<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>深度学习 - 分类 - Aphros的博客</title><link>https://blog.papergate.top/categories/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/</link><description>我的个人博客</description><generator>Hugo 0.161.1 &amp; FixIt v0.4.0-alpha.3-20251225101113-8ffb9a95</generator><language>zh-CN</language><lastBuildDate>Tue, 06 Jan 2026 15:23:11 +0800</lastBuildDate><atom:link href="https://blog.papergate.top/categories/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/index.xml" rel="self" type="application/rss+xml"/><item><title>Pytorch 卷积神经网络</title><link>https://blog.papergate.top/posts/pytorch-%E5%8D%B7%E7%A7%AF%E7%A5%9E%E7%BB%8F%E7%BD%91%E7%BB%9C/</link><pubDate>Sun, 04 Jan 2026 09:44:47 +0800</pubDate><guid>https://blog.papergate.top/posts/pytorch-%E5%8D%B7%E7%A7%AF%E7%A5%9E%E7%BB%8F%E7%BD%91%E7%BB%9C/</guid><category domain="https://blog.papergate.top/categories/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/">深度学习</category><description>在本文节中，使用卷积神经网络，对上一篇的 Fashion-Minist 数据集再次进行分类。</description></item><item><title>Pytorch 全连接神经网络</title><link>https://blog.papergate.top/posts/pytorch-%E5%85%A8%E8%BF%9E%E6%8E%A5%E7%A5%9E%E7%BB%8F%E7%BD%91%E7%BB%9C/</link><pubDate>Sat, 03 Jan 2026 21:41:39 +0800</pubDate><guid>https://blog.papergate.top/posts/pytorch-%E5%85%A8%E8%BF%9E%E6%8E%A5%E7%A5%9E%E7%BB%8F%E7%BD%91%E7%BB%9C/</guid><category domain="https://blog.papergate.top/categories/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/">深度学习</category><description>在本文中，使用全连接神经网络进行简单的分类和回归。</description></item><item><title>Pytorch 张量</title><link>https://blog.papergate.top/posts/pytorch-%E5%BC%A0%E9%87%8F/</link><pubDate>Tue, 30 Dec 2025 14:46:16 +0800</pubDate><guid>https://blog.papergate.top/posts/pytorch-%E5%BC%A0%E9%87%8F/</guid><category domain="https://blog.papergate.top/categories/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/">深度学习</category><description>本文的内容主要来自《&lt;a href="https://github.com/d2l-ai/d2l-zh" target="_blank" rel="external nofollow noopener noreferrer"&gt;动手学深度学习&lt;/a&gt;》和《&lt;a href="https://github.com/datawhalechina/thorough-pytorch" target="_blank" rel="external nofollow noopener noreferrer"&gt;深入浅出 Pytorch&lt;/a&gt;》, 在本系列中，不会涉及过多的深度学习相关知识，主要聚焦于如何使用 Pytorch 进行深度学习。</description></item></channel></rss>