<?xml version="1.0" encoding="UTF-8"?><rss xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title><![CDATA[RSS Feed]]></title><description><![CDATA[RSS Feed]]></description><link>https://ecency.com</link><image><url>https://ecency.com/logo512.png</url><title>RSS Feed</title><link>https://ecency.com</link></image><generator>RSS for Node</generator><lastBuildDate>Fri, 14 Aug 2026 07:52:43 GMT</lastBuildDate><atom:link href="https://ecency.com/@richardhan/rss" rel="self" type="application/rss+xml"/><item><title><![CDATA[The Math Behind Machine Learning]]></title><description><![CDATA[Let’s look at several techniques in machine learning and the math topics that are used in the process. In linear regression, we try to find the best fit line or hyperplane for a given set of data points.]]></description><link>https://ecency.com/@richardhan/the-math-behind-machine-learning</link><guid isPermaLink="true">https://ecency.com/@richardhan/the-math-behind-machine-learning</guid><category><![CDATA[machinelearning]]></category><dc:creator><![CDATA[richardhan]]></dc:creator><pubDate>Fri, 02 Nov 2018 04:47:54 GMT</pubDate><enclosure url="https://i.ecency.com/p/cyxkEVqiiLyCAwGTdB3LH2EHojbEJGXUSf9jGNrsasNA1r8YTH6SfwZGCQ4q4EbLt9xZg8QhypVTizBEyGdSPdLc5oMyucaJobdmjddkjk5oC4ApBGsHYxPqvzKd1yRJptN?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Math for Machine Learning: Open Doors to Great Careers]]></title><description><![CDATA[Learn the core topics of  Machine Learning to open doors to Computer Science, Data Science, and Artificial Intelligence!  Visit:]]></description><link>https://ecency.com/@richardhan/math-for-machine-learning-open-doors-to-great-careers</link><guid isPermaLink="true">https://ecency.com/@richardhan/math-for-machine-learning-open-doors-to-great-careers</guid><category><![CDATA[math]]></category><dc:creator><![CDATA[richardhan]]></dc:creator><pubDate>Mon, 29 Jan 2018 21:10:33 GMT</pubDate><enclosure url="https://i.ecency.com/p/S5Eokt4BcQdk7EHeT1aYjzebg2hC7hkthT45eAjbbQMQ6tUoQj8FC7dCLfpRpMAq77p4Ye2?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Introduction Lecture Math for Machine Learning]]></title><description><![CDATA[Learn the core topics of Machine Learning to open doors to Computer Science, Data Science, Artificial Intelligence!  For the full course, visit:]]></description><link>https://ecency.com/@richardhan/introduction-lecture-math-for-machine-learning</link><guid isPermaLink="true">https://ecency.com/@richardhan/introduction-lecture-math-for-machine-learning</guid><category><![CDATA[math]]></category><dc:creator><![CDATA[richardhan]]></dc:creator><pubDate>Mon, 29 Jan 2018 21:05:18 GMT</pubDate><enclosure url="https://i.ecency.com/p/S5Eokt4BcQdk7EHeT1aYjzebg2hC7hkthT45dvdavnhqxx1aeeBS8wgy8SUYcYwrP3qiWfG?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Math for Machine Learning (First Module)]]></title><description><![CDATA[This is the first module of the online course Math for Machine Learning by Richard Han. Learn the core topics of Machine Learning to open doors to Computer Science, Data Science, Artificial Intelligence!]]></description><link>https://ecency.com/@richardhan/math-for-machine-learning-first-module</link><guid isPermaLink="true">https://ecency.com/@richardhan/math-for-machine-learning-first-module</guid><category><![CDATA[math]]></category><dc:creator><![CDATA[richardhan]]></dc:creator><pubDate>Mon, 29 Jan 2018 20:53:48 GMT</pubDate><enclosure url="https://i.ecency.com/p/S5Eokt4BcQdk7EHeT1aYjzebg2hC7hkthT45dvdavnhqxx1aeeBS8wgy8SUYcYwrP3qiWfG?format=match&amp;mode=fit" length="0" type="false"/></item></channel></rss>