[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-9592":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":10,"languages":10,"totalLinesOfCode":10,"stars":11,"forks":12,"watchers":13,"openIssues":14,"contributorsCount":15,"subscribersCount":15,"size":15,"stars1d":16,"stars7d":17,"stars30d":18,"stars90d":15,"forks30d":15,"starsTrendScore":19,"compositeScore":20,"rankGlobal":10,"rankLanguage":10,"license":21,"archived":22,"fork":22,"defaultBranch":23,"hasWiki":24,"hasPages":22,"topics":25,"createdAt":10,"pushedAt":10,"updatedAt":34,"readmeContent":35,"aiSummary":36,"trendingCount":15,"starSnapshotCount":15,"syncStatus":37,"lastSyncTime":38,"discoverSource":39},9592,"stanford-cs-229-machine-learning","afshinea\u002Fstanford-cs-229-machine-learning","afshinea","VIP cheatsheets for Stanford's CS 229 Machine Learning","https:\u002F\u002Fstanford.edu\u002F~shervine\u002Fteaching\u002Fcs-229",null,19496,4171,726,20,0,3,7,117,9,89.5,"MIT License",false,"master",true,[26,27,28,29,30,31,32,33],"cheatsheet","cs229","data-science","deep-learning","machine-learning","ml-cheatsheet","supervised-learning","unsupervised-learning","2026-06-12 04:00:45","# Machine Learning cheatsheets for Stanford's CS 229\n\nAvailable in [العربية](https:\u002F\u002Fgithub.com\u002Fafshinea\u002Fstanford-cs-229-machine-learning\u002Ftree\u002Fmaster\u002Far) -  [English](https:\u002F\u002Fgithub.com\u002Fafshinea\u002Fstanford-cs-229-machine-learning\u002Ftree\u002Fmaster\u002Fen) -  [Español](https:\u002F\u002Fgithub.com\u002Fafshinea\u002Fstanford-cs-229-machine-learning\u002Ftree\u002Fmaster\u002Fes) -  [فارسی](https:\u002F\u002Fgithub.com\u002Fafshinea\u002Fstanford-cs-229-machine-learning\u002Ftree\u002Fmaster\u002Ffa) -  [Français](https:\u002F\u002Fgithub.com\u002Fafshinea\u002Fstanford-cs-229-machine-learning\u002Ftree\u002Fmaster\u002Ffr) -  [한국어](https:\u002F\u002Fstanford.edu\u002F~shervine\u002Fl\u002Fko\u002Fteaching\u002Fcs-229\u002Fcheatsheet-machine-learning-tips-and-tricks) -  [Português](https:\u002F\u002Fgithub.com\u002Fafshinea\u002Fstanford-cs-229-machine-learning\u002Ftree\u002Fmaster\u002Fpt) -  [Türkçe](https:\u002F\u002Fgithub.com\u002Fafshinea\u002Fstanford-cs-229-machine-learning\u002Ftree\u002Fmaster\u002Ftr) - [Tiếng Việt](https:\u002F\u002Fgithub.com\u002Fafshinea\u002Fstanford-cs-229-machine-learning\u002Ftree\u002Fmaster\u002Fvi) -  [简中](https:\u002F\u002Fgithub.com\u002Fafshinea\u002Fstanford-cs-229-machine-learning\u002Ftree\u002Fmaster\u002Fzh) -  [繁中](https:\u002F\u002Fgithub.com\u002Fafshinea\u002Fstanford-cs-229-machine-learning\u002Ftree\u002Fmaster\u002Fzh-tw)\n\n## Goal\nThis repository aims at summing up in the same place all the important notions that are covered in Stanford's CS 229 Machine Learning course, and include:\n- **Refreshers** in related topics that highlight the key points of the **prerequisites of the course**.\n- **Cheatsheets for each machine learning field**, as well as another dedicated to tips and tricks to have in mind when training a model.\n- All elements of the above combined in an **ultimate compilation of concepts**, to have with you at all times!\n\n## Content\n#### VIP Cheatsheets\n|\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fafshinea\u002Fstanford-cs-229-machine-learning\u002Fblob\u002Fmaster\u002Fen\u002Fcheatsheet-supervised-learning.pdf\">\u003Cimg src=\"https:\u002F\u002Fstanford.edu\u002F~shervine\u002Fteaching\u002Fcs-229\u002Fillustrations\u002Fcover\u002Fen-001.png?