<?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>http://direct.ecency.com</link><image><url>http://direct.ecency.com/logo512.png</url><title>RSS Feed</title><link>http://direct.ecency.com</link></image><generator>RSS for Node</generator><lastBuildDate>Thu, 16 Apr 2026 13:20:17 GMT</lastBuildDate><atom:link href="http://direct.ecency.com/created/tensorboard/rss.xml" rel="self" type="application/rss+xml"/><item><title><![CDATA[Source that deep learning with mnist data]]></title><description><![CDATA[MNIST reads the data one-hot to create tansorboard data and stores the training results. %autosave 0 def reset_graph(seed=42): tf.reset_default_graph() tf.set_random_seed(seed) np.random.seed(seed) from]]></description><link>http://direct.ecency.com/tensorflow/@south-man/source-that-deep-learning-with-mnist-data</link><guid isPermaLink="true">http://direct.ecency.com/tensorflow/@south-man/source-that-deep-learning-with-mnist-data</guid><category><![CDATA[tensorflow]]></category><dc:creator><![CDATA[south-man]]></dc:creator><pubDate>Wed, 02 May 2018 09:53:57 GMT</pubDate><enclosure url="https://images.ecency.com/p/2gsjgna1uruvUuS7ndh9YqVwYGPLVszbFLwwpAYXZ1CgSdDTXFPsX1Ue7hRLNFVCiRndov5TpFQtQJ3njXMrkK5f9QoLXhxMpgpzhmH5jV4VY16uGA?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[mnist 데이터를 가지고 딥러닝하는 소스]]></title><description><![CDATA[mnist 데이터를 one-hot으로 읽어들여서 tansorboard 데이터를 만들고 훈련 결과를 저장합니다. %autosave 0 def reset_graph(seed=42): tf.reset_default_graph() tf.set_random_seed(seed) np.random.seed(seed) from]]></description><link>http://direct.ecency.com/deep-running/@south-man/mnist</link><guid isPermaLink="true">http://direct.ecency.com/deep-running/@south-man/mnist</guid><category><![CDATA[deep-running]]></category><dc:creator><![CDATA[south-man]]></dc:creator><pubDate>Wed, 02 May 2018 09:42:27 GMT</pubDate><enclosure url="https://images.ecency.com/p/2gsjgna1uruvUuS7ndh9YqVwYGPLVszbFLwwpAYXZ1CgSdDTXFPsX1Ue7hRLNFVCiRndov5TpFQtQJ3njXMrkK5f9QoLXhxMpgpzhmH5jV4VY16uGA?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[What happens when you apply Dropout to a bad initialized Deep Neural Network]]></title><description><![CDATA[Introduction: This is a post that explains a problem that I found during the development of Deep Neural Network (with Tensorflow) in order to do multi-label classification and the applicaton of the popular]]></description><link>http://direct.ecency.com/tensorflow/@alberduris/what-happens-when-you-apply-dropout-to-a-bad-initialized-deep-neural-network</link><guid isPermaLink="true">http://direct.ecency.com/tensorflow/@alberduris/what-happens-when-you-apply-dropout-to-a-bad-initialized-deep-neural-network</guid><category><![CDATA[tensorflow]]></category><dc:creator><![CDATA[alberduris]]></dc:creator><pubDate>Sat, 24 Mar 2018 14:15:15 GMT</pubDate><enclosure url="https://images.ecency.com/p/62PdCouTvNPDuXRaduVYiCb9hxbZWDcAb1acVYBWN5iXusz3hN5auNM3pAyzjVbS7EYHdcnGPWnyWhQnvMHKz32CzKKNDpgpD6BhRruMwyqhH7B?format=match&amp;mode=fit" length="0" type="false"/></item></channel></rss>