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面试必看 \u003c/h1\u003e\n\u003c/div\u003e\n\u003cdiv align=\"center\"\u003e\n\u003cdiv align=\"center\"\u003e\n\n[![GitHub stars](https://img.shields.io/github/stars/datawhalechina/daily-interview?style=for-the-badge\u0026logo=github)](https://github.com/datawhalechina/daily-interview/stargazers)\n[![GitHub forks](https://img.shields.io/github/forks/datawhalechina/daily-interview?style=for-the-badge\u0026logo=github)](https://github.com/datawhalechina/daily-interview/network)\n[![GitHub issues](https://img.shields.io/github/issues/datawhalechina/daily-interview?style=for-the-badge\u0026logo=github)](https://github.com/datawhalechina/daily-interview/issues)\n[![License](https://img.shields.io/badge/license-CC%20BY--NC--SA%204.0-lightgrey?style=for-the-badge)](http://creativecommons.org/licenses/by-nc-sa/4.0/)\n\n**每一个面试者面试之前必看一遍的小面经**\n\n[📖 在线阅读](https://datawhalechina.github.io/daily-interview/) | [🚀 快速开始](#使用指南) | [🤝 参与贡献](#招募)\n\n\u003c/div\u003e\n\n## 📖 项目背景\n\n在求职路上，我们经常面临这样的困扰：\n\n- 📚 **信息过载**：牛客网、知乎等平台虽然有海量面经，但往往大而散，难以高效利用\n- ⏰ **时间紧迫**：面试前临时抱佛脚，翻阅大量材料反而增加心理压力\n- 🎯 **缺乏重点**：不知道哪些是真正的高频考点，复习没有针对性\n\n**Daily Interview** 就是为了解决这些问题而生的！\n\n## 🎯 项目宗旨\n\n\u003e 💡 **核心理念**：不求大而全，但求精而准\n\n- ✅ **精选高频**：只收录面试中真正高频的知识点和题目\n- ✅ **快速复习**：面试前半天时间，温故而知新\n- ✅ **举一反三**：提供思路和方法，而非标准答案\n- ❌ **不求全面**：知识在更新迭代，我们专注核心内容\n- ❌ **不做补习**：每个人短板不同，需要自主完善知识体系\n\n## 📚 内容体系\n\n\u003cdiv align=\"center\"\u003e\n\u003cimg src=\"https://github.com/datawhalechina/daily-interview/blob/master/content.png\" width=\"500px\" alt=\"内容体系图\"\u003e\n\u003c/div\u003e\n\n### 🗂️ 知识模块\n\n| 模块 | 内容 | 适用岗位 |\n|------|------|----------|\n| 🧮 **算法基础** | 数据结构、算法思想、复杂度分析 | 🌟 所有技术岗位 |\n| 💻 **编程语言** | Java、JavaScript、Python等 | 开发岗、算法岗 |\n| 🔧 **计算机基础** | 操作系统、网络、数据库、数学 | 🌟 所有技术岗位 |\n| 🤖 **AI算法** | 机器学习、深度学习、NLP、CV | 算法岗、AI工程师 |\n| 🏗️ **系统设计** | 分布式系统、高并发架构 | 高级开发岗 |\n| 🛠️ **开发技术** | 前端、后端、大数据技术栈 | 开发岗 |\n| 📋 **项目经验** | 项目介绍、技术难点、优化方案 | 🌟 所有岗位 |\n| 🗣️ **行为面试** | 自我介绍、职业规划、团队协作 | 🌟 所有岗位 |\n\n### 📊 Star History\n\n\u003cdiv align=\"center\"\u003e\n\n[![Star History Chart](https://api.star-history.com/svg?repos=datawhalechina/daily-interview\u0026type=Date\u0026theme=dark)](https://star-history.com/#datawhalechina/daily-interview\u0026Date)\n\n\u003c/div\u003e\n\n\n## 🚀 使用指南\n\n### 📖 在线阅读\n访问 [https://datawhalechina.github.io/daily-interview/](https://datawhalechina.github.io/daily-interview/) 获得最佳阅读体验。\n\n### 🎯 按岗位复习\n\n#### 🤖 算法岗位\n```\n重点模块：AI算法 + 数据结构与算法\n辅助模块：数学基础 + 计算机基础\n复习时间：面试前1-2天重点复习\n```\n\n#### 💻 开发岗位\n```\n重点模块：开发技术 + 数据结构与算法 + 计算机基础\n辅助模块：系统设计（高级岗位）\n复习时间：面试前半天快速过一遍\n```\n\n#### 📋 通用准备\n```\n必备模块：项目经验 + 行为面试\n适用对象：所有技术岗位\n建议：提前准备，形成自己的表达模板\n```\n\n### 💡 使用技巧\n\n1. **🔖 收藏重点**：标记自己薄弱的知识点，重点复习\n2. **🔄 反复练习**：算法题要动手实现，不能只看不练\n3. **🗣️ 模拟面试**：找朋友或同事进行模拟面试练习\n4. **📝 个人笔记**：基于本项目内容，整理自己的面试笔记\n\n\n## 🤝 招募贡献者\n\n我们欢迎所有对面试准备有经验的朋友参与贡献！