<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>霜庭小筑</title><description>一个简约低调、带有细腻 ACG 氛围的个人博客。</description><link>https://kaikaikk.com/</link><language>zh-CN</language><item><title>9.1 序列模型</title><link>https://kaikaikk.com/posts/d2l-9-1-sequence-models/</link><guid isPermaLink="true">https://kaikaikk.com/posts/d2l-9-1-sequence-models/</guid><pubDate>Sun, 30 Aug 2026 00:00:00 GMT</pubDate><category>深度学习</category><category>PyTorch</category><category>动手学深度学习</category><category>循环神经网络</category><category>序列模型</category><category>代码实现</category></item><item><title>12.5-12.6 多 GPU 训练</title><link>https://kaikaikk.com/posts/d2l-12-5-multi-gpu/</link><guid isPermaLink="true">https://kaikaikk.com/posts/d2l-12-5-multi-gpu/</guid><pubDate>Sat, 15 Aug 2026 00:00:00 GMT</pubDate><category>深度学习</category><category>PyTorch</category><category>动手学深度学习</category><category>多GPU</category><category>代码实现</category></item><item><title>7.7 稠密连接网络（DenseNet）</title><link>https://kaikaikk.com/posts/d2l-7-7-densenet/</link><guid isPermaLink="true">https://kaikaikk.com/posts/d2l-7-7-densenet/</guid><pubDate>Wed, 12 Aug 2026 00:00:00 GMT</pubDate><category>深度学习</category><category>PyTorch</category><category>动手学深度学习</category><category>卷积神经网络</category><category>DenseNet</category><category>代码实现</category></item><item><title>7.6 残差网络（ResNet）</title><link>https://kaikaikk.com/posts/d2l-7-6-resnet/</link><guid isPermaLink="true">https://kaikaikk.com/posts/d2l-7-6-resnet/</guid><pubDate>Mon, 10 Aug 2026 00:00:00 GMT</pubDate><category>深度学习</category><category>PyTorch</category><category>动手学深度学习</category><category>卷积神经网络</category><category>ResNet</category><category>代码实现</category></item><item><title>7.5 批量归一化</title><link>https://kaikaikk.com/posts/d2l-7-5-batch-norm/</link><guid isPermaLink="true">https://kaikaikk.com/posts/d2l-7-5-batch-norm/</guid><pubDate>Sun, 09 Aug 2026 00:00:00 GMT</pubDate><category>深度学习</category><category>PyTorch</category><category>动手学深度学习</category><category>卷积神经网络</category><category>批量归一化</category></item><item><title>7.4 含并行连结的网络（GoogLeNet）</title><link>https://kaikaikk.com/posts/d2l-7-4-googlenet/</link><guid isPermaLink="true">https://kaikaikk.com/posts/d2l-7-4-googlenet/</guid><pubDate>Sat, 08 Aug 2026 00:00:00 GMT</pubDate><category>深度学习</category><category>PyTorch</category><category>动手学深度学习</category><category>卷积神经网络</category><category>GoogLeNet</category><category>代码实现</category></item><item><title>7.2 使用块的网络（VGG）</title><link>https://kaikaikk.com/posts/d2l-7-2-vgg/</link><guid isPermaLink="true">https://kaikaikk.com/posts/d2l-7-2-vgg/</guid><pubDate>Fri, 07 Aug 2026 00:00:00 GMT</pubDate><category>深度学习</category><category>PyTorch</category><category>动手学深度学习</category><category>卷积神经网络</category><category>VGG</category><category>代码实现</category></item><item><title>7.3 网络中的网络（NiN）</title><link>https://kaikaikk.com/posts/d2l-7-3-nin/</link><guid isPermaLink="true">https://kaikaikk.com/posts/d2l-7-3-nin/</guid><pubDate>Fri, 07 Aug 2026 00:00:00 GMT</pubDate><category>深度学习</category><category>PyTorch</category><category>动手学深度学习</category><category>卷积神经网络</category><category>NiN</category><category>代码实现</category></item><item><title>7.1 AlexNet</title><link>https://kaikaikk.com/posts/d2l-7-1-alexnet/</link><guid isPermaLink="true">https://kaikaikk.com/posts/d2l-7-1-alexnet/</guid><pubDate>Thu, 06 Aug 2026 00:00:00 