<?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>Sun, 23 Aug 2026 23:11:58 GMT</lastBuildDate><atom:link href="https://ecency.com/created/machine-learing/rss.xml" rel="self" type="application/rss+xml"/><item><title><![CDATA[学习笔记：神经网络的优化策略]]></title><description><![CDATA[本文基本上是 Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization 的知识点大纲。 具体的公式和理论，可以看Bin Weber的博客。 训练/开发/测试集（Train/dev/test） 数据量10000之内：70/30（免去dev）或60/20/20]]></description><link>https://ecency.com/@heyeshuang/6oww5x</link><guid isPermaLink="true">https://ecency.com/@heyeshuang/6oww5x</guid><category><![CDATA[cn]]></category><dc:creator><![CDATA[heyeshuang]]></dc:creator><pubDate>Sat, 09 Dec 2017 09:53:48 GMT</pubDate></item></channel></rss>