165 lines
6.6 KiB
YAML
165 lines
6.6 KiB
YAML
site_name: CS自学指南
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site_url: https://csdiy.wiki/
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site_author: PKUFlyingPig
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site_description: >-
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CS自学指南
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repo_name: cs-self-learning
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repo_url: https://github.com/pkuflyingpig/cs-self-learning/
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copyright: Copyright © 2021-present <a href="https://github.com/PKUFlyingPig" target="_blank" rel="noopener noreferrer">PKUFlyingPig</a>
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# - navigation.instant
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link: https://github.com/pkuflyingpig/cs-self-learning/
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nav:
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- 前言: 'index.md'
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- 一个仅供参考的CS学习规划: 'CS学习规划.md'
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- 必学工具:
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- 翻墙: '必学工具/翻墙.md'
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- Vim: '必学工具/Vim.md'
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- Git: '必学工具/Git.md'
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- Github: '必学工具/Github.md'
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- Makefile: '必学工具/Makefile.md'
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- CMake: '必学工具/CMake.md'
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- Latex: '必学工具/Latex.md'
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- Docker: '必学工具/Docker.md'
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- 实用工具箱: '必学工具/tools.md'
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- 好书推荐: '好书推荐.md'
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- 数学基础:
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- 'MIT18.01/18.02: Calculus': '数学基础/MITmaths.md'
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- 'MIT18.06: Linear Algebra': '数学基础/MITLA.md'
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- 'MIT6.050J: Information theory and Entropy': '数学基础/information.md'
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- 数学进阶:
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- 'UCB CS70: discrete Math and probability theory': '数学进阶/CS70.md'
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- 'UCB CS126: probability theory': '数学进阶/CS126.md'
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- 'MIT 6.042J: Mathematics for Computer Science': '数学进阶/6.042J.md'
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- 'MIT18.330: Introduction to numerical analysis': '数学进阶/numerical.md'
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- 'Standford EE364A: Convex Optimization': '数学进阶/convex.md'
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- 'The Information Theory, Patter Recognition, and Neural Networks': '数学进阶/The Information Theory, Pattern Recognition, and Neural Networks.md'
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- 编程入门:
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- 'MIT-Missing-Semester': '编程入门/MIT-Missing-Semester.md'
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- 'Harvard CS50: This is CS50x': '编程入门/CS50.md'
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- 'UCB CS61A: Structure and Interpretation of Computer Programs': '编程入门/CS61A.md'
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- 'Stanford CS106L: Standard C++ Programming': '编程入门/CS106L.md'
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- 'Stanford CS110L: Safety in Systems Programming': '编程入门/CS110L.md'
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- 电子基础:
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- 'EE16A&B: Designing Information Devices and Systems I&II': '电子基础/EE16.md'
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- 'UCB EE120 : Signal and Systems': '电子基础/signal.md'
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- 'MIT 6.007 Signals and Systems': '电子基础/Signals and Systems_AVO.md'
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- 数据结构与算法:
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- 'UCB CS61B: Data Structures and Algorithms': '数据结构与算法/CS61B.md'
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- 'Coursera: Algorithms I & II': '数据结构与算法/Algo.md'
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- 'Stanford CS106B/X': '数据结构与算法/CS106B_CS106X.md'
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- 'UCB CS170: Efficient Algorithms and Intractable Problems': '数据结构与算法/CS170.md'
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- 软件工程:
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- 'MIT 6.031: Software Construction': '软件工程/6031.md'
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- 'UCB CS169: software engineering': '软件工程/CS169.md'
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- 体系结构:
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- 'Coursera: Nand2Tetris': '体系结构/N2T.md'
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- 'UCB CS61C: Great Ideas in Computer Architecture': '体系结构/CS61C.md'
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- 'CMU 15-213: CSAPP': '体系结构/CSAPP.md'
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- 操作系统:
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- 'MIT 6.S081: Operating System Engineering': '操作系统/MIT6.S081.md'
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- 'UCB CS162: Operating System': '操作系统/CS162.md'
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- 并行与分布式系统:
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- 'CMU 15-418/Stanford CS149: Parallel Computing': '并行与分布式系统/CS149.md'
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- 'MIT 6.824: Distributed System': '并行与分布式系统/MIT6.824.md'
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- 计算机系统安全:
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- 'UCB CS161: Computer Security': '系统安全/CS161.md'
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- 'MIT 6.858: Computer System Security': '系统安全/MIT6.858.md'
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- 计算机网络:
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- 'Computer Networking: A Top-Down Approach': '计算机网络/topdown.md'
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- 'Stanford CS144: Computer Network': '计算机网络/CS144.md'
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- 数据库系统:
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- 'UCB CS186: Introduction to Database System': '数据库系统/CS186.md'
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- 'CMU 15-445: Database Systems': '数据库系统/15445.md'
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- 编译原理:
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- 'Stanford CS143: Compilers': '编译原理/CS143.md'
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- 计算机图形学:
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- 'GAMES101': '计算机图形学/GAMES101.md'
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- Web开发:
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- 'MIT web development course': 'Web开发/mitweb.md'
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- 'Stanford CS142: Web Applications': 'Web开发/CS142.md'
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- 数据科学:
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- 'UCB Data100: Principles and Techniques of Data Science': '数据科学/Data100.md'
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- 人工智能:
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- 'Harvard CS50’s Introduction to AI with Python': '人工智能/CS50.md'
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- 'UCB CS188: Introduction to Artificial Intelligence': '人工智能/CS188.md'
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- '智能计算系统': '人工智能/CYJ.md'
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- 机器学习:
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- 'Coursera: Machine Learning': '机器学习/ML.md'
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- 'Stanford CS229: Machine Learning': '机器学习/CS229.md'
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- 'UCB CS189: Introduction to Machine Learning': '机器学习/CS189.md'
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- 深度学习:
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- 'Coursera: Deep Learning': '深度学习/CS230.md'
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- '台湾国立大学：李宏毅机器学习': '深度学习/LHY.md'
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- 'Stanford CS231n: CNN for Visual Recognition': '深度学习/CS231.md'
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- 'Stanford CS224n: Natural Language Processing': '深度学习/CS224n.md'
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- 'Stanford CS224w: Machine Learning with Graphs': '深度学习/CS224w.md'
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- 'UCB CS285: Deep Reinforcement Learning': '深度学习/CS285.md'
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- 机器学习进阶:
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- '进阶路线图': '机器学习进阶/roadmap.md'
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- 'CMU 10-708: Probabilistic Graphical Models': '机器学习进阶/CMU10-708.md'
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- 'Columbia STAT 8201: Deep Generative Models': '机器学习进阶/STAT8201.md'
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- 'U Toronto STA 4273 Winter 2021: Minimizing Expectations': '机器学习进阶/STA4273.md'
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- 'Stanford STATS214 / CS229M: Machine Learning Theory': '机器学习进阶/CS229M.md'
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- 后记: '后记.md'
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