\n\n### 🎯 我们需要你的帮助\n\n- 📝 **内容贡献**：补充面试题目、优化答案解析\n- 🐛 **问题反馈**：发现错误或改进建议\n- 🌐 **技术支持**：网站优化、功能开发\n- 📚 **经验分享**：分享面试经验和技巧\n\n### 📧 联系方式\n\n- **项目负责人**：[@muxiaoxiong](https://github.com/muxiaoxiong)\n- **Issue**：[GitHub Issues](https://github.com/datawhalechina/daily-interview/issues)\n- **讨论**：[GitHub Discussions](https://github.com/datawhalechina/daily-interview/discussions)\n\n## 👥 贡献者\n\n感谢所有为这个项目做出贡献的朋友们！\n\n### 🏆 特别贡献者\n\n- **[@muxiaoxiong](https://github.com/muxiaoxiong)** - 项目负责人，主要维护者\n- **[@heitao](https://github.com/heitao)** - 项目发起人，核心内容贡献者 (66+ commits)\n- **[@xiaorrancs](https://github.com/xiaorrancs)** - 主要内容贡献者，算法题目整理 (39+ commits)\n- **[@1985312383](https://github.com/1985312383)** - VitePress迁移，网站重构，内容整理\n\n## 📅 更新日志\n\n### 🎉 2025-08-26 - 重大更新\n- ✨ **技术栈升级**：从Docsify迁移到VitePress，构建速度提升99%+\n- 🎨 **界面重构**：全新的双侧边栏设计，支持VS Code Dark主题\n- 🔍 **搜索优化**：新增本地搜索功能，支持中文搜索\n- 📱 **响应式设计**：完美适配各种屏幕尺寸\n- 🧮 **数学公式**：支持LaTeX数学公式渲染\n- 🗂️ **内容重组**：系统性重组所有文档，修复乱码问题\n- 🖼️ **图片优化**：统一图片路径，确保所有图片正常显示\n- 💻 **代码高亮**：为所有代码块添加语言标识，提升阅读体验\n- 🚀 **部署优化**：更新GitHub Actions，支持自动化部署\n- 📋 **导航重构**：从Docsify的侧边栏导航升级为VitePress的双侧边栏设计\n\n### 📚 历史版本\n- **2025-07-15**：新增大语言模型相关面试资料\n\n\n## 🌟 关注我们\n\n\u003cdiv align=\"center\"\u003e\n\n### 📱 微信公众号\n扫描下方二维码关注 **Datawhale** 公众号，获取更多学习资源\n\n\u003cimg src=\"https://raw.githubusercontent.com/datawhalechina/pumpkin-book/master/res/qrcode.jpeg\" width=\"200\" height=\"200\" alt=\"Datawhale公众号\"\u003e\n\n### 🔗 相关链接\n\n[![GitHub](https://img.shields.io/badge/GitHub-datawhalechina-black?style=for-the-badge\u0026logo=github)](https://github.com/datawhalechina)\n[![Website](https://img.shields.io/badge/Website-datawhale.cn-blue?style=for-the-badge\u0026logo=internet-explorer)](https://datawhale.cn)\n\n\u003c/div\u003e\n\n## 📄 开源协议\n\n\u003cdiv align=\"center\"\u003e\n\n\u003ca rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-sa/4.0/\"\u003e\n\u003cimg alt=\"知识共享许可协议\" style=\"border-width:0\" src=\"https://img.shields.io/badge/license-CC%20BY--NC--SA%204.0-lightgrey?style=for-the-badge\" /\u003e\n\u003c/a\u003e\n\n本作品采用 [知识共享署名-非商业性使用-相同方式共享 4.0 国际许可协议](http://creativecommons.org/licenses/by-nc-sa/4.0/) 进行许可。\n\n**这意味着你可以：**\n- ✅ **分享** - 在任何媒介以任何形式复制、发行本作品\n- ✅ **演绎** - 修改、转换或以本作品为基础进行创作\n\n**但需要遵循以下条件：**\n- 📝 **署名** - 必须给出适当的署名\n- 🚫 **非商业性使用** - 不得用于商业目的\n- 🔄 **相同方式共享** - 如果修改、转换或以本作品为基础进行创作，必须基于与原先许可协议相同的许可协议分布\n\n\u003c/div\u003e\n\n---\n\n\u003cdiv align=\"center\"\u003e\n\n**⭐ 如果这个项目对你有帮助，请给我们一个Star！⭐**\n\n**💪 祝愿所有使用这份面经的朋友都能拿到心仪的offer！💪**\n\n\u003c/div\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdatawhalechina%2Fdaily-interview","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdatawhalechina%2Fdaily-interview","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdatawhalechina%2Fdaily-interview/lists"}