https://linkedbus.com/sitetag/%E9%85%8D%E5%A5%97%E4%BB%A3%E7%A0%81/ Recent content in 配套代码 on 链氪巴士 Hugo -- gohugo.io zh-CN Mon, 09 Dec 2024 14:43:53 +0800 https://linkedbus.com/sites/22468.html Fri, 06 Dec 2024 00:00:00 +0800 https://linkedbus.com/sites/22468.html <img src="https://linkedbus.com/uploads/linkedbus.com/favicon/1733218100-images.png" alt="Featured image of post antispider:Python3反爬虫原理与绕过实战配套代码" /><p class="site-visit"><a href="https://github.com/asyncins/antispider" target="_blank" rel="noopener nofollow">访问官网 →</a></p> <h2 id="antispiderpython3反爬虫原理与绕过实战配套代码"><a href="#antispiderpython3%e5%8f%8d%e7%88%ac%e8%99%ab%e5%8e%9f%e7%90%86%e4%b8%8e%e7%bb%95%e8%bf%87%e5%ae%9e%e6%88%98%e9%85%8d%e5%a5%97%e4%bb%a3%e7%a0%81" class="header-anchor"></a>antispider:《Python3反爬虫原理与绕过实战》配套代码 </h2><h3 id="项目简介"><a href="#%e9%a1%b9%e7%9b%ae%e7%ae%80%e4%bb%8b" class="header-anchor"></a>项目简介 </h3><p>antispider是书籍《Python3反爬虫原理与绕过实战》的配套代码。该项目除了书中第1章环境安装配置和第3章爬虫与反爬虫之外，其他章节涉及的Python代码均有记录。代码包含了WEB网站的构成和页面渲染、信息校验型反爬虫、动态渲染反爬虫等多方面相关内容。同时代码经过运行验证，与书本所述相同。</p> https://linkedbus.com/sites/22413.html Fri, 06 Dec 2024 00:00:00 +0800 https://linkedbus.com/sites/22413.html <img src="https://linkedbus.com/uploads/linkedbus.com/favicon/1733218100-images.png" alt="Featured image of post PyQt5-PyQt5快速开发与实战配套代码" /><p class="site-visit"><a href="https://github.com/cxinping/PyQt5" target="_blank" rel="noopener nofollow">访问官网 →</a></p> <h2 id="项目标题pyqt5-pyqt5快速开发与实战配套代码"><a href="#%e9%a1%b9%e7%9b%ae%e6%a0%87%e9%a2%98pyqt5-pyqt5%e5%bf%ab%e9%80%9f%e5%bc%80%e5%8f%91%e4%b8%8e%e5%ae%9e%e6%88%98%e9%85%8d%e5%a5%97%e4%bb%a3%e7%a0%81" class="header-anchor"></a>项目标题：PyQt5-《PyQt5快速开发与实战》配套代码 </h2><h3 id="项目简介"><a href="#%e9%a1%b9%e7%9b%ae%e7%ae%80%e4%bb%8b" class="header-anchor"></a>项目简介 </h3><p>这是《PyQt5快速开发与实战》的配套代码。PyQt5近年来发展迅速，但缺乏针对新手的系统学习教材，网络上的学习案例知识结构零碎。本书作者结合自身学习和实战经验编写，代码库结构基于PyQt5.9版本，包含11个章节相关的示例代码，涵盖从入门到实战的各个知识点。</p> https://linkedbus.com/sites/21523.html Fri, 06 Dec 2024 00:00:00 +0800 https://linkedbus.com/sites/21523.html <img src="https://linkedbus.com/uploads/linkedbus.com/favicon/1733218100-images.png" alt="Featured image of post PyTorch_Tutorial：Pytorch模型训练实用教程配套代码" /><p class="site-visit"><a href="https://github.com/TingsongYu/PyTorch_Tutorial" target="_blank" rel="noopener nofollow">访问官网 →</a></p> <h2 id="github项目名pytorch_tutorialpytorch模型训练实用教程配套代码"><a href="#github%e9%a1%b9%e7%9b%ae%e5%90%8dpytorch_tutorialpytorch%e6%a8%a1%e5%9e%8b%e8%ae%ad%e7%bb%83%e5%ae%9e%e7%94%a8%e6%95%99%e7%a8%8b%e9%85%8d%e5%a5%97%e4%bb%a3%e7%a0%81" class="header-anchor"></a>【Github】项目名：PyTorch_Tutorial：《Pytorch模型训练实用教程》配套代码 </h2><h3 id="项目简介"><a href="#%e9%a1%b9%e7%9b%ae%e7%ae%80%e4%bb%8b" class="header-anchor"></a>项目简介 </h3><p>此项目为《Pytorch模型训练实用教程》中的配套代码。该教程已推出第二版且已开源（https://tingsongyu.github.io/PyTorch-Tutorial-2nd/），第二版新增丰富的深度学习应用案例和推理部署框架，涵盖CV、NLP和LLM的十多个实战项目以及ONNX和TensorRT的教程。代码在win10 64位+python3.5+pytorch==0.4.0和mac+python3.6+pytorch==0.4.1/pytorch==1.0.0这两种环境下测试过。</p>