GMT</pubDate><category>深度学习</category><category>PyTorch</category><category>动手学深度学习</category><category>卷积神经网络</category><category>AlexNet</category><category>代码实现</category></item><item><title>6.6 LeNet</title><link>https://kaikaikk.com/posts/d2l-6-6-lenet/</link><guid isPermaLink="true">https://kaikaikk.com/posts/d2l-6-6-lenet/</guid><pubDate>Wed, 05 Aug 2026 00:00:00 GMT</pubDate><category>深度学习</category><category>PyTorch</category><category>动手学深度学习</category><category>卷积神经网络</category><category>LeNet</category><category>代码实现</category></item><item><title>6.2-6.5 卷积的一些基础代码</title><link>https://kaikaikk.com/posts/d2l-6-2-convolution-basics/</link><guid isPermaLink="true">https://kaikaikk.com/posts/d2l-6-2-convolution-basics/</guid><pubDate>Tue, 04 Aug 2026 00:00:00 GMT</pubDate><category>深度学习</category><category>PyTorch</category><category>动手学深度学习</category><category>卷积神经网络</category><category>代码实现</category></item><item><title>4.6 Dropout 的代码实现</title><link>https://kaikaikk.com/posts/d2l-4-6-dropout/</link><guid isPermaLink="true">https://kaikaikk.com/posts/d2l-4-6-dropout/</guid><pubDate>Sat, 25 Jul 2026 00:00:00 GMT</pubDate><category>深度学习</category><category>PyTorch</category><category>动手学深度学习</category><category>模型选择</category><category>正则化</category><category>代码实现</category></item><item><title>4.5 权重衰退的代码实现</title><link>https://kaikaikk.com/posts/d2l-4-5-weight-decay/</link><guid isPermaLink="true">https://kaikaikk.com/posts/d2l-4-5-weight-decay/</guid><pubDate>Sat, 25 Jul 2026 00:00:00 GMT</pubDate><category>深度学习</category><category>PyTorch</category><category>动手学深度学习</category><category>模型选择</category><category>正则化</category><category>代码实现</category></item><item><title>4.4 通过多项式拟合来探索过拟合与欠拟合</title><link>https://kaikaikk.com/posts/d2l-4-4-overfitting-underfitting/</link><guid isPermaLink="true">https://kaikaikk.com/posts/d2l-4-4-overfitting-underfitting/</guid><pubDate>Thu, 23 Jul 2026 00:00:00 GMT</pubDate><category>深度学习</category><category>PyTorch</category><category>动手学深度学习</category><category>模型选择</category><category>过拟合</category><category>代码实现</category></item><item><title>4.2-4.3 多层感知机的实现</title><link>https://kaikaikk.com/posts/d2l-4-2-mlp/</link><guid isPermaLink="true">https://kaikaikk.com/posts/d2l-4-2-mlp/</guid><pubDate>Wed, 22 Jul 2026 00:00:00 GMT</pubDate><category>深度学习</category><category>PyTorch</category><category>动手学深度学习</category><category>多层感知机</category><category>代码实现</category></item><item><title>3.6-3.7 Softmax 回归的实现</title><link>https://kaikaikk.com/posts/d2l-3-6-softmax-regression/</link><guid isPermaLink="true">https://kaikaikk.com/posts/d2l-3-6-softmax-regression/</guid><pubDate>Tue, 21 Jul 2026 00:00:00 GMT</pubDate><category>深度学习</category><category>PyTorch</category><category>动手学深度学习</category><category>Softmax回归</category><category>代码实现</category></item><item><title>3.2-3.3 线性回归的实现</title><link>https://kaikaikk.com/posts/d2l-3-2-linear-regression/</link><guid isPermaLink="true">https://kaikaikk.com/posts/d2l-3-2-linear-regression/</guid><pubDate>Tue, 21 Jul 2026 00:00:00 GMT</pubDate><category>深度学习</category><category>PyTorch</category><category>动手学深度学习</category><category>线性回归</category><category>代码实现</category></item><item><title>你好，泰拉大陆！——本站正式开张</title><link>https://kaikaikk.com/posts/hello-terra/</link><guid isPermaLink="true">https://kaikaikk.com/posts/hello-terra/</guid><pubDate>Tue, 21 Jul 2026 00:00:00 GMT</pubDate><category>公告</category><category>日常</category></item></channel></rss>