Comprehensive notes for various CS courses offered at Carnegie Mellon University are designed as an invaluable resource for students and educators alike.

Born out of a need to consolidate and share rich academic knowledge, this repository aims to provide detailed and accessible notes covering a wide range of subjects taught at CMU. From Computer Systems to Machine Learning and Artificial Intelligence, the notes encapsulate key concepts, lecture insights, and study guides. This resource is ideal for CMU students seeking supplementary study material, educators looking for teaching aids, and self-learners interested in the curriculum.

• 10-601 Machine Learning
• 14-736 Distributed Systems
• 14-741 Information Security
• 15-513 Computer Systems

• 10-605 Machine Learning with Large Datasets
• 10-617 Intermediate Deep Learning
• 10-623 Generative AI
• 10-725 Convex Optimization
• 11-742 Search Engines
• 15-619 Cloud Computing
• 15-641 Computer Networks
• 15-645 Database Systems
• 18-746 Storage Systems

The repository is organized by course departments. Each department folder contains individual courses, where you'll find notes in PDF and Markdown formats.

To view a note, simply click on the file. To download, click the 'Download' button or use the raw option in the GitHub interface.

We welcome contributions to courses not yet listed at the moment! To contribute:

1. Fork the repository.
2. Make your changes.
3. Submit a pull request with a clear description of your improvements.

Please refrain from uploading code or unauthorized material from CMU. Such pull requests will not be granted.

This project is licensed under the MIT License. This means you're free to use, modify, and distribute the notes as long as you credit the source. See LICENSE.md for more details.

Questions, feedback, or want to collaborate? Feel free to reach out to me at [email protected] or connect with me on LinkedIn.

Special thanks to the faculty and students of CMU who have contributed to and inspired this collection of notes and Xuezzou, who inspired me to create this project.

这个项目为本人在卡内基梅隆大学学习期间保留的计算机科学课程的全面笔记。

出于整合和分享丰富的学术知识的需求，这个资料库旨在提供详细和易于访问的笔记，涵盖在CMU教授的广泛学科。从计算机系统到机器学习和人工智能，这些笔记包含了关键概念、课堂洞察和学习指南。这个资源非常适合寻求补充学习材料的CMU学生、寻找教学辅助材料的教育工作者，以及对课程感兴趣的自学者。

• 15-513 计算机系统导论
• 14-736 分布式系统
• 10-601 机器学习
• 14-741 信息安全

• 10-605 机器学习与大数据
• 10-617 中级深度学习
• 10-623 生成式人工智能
• 10-725 凸优化/非线性优化
• 11-742 搜索引擎
• 15-619 云计算
• 15-641 计算机网络
• 15-645 数据库系统
• 18-746 存储系统

资料库按课程部门组织。每个部门文件夹包含单独的课程，在那里您会找到以PDF和Markdown格式的笔记。

要查看笔记，只需点击文件。要下载，点击“下载”按钮或使用GitHub界面中的raw选项。

欢迎对目前尚未列出的课程进行贡献！如果您希望做出贡献：

1. Fork该资料库。
2. 进行更改。
3. 提交一个明确描述您改进的Pull请求。

请避免上传来自CMU的代码或未经授权的材料。这样的Pull请求将不会被批准。

该项目在MIT许可证下授权。这意味着您可以自由使用、修改和分发笔记，只要您注明来源。更多详情见LICENSE.md。

有问题、反馈或想合作？欢迎通过[email protected]与我联系，或在LinkedIn上与我连接。