<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[Mono05的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/Mono05</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; Mono05]]></copyright><item><title><![CDATA[编译原理第一次实验]]></title><link>https://blog.youkuaiyun.com/Mono05/article/details/146310839</link><guid>https://blog.youkuaiyun.com/Mono05/article/details/146310839</guid><author>Mono05</author><pubDate>Mon, 17 Mar 2025 11:30:00 +0800</pubDate><description><![CDATA[从文本文件中读入测试源代码，根据状态转换图，分析出一个单词，、根据以下的正规式，编制正规文法，画出状态图；常数为无符号整形数；、根据状态图，设计词法分析函数。） 以二元式形式输出单词。、编写测试程序，反复调。，输出单词种别和属性。]]></description><category></category></item><item><title><![CDATA[NLP实验二]]></title><link>https://blog.youkuaiyun.com/Mono05/article/details/146091690</link><guid>https://blog.youkuaiyun.com/Mono05/article/details/146091690</guid><author>Mono05</author><pubDate>Fri, 07 Mar 2025 11:39:25 +0800</pubDate><description><![CDATA[【代码】NLP实验二。]]></description><category></category></item><item><title><![CDATA[深度学习第十一次作业（LSTM反向推导和算子实现）]]></title><link>https://blog.youkuaiyun.com/Mono05/article/details/144704830</link><guid>https://blog.youkuaiyun.com/Mono05/article/details/144704830</guid><author>Mono05</author><pubDate>Tue, 24 Dec 2024 23:12:11 +0800</pubDate><description><![CDATA[1、使用Numpy实现LSTM算子。2、使用nn.LSTMCell实现。3、使用nn.LSTM实现。]]></description><category></category></item><item><title><![CDATA[深度学习第十七次实验（优化算法比较）]]></title><link>https://blog.youkuaiyun.com/Mono05/article/details/144648557</link><guid>https://blog.youkuaiyun.com/Mono05/article/details/144648557</guid><author>Mono05</author><pubDate>Sun, 22 Dec 2024 16:45:44 +0800</pubDate><description><![CDATA[1、不同优化算法的2D可视化实验。2、不同优化算法的3D可视化实验。2）不同优化算法的3D轨迹图。3、复现CS231经典动画。]]></description><category></category></item><item><title><![CDATA[深度学习第十六次实验（双向LSTM模型进行文本分类）]]></title><link>https://blog.youkuaiyun.com/Mono05/article/details/144509048</link><guid>https://blog.youkuaiyun.com/Mono05/article/details/144509048</guid><author>Mono05</author><pubDate>Mon, 16 Dec 2024 14:55:12 +0800</pubDate><description><![CDATA[【代码】深度学习第十六次实验（双向LSTM模型进行文本分类）]]></description><category></category></item><item><title><![CDATA[深度学习第十五次实验（梯度爆炸问题、LSTM的长程依赖能力）]]></title><link>https://blog.youkuaiyun.com/Mono05/article/details/144354824</link><guid>https://blog.youkuaiyun.com/Mono05/article/details/144354824</guid><author>Mono05</author><pubDate>Mon, 09 Dec 2024 18:32:52 +0800</pubDate><description><![CDATA[3、LSTM的长程依赖能力。]]></description><category></category></item><item><title><![CDATA[深度学习第十四次实验（循环神经网络（1）——SRN)]]></title><link>https://blog.youkuaiyun.com/Mono05/article/details/144273620</link><guid>https://blog.youkuaiyun.com/Mono05/article/details/144273620</guid><author>Mono05</author><pubDate>Thu, 05 Dec 2024 18:59:32 +0800</pubDate><description><![CDATA[【代码】深度学习第十四次实验（循环神经网络（1）——SRN)]]></description><category></category></item><item><title><![CDATA[深度学习第十三次实验（ResNet网络对CIFAR-10数据集的分类）]]></title><link>https://blog.youkuaiyun.com/Mono05/article/details/144211729</link><guid>https://blog.youkuaiyun.com/Mono05/article/details/144211729</guid><author>Mono05</author><pubDate>Tue, 03 Dec 2024 12:15:20 +0800</pubDate><description><![CDATA[【代码】深度学习第十三次实验（ResNet网络对CIFAR-10数据集的分类）]]></description><category></category></item><item><title><![CDATA[深度学习第九次作业（SRN、Seq2Seq）]]></title><link>https://blog.youkuaiyun.com/Mono05/article/details/144145794</link><guid>https://blog.youkuaiyun.com/Mono05/article/details/144145794</guid><author>Mono05</author><pubDate>Fri, 29 Nov 2024 21:08:47 +0800</pubDate><description><![CDATA[NNDL 作业9 RNN-SRN简单循环神经网络 [HBU]_简单循环网络-优快云博客。2、增加激活函数tanh。]]></description><category></category></item><item><title><![CDATA[深度学习第十二次实验（ResNet残差网络实现对MNIST数据集的识别）]]></title><link>https://blog.youkuaiyun.com/Mono05/article/details/143993119</link><guid>https://blog.youkuaiyun.com/Mono05/article/details/143993119</guid><author>Mono05</author><pubDate>Sat, 23 Nov 2024 15:23:42 +0800</pubDate><description><![CDATA[2、无残差连接的ResNet网络模型。