\" alt=\"Illustration\" width=\"220px\"\u002F>\u003C\u002Fa>|\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fafshinea\u002Fstanford-cs-229-machine-learning\u002Fblob\u002Fmaster\u002Fen\u002Fcheatsheet-unsupervised-learning.pdf\">\u003Cimg src=\"https:\u002F\u002Fstanford.edu\u002F~shervine\u002Fteaching\u002Fcs-229\u002Fillustrations\u002Fcover\u002Fen-002.png\" alt=\"Illustration\" width=\"220px\"\u002F>\u003C\u002Fa>|\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fafshinea\u002Fstanford-cs-229-machine-learning\u002Fblob\u002Fmaster\u002Fen\u002Fcheatsheet-deep-learning.pdf\">\u003Cimg src=\"https:\u002F\u002Fstanford.edu\u002F~shervine\u002Fteaching\u002Fcs-229\u002Fillustrations\u002Fcover\u002Fen-003.png\" alt=\"Illustration\" width=\"220px\"\u002F>\u003C\u002Fa>|\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fafshinea\u002Fstanford-cs-229-machine-learning\u002Fblob\u002Fmaster\u002Fen\u002Fcheatsheet-machine-learning-tips-and-tricks.pdf\">\u003Cimg src=\"https:\u002F\u002Fstanford.edu\u002F~shervine\u002Fteaching\u002Fcs-229\u002Fillustrations\u002Fcover\u002Fen-004.png\" alt=\"Illustration\" width=\"220px\"\u002F>\u003C\u002Fa>|\n|:--:|:--:|:--:|:--:|\n|Supervised Learning|Unsupervised Learning|Deep Learning|Tips and tricks|\n\n#### VIP Refreshers\n|\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fafshinea\u002Fstanford-cs-229-machine-learning\u002Fblob\u002Fmaster\u002Fen\u002Frefresher-probabilities-statistics.pdf\">\u003Cimg src=\"https:\u002F\u002Fstanford.edu\u002F~shervine\u002Fteaching\u002Fcs-229\u002Fillustrations\u002Fcover\u002Fen-005.png\" alt=\"Illustration\" width=\"220px\"\u002F>\u003C\u002Fa>|\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fafshinea\u002Fstanford-cs-229-machine-learning\u002Fblob\u002Fmaster\u002Fen\u002Frefresher-algebra-calculus.pdf\">\u003Cimg src=\"https:\u002F\u002Fstanford.edu\u002F~shervine\u002Fteaching\u002Fcs-229\u002Fillustrations\u002Fcover\u002Fen-006.png#1\" alt=\"Illustration\" width=\"220px\"\u002F>\u003C\u002Fa>|\n|:--:|:--:|\n|Probabilities and Statistics|Algebra and Calculus|\n\n\n#### Super VIP Cheatsheet\n|\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fafshinea\u002Fstanford-cs-229-machine-learning\u002Fblob\u002Fmaster\u002Fen\u002Fsuper-cheatsheet-machine-learning.pdf\">\u003Cimg src=\"https:\u002F\u002Fstanford.edu\u002F~shervine\u002Fteaching\u002Fcs-229\u002Fillustrations\u002Fcover\u002Fen-007.png\" alt=\"Illustration\" width=\"400px\"\u002F>\u003C\u002Fa>|\n|:--:|\n|All the above gathered in one place|\n\n## Website\nThis material is also available on a dedicated [website](https:\u002F\u002Fstanford.edu\u002F~shervine\u002Fteaching\u002Fcs-229), so that you can enjoy reading it from any device.\n\n## Translation\nWould you like to see these cheatsheets in your native language? You can help us translating them on [this dedicated repo](https:\u002F\u002Fgithub.com\u002Fshervinea\u002Fcheatsheet-translation)!\n\n## Authors\n[Afshine Amidi](https:\u002F\u002Ftwitter.com\u002Fafshinea) (Ecole Centrale Paris, MIT) and [Shervine Amidi](https:\u002F\u002Ftwitter.com\u002Fshervinea) (Ecole Centrale Paris, Stanford University)\n","该项目为斯坦福大学CS 229机器学习课程提供了详尽的速查表。核心功能包括涵盖监督学习、无监督学习、深度学习等领域的速查表，以及关于模型训练技巧与提示的专门章节。此外，还提供了一系列相关主题的知识点复习材料，帮助学习者快速掌握课程所需的先修知识。这些资源被精心编排成多语言版本，方便全球的学习者使用。该项目特别适合正在学习或准备学习斯坦福CS 229课程的学生，以及希望巩固机器学习基础知识的专业人士。",2,"2026-06-11 03:23:37","top_topic"]