\/wp-includes\/js\/wp-embed.min.js\n\/* ]]> *\/\n<\/script>\n","thumbnail_url":"https:\/\/devblogs.microsoft.com\/dotnet\/wp-content\/uploads\/sites\/10\/2019\/03\/mlnet-logo.png","thumbnail_width":115,"thumbnail_height":115,"description":"ML.NET\u00a0is an open source and cross-platform machine learning framework made for .NET developers. Using ML.NET you can easily build custom machine learning models for scenarios like sentiment analysis, price prediction, sales forecasting, recommendation, image classification, and more. ML.NET 1.0 was released at \/\/Build 2019, and since then the team has been working hard on adding [&hellip;]"}