3、有残差连接的ResNet网络模型。]]></description><category></category></item><item><title><![CDATA[深度学习第十一次实验（LeNet实现MNIST数据集的识别）]]></title><link>https://blog.youkuaiyun.com/Mono05/article/details/143858083</link><guid>https://blog.youkuaiyun.com/Mono05/article/details/143858083</guid><author>Mono05</author><pubDate>Mon, 18 Nov 2024 15:16:31 +0800</pubDate><description><![CDATA[2、模型训练、评价与测试。]]></description><category></category></item><item><title><![CDATA[深度学习第十次实验（卷积神经网络（1））]]></title><link>https://blog.youkuaiyun.com/Mono05/article/details/143666778</link><guid>https://blog.youkuaiyun.com/Mono05/article/details/143666778</guid><author>Mono05</author><pubDate>Sun, 10 Nov 2024 21:07:02 +0800</pubDate><description><![CDATA[6、分别用自定义卷积算子和torch.nn.Conv2d()编程实现下面的卷积运算。2、自定义带步长和零填充的二维卷积算子。5、自定义卷积层算子和汇聚层算子。4、RGB图像的边缘检测。1、自定义二维卷积算子。3、实现图像边缘检测。]]></description><category></category></item><item><title><![CDATA[深度学习第七次作业（卷积2）]]></title><link>https://blog.youkuaiyun.com/Mono05/article/details/143529337</link><guid>https://blog.youkuaiyun.com/Mono05/article/details/143529337</guid><author>Mono05</author><pubDate>Tue, 05 Nov 2024 21:53:04 +0800</pubDate><description><![CDATA[1、参考资料代码复现。2、重新设计网络结构。]]></description><category></category></item><item><title><![CDATA[深度学习第八次实验（前馈神经网络-优化问题）]]></title><link>https://blog.youkuaiyun.com/Mono05/article/details/143495069</link><guid>https://blog.youkuaiyun.com/Mono05/article/details/143495069</guid><author>Mono05</author><pubDate>Mon, 04 Nov 2024 21:55:17 +0800</pubDate><description><![CDATA[3、死亡ReLU问题。]]></description><category></category></item><item><title><![CDATA[深度学习第九次实验（前馈神经网络-鸢尾花分类）]]></title><link>https://blog.youkuaiyun.com/Mono05/article/details/143494962</link><guid>https://blog.youkuaiyun.com/Mono05/article/details/143494962</guid><author>Mono05</author><pubDate>Mon, 04 Nov 2024 21:48:47 +0800</pubDate><description><![CDATA[【代码】深度学习第九次实验（前馈神经网络-鸢尾花分类）]]></description><category></category></item><item><title><![CDATA[深度学习第七次实验（前馈神经网络-自动梯度计算）]]></title><link>https://blog.youkuaiyun.com/Mono05/article/details/143257519</link><guid>https://blog.youkuaiyun.com/Mono05/article/details/143257519</guid><author>Mono05</author><pubDate>Sat, 26 Oct 2024 18:22:22 +0800</pubDate><description><![CDATA[3、自定义隐藏层层数和每个隐藏层中的神经元个数，尝试找到最优超参数完成二分类。可以适当修改数据集，便于探索超参数。2、增加一个3个神经元的隐藏层，再次实现二分类，并与1做对比。1、使用pytorch的预定义算子来重新实现二分类任务。]]></description><category></category></item><item><title><![CDATA[深度学习第六次作业（卷积）]]></title><link>https://blog.youkuaiyun.com/Mono05/article/details/143243959</link><guid>https://blog.youkuaiyun.com/Mono05/article/details/143243959</guid><author>Mono05</author><pubDate>Fri, 25 Oct 2024 21:22:13 +0800</pubDate><description><![CDATA[2、灰度图的边缘检测、锐化、模糊。1、编程实现几个基础的卷积核。]]></description><category></category></item><item><title><![CDATA[深度学习第六次实验（前馈神经网络-二分类)]]></title><link>https://blog.youkuaiyun.com/Mono05/article/details/143161260</link><guid>https://blog.youkuaiyun.com/Mono05/article/details/143161260</guid><author>Mono05</author><pubDate>Tue, 22 Oct 2024 16:14:50 +0800</pubDate><description><![CDATA[【代码】深度学习第六次实验（前馈神经网络-二分类)]]></description><category></category></item><item><title><![CDATA[深度学习第五次实验（前馈神经网络-神经元 激活函数）]]></title><link>https://blog.youkuaiyun.com/Mono05/article/details/142927242</link><guid>https://blog.youkuaiyun.com/Mono05/article/details/142927242</guid><author>Mono05</author><pubDate>Mon, 14 Oct 2024 20:01:04 +0800</pubDate><description><![CDATA[2、torch.nn.Linear（）函数。3、Logistic函数、Tanh函数。4、ReLU、带泄露的ReLU的函数。1、使用Pytorch计算活性值。]]></description><category></category></item><item><title><![CDATA[深度学习作业4-BP算法]]></title><link>https://blog.youkuaiyun.com/Mono05/article/details/142771972</link><guid>https://blog.youkuaiyun.com/Mono05/article/details/142771972</guid><author>Mono05</author><pubDate>Tue, 08 Oct 2024 23:35:21 +0800</pubDate><description><![CDATA[2、PyTorch程序。]]></description><category></category></item></channel></rss>