<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[ygl_9913的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/ygl_9913</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; ygl_9913]]></copyright><item><title><![CDATA[1.14 梯度检验应用的注意事项-深度学习第二课《改善深层神经网络》-Stanford吴恩达教授]]></title><link>https://blog.youkuaiyun.com/ygl_9913/article/details/130336760</link><guid>https://blog.youkuaiyun.com/ygl_9913/article/details/130336760</guid><author>ygl_9913</author><pubDate>Mon, 24 Apr 2023 11:12:10 +0800</pubDate><description><![CDATA[2_1.14]]></description><category></category></item><item><title><![CDATA[1.13 梯度检验-深度学习第二课《改善深层神经网络》-Stanford吴恩达教授]]></title><link>https://blog.youkuaiyun.com/ygl_9913/article/details/130336061</link><guid>https://blog.youkuaiyun.com/ygl_9913/article/details/130336061</guid><author>ygl_9913</author><pubDate>Mon, 24 Apr 2023 10:05:38 +0800</pubDate><description><![CDATA[梯度检验帮我们节省了很多时间，也多次帮我发现实施过程中的，接下来，我们看看如何利用它来调试或检验的实施是否正确。在实施神经网络时，我经常需要执行foreprop和backprop，然后我可能发现这个梯度检验有一个相对较大的值，我会怀疑存在bug，然后开始调试，调试，调试，调试一段时间后，我得到一个很小的梯度检验值，现在我可以很自信的说，神经网络实施是正确的。现在你已经了解了梯度检验的工作原理，它帮助我在神经网络实施中发现了很多bug，希望它对你也有所帮助。]]></description><category></category></item><item><title><![CDATA[1.12 梯度的数值逼近-深度学习第二课《改善深层神经网络》-Stanford吴恩达教授]]></title><link>https://blog.youkuaiyun.com/ygl_9913/article/details/130335681</link><guid>https://blog.youkuaiyun.com/ygl_9913/article/details/130335681</guid><author>ygl_9913</author><pubDate>Mon, 24 Apr 2023 09:49:24 +0800</pubDate><description><![CDATA[2_1.12]]></description><category></category></item><item><title><![CDATA[1.7 理解 Dropout-深度学习第二课《改善深层神经网络》-Stanford吴恩达教授]]></title><link>https://blog.youkuaiyun.com/ygl_9913/article/details/130067513</link><guid>https://blog.youkuaiyun.com/ygl_9913/article/details/130067513</guid><author>ygl_9913</author><pubDate>Mon, 10 Apr 2023 21:24:48 +0800</pubDate><description><![CDATA[2_1.7]]></description><category></category></item><item><title><![CDATA[1.6 Dropout 正则化-深度学习第二课《改善深层神经网络》-Stanford吴恩达教授]]></title><link>https://blog.youkuaiyun.com/ygl_9913/article/details/130064793</link><guid>https://blog.youkuaiyun.com/ygl_9913/article/details/130064793</guid><author>ygl_9913</author><pubDate>Mon, 10 Apr 2023 17:45:45 +0800</pubDate><description><![CDATA[2_1.6]]></description><category></category></item><item><title><![CDATA[核函数Kernel Function的学习笔记]]></title><link>https://blog.youkuaiyun.com/ygl_9913/article/details/129930783</link><guid>https://blog.youkuaiyun.com/ygl_9913/article/details/129930783</guid><author>ygl_9913</author><pubDate>Mon, 03 Apr 2023 15:31:48 +0800</pubDate><description><![CDATA[学习笔记]]></description><category></category></item><item><title><![CDATA[求解为什么插入排序失效？奇怪的现象，为什么a[i]不会更新呢？]]></title><link>https://blog.youkuaiyun.com/ygl_9913/article/details/129557040</link><guid>https://blog.youkuaiyun.com/ygl_9913/article/details/129557040</guid><author>ygl_9913</author><pubDate>Wed, 15 Mar 2023 15:28:32 +0800</pubDate><description><![CDATA[一个蓝桥杯的题目，我想用快排从小到大排序，可是出错]]></description><category></category></item><item><title><![CDATA[4.6 前向和反向传播-深度学习-Stanford吴恩达教授]]></title><link>https://blog.youkuaiyun.com/ygl_9913/article/details/129520560</link><guid>https://blog.youkuaiyun.com/ygl_9913/article/details/129520560</guid><author>ygl_9913</author><pubDate>Tue, 14 Mar 2023 11:57:50 +0800</pubDate><description><![CDATA[笔记]]></description><category></category></item><item><title><![CDATA[3.1 神经网络概览-深度学习-Stanford吴恩达教授]]></title><link>https://blog.youkuaiyun.com/ygl_9913/article/details/128993547</link><guid>https://blog.youkuaiyun.com/ygl_9913/article/details/128993547</guid><author>ygl_9913</author><pubDate>Mon, 13 Feb 2023 16:13:49 +0800</pubDate><description><![CDATA[笔记]]></description><category></category></item><item><title><![CDATA[2.18 Logistic 