<?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>Tue, 18 Aug 2026 18:50:29 GMT</lastBuildDate><atom:link href="https://ecency.com/created/r-programming/rss.xml" rel="self" type="application/rss+xml"/><item><title><![CDATA[Machine Learning with R and TensorFlow]]></title><description><![CDATA[J.J. Allaire's keynote at rstudio::conf 2018 on the R interface to TensorFlow ( a suite of packages that provide high-level interfaces to deep learning models (Keras) and standard regression and classification]]></description><link>https://ecency.com/@datatreemap/machine-learning-with-r-and-tensorflow</link><guid isPermaLink="true">https://ecency.com/@datatreemap/machine-learning-with-r-and-tensorflow</guid><category><![CDATA[machine-learning]]></category><dc:creator><![CDATA[datatreemap]]></dc:creator><pubDate>Thu, 24 May 2018 06:52:00 GMT</pubDate><enclosure url="https://i.ecency.com/p/S5Eokt4BcQdk7EHeT1aYjzebg2hC7hkthT45eFBmk8fvF67hTSgJXHmrPyCHm5owwNyBPjU?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[TensorFlow and Keras in R]]></title><description><![CDATA[Josh Gordon sits down with J.J. Allaire, the founder of RStudio. They discuss TensorFlow and Keras support in R, and the educational resources available for R developers new to deep learning. Learn more]]></description><link>https://ecency.com/@datatreemap/tensorflow-and-keras-in-r</link><guid isPermaLink="true">https://ecency.com/@datatreemap/tensorflow-and-keras-in-r</guid><category><![CDATA[deep-learning]]></category><dc:creator><![CDATA[datatreemap]]></dc:creator><pubDate>Wed, 23 May 2018 08:25:21 GMT</pubDate><enclosure url="https://i.ecency.com/p/S5Eokt4BcQdk7EHeT1aYjzebg2hC7hkthT45eBxthBBMCpw2DEynesiKwi8DMPqPG6ZQq6E?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[R Programming Tutorial – How to Compute PI using Monte Carlo in R?  R语言入门之 – 如何通过Monte Carlo来计算 PI?]]></title><description><![CDATA[ This tutorial will continue to help you understand how powerful R is to handle the vectors (arrays).   We know that the math constant  can be approximated by 4 times of the number]]></description><link>https://ecency.com/@justyy/r-programming-tutorial-how-to-compute-pi-using-monte-carlo-in-r-r-monte-carlo-pi</link><guid isPermaLink="true">https://ecency.com/@justyy/r-programming-tutorial-how-to-compute-pi-using-monte-carlo-in-r-r-monte-carlo-pi</guid><category><![CDATA[cn]]></category><dc:creator><![CDATA[justyy]]></dc:creator><pubDate>Sun, 23 Jul 2017 07:32:54 GMT</pubDate><enclosure url="https://i.ecency.com/p/MG5aEqKFcQi7H7hxeMCW1S283dy19xTaejdgVX11MHzawqeAn6KN8PMVsSi3sU98uW7YN9XeEqQyq4hGQ6pE4h7KX5if9LsuY?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[错位排列 的 R语言实现]]></title><description><![CDATA[ 递归终止条件: F(1) = 0, F(2) = 1. 具体的推导可以看这里.英文: Derangement Permutation Implementation using R Programming    XXX原文::]]></description><link>https://ecency.com/@justyy/r</link><guid isPermaLink="true">https://ecency.com/@justyy/r</guid><category><![CDATA[cn]]></category><dc:creator><![CDATA[justyy]]></dc:creator><pubDate>Sat, 20 Aug 2016 20:54:57 GMT</pubDate></item></channel></rss>