损失函数的解释-深度学习-Stanford吴恩达教授]]></title><link>https://blog.youkuaiyun.com/ygl_9913/article/details/128984637</link><guid>https://blog.youkuaiyun.com/ygl_9913/article/details/128984637</guid><author>ygl_9913</author><pubDate>Sat, 11 Feb 2023 21:15:32 +0800</pubDate><description><![CDATA[笔记]]></description><category></category></item><item><title><![CDATA[2.16 关于 Python Numpy 的说明-深度学习-Stanford吴恩达教授]]></title><link>https://blog.youkuaiyun.com/ygl_9913/article/details/128976230</link><guid>https://blog.youkuaiyun.com/ygl_9913/article/details/128976230</guid><author>ygl_9913</author><pubDate>Fri, 10 Feb 2023 21:39:09 +0800</pubDate><description><![CDATA[视频]]></description><category></category></item><item><title><![CDATA[2.15 Python 中的广播-深度学习-Stanford吴恩达教授]]></title><link>https://blog.youkuaiyun.com/ygl_9913/article/details/128969632</link><guid>https://blog.youkuaiyun.com/ygl_9913/article/details/128969632</guid><author>ygl_9913</author><pubDate>Fri, 10 Feb 2023 15:30:29 +0800</pubDate><description><![CDATA[笔记]]></description><category></category></item><item><title><![CDATA[2.14 向量化 Logistic 回归的梯度输出-深度学习-Stanford吴恩达教授]]></title><link>https://blog.youkuaiyun.com/ygl_9913/article/details/128966860</link><guid>https://blog.youkuaiyun.com/ygl_9913/article/details/128966860</guid><author>ygl_9913</author><pubDate>Fri, 10 Feb 2023 14:27:09 +0800</pubDate><description><![CDATA[视频]]></description><category></category></item><item><title><![CDATA[2.13 向量化 Logistic 回归-深度学习-Stanford吴恩达教授]]></title><link>https://blog.youkuaiyun.com/ygl_9913/article/details/128955218</link><guid>https://blog.youkuaiyun.com/ygl_9913/article/details/128955218</guid><author>ygl_9913</author><pubDate>Thu, 09 Feb 2023 18:15:11 +0800</pubDate><description><![CDATA[视频笔记]]></description><category></category></item><item><title><![CDATA[2.12 向量化更多例子-深度学习-Stanford吴恩达教授]]></title><link>https://blog.youkuaiyun.com/ygl_9913/article/details/128952234</link><guid>https://blog.youkuaiyun.com/ygl_9913/article/details/128952234</guid><author>ygl_9913</author><pubDate>Thu, 09 Feb 2023 16:16:57 +0800</pubDate><description><![CDATA[视频笔记]]></description><category></category></item><item><title><![CDATA[2.11 向量化-深度学习-Stanford吴恩达教授]]></title><link>https://blog.youkuaiyun.com/ygl_9913/article/details/128950867</link><guid>https://blog.youkuaiyun.com/ygl_9913/article/details/128950867</guid><author>ygl_9913</author><pubDate>Thu, 09 Feb 2023 14:17:26 +0800</pubDate><description><![CDATA[视频笔记]]></description><category></category></item><item><title><![CDATA[2.10 m 个样本的梯度下降-深度学习-Stanford吴恩达教授]]></title><link>https://blog.youkuaiyun.com/ygl_9913/article/details/128935927</link><guid>https://blog.youkuaiyun.com/ygl_9913/article/details/128935927</guid><author>ygl_9913</author><pubDate>Wed, 08 Feb 2023 16:43:31 +0800</pubDate><description><![CDATA[视频笔记]]></description><category></category></item><item><title><![CDATA[2.9 Logistic 回归的梯度下降法-深度学习-Stanford吴恩达教授]]></title><link>https://blog.youkuaiyun.com/ygl_9913/article/details/128926514</link><guid>https://blog.youkuaiyun.com/ygl_9913/article/details/128926514</guid><author>ygl_9913</author><pubDate>Wed, 08 Feb 2023 14:11:09 +0800</pubDate><description><![CDATA[视频笔记]]></description><category></category></item><item><title><![CDATA[2.8 计算图的导数计算-深度学习-Stanford吴恩达教授]]></title><link>https://blog.youkuaiyun.com/ygl_9913/article/details/128923839</link><guid>https://blog.youkuaiyun.com/ygl_9913/article/details/128923839</guid><author>ygl_9913</author><pubDate>Tue, 07 Feb 2023 20:31:14 +0800</pubDate><description><![CDATA[视频笔记]]></description><category></category></item><item><title><![CDATA[2.7 计算图-深度学习-Stanford吴恩达教授]]></title><link>https://blog.youkuaiyun.com/ygl_9913/article/details/128921990</link><guid>https://blog.youkuaiyun.com/ygl_9913/article/details/128921990</guid><author>ygl_9913</author><pubDate>Tue, 07 Feb 2023 17:09:40 +0800</pubDate><description><![CDATA[视频笔记]]></description><category></category></item></channel></rss>