Repository: afshinea/stanford-cs-229-machine-learning
Branch: master
Commit: d96dd195ea67
Files: 21
Total size: 47.7 KB
Directory structure:
gitextract_6swhify8/
├── LICENSE
├── README.md
├── ar/
│ ├── LICENSE
│ └── README.md
├── en/
│ ├── LICENSE
│ └── README.md
├── es/
│ ├── LICENSE
│ └── README.md
├── fa/
│ └── README.md
├── fr/
│ ├── LICENSE
│ └── README.md
├── pt/
│ ├── LICENSE
│ └── README.md
├── tr/
│ ├── LICENSE
│ └── README.md
├── vi/
│ ├── LICENSE
│ └── README.md
├── zh/
│ ├── LICENSE
│ └── README.md
└── zh-tw/
├── LICENSE
└── README.md
================================================
FILE CONTENTS
================================================
================================================
FILE: LICENSE
================================================
MIT License
Copyright (c) 2018 Afshine Amidi and Shervine Amidi
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
================================================
FILE: README.md
================================================
# Machine Learning cheatsheets for Stanford's CS 229
Available in [العربية](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/ar) - [English](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/en) - [Español](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/es) - [فارسی](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/fa) - [Français](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/fr) - [한국어](https://stanford.edu/~shervine/l/ko/teaching/cs-229/cheatsheet-machine-learning-tips-and-tricks) - [Português](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/pt) - [Türkçe](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/tr) - [Tiếng Việt](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/vi) - [简中](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/zh) - [繁中](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/zh-tw)
## Goal
This 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:
- **Refreshers** in related topics that highlight the key points of the **prerequisites of the course**.
- **Cheatsheets for each machine learning field**, as well as another dedicated to tips and tricks to have in mind when training a model.
- All elements of the above combined in an **ultimate compilation of concepts**, to have with you at all times!
## Content
#### VIP Cheatsheets
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-supervised-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/en-001.png?" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-unsupervised-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/en-002.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-deep-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/en-003.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-machine-learning-tips-and-tricks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/en-004.png" alt="Illustration" width="220px"/></a>|
|:--:|:--:|:--:|:--:|
|Supervised Learning|Unsupervised Learning|Deep Learning|Tips and tricks|
#### VIP Refreshers
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/refresher-probabilities-statistics.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/en-005.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/refresher-algebra-calculus.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/en-006.png#1" alt="Illustration" width="220px"/></a>|
|:--:|:--:|
|Probabilities and Statistics|Algebra and Calculus|
#### Super VIP Cheatsheet
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/super-cheatsheet-machine-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/en-007.png" alt="Illustration" width="400px"/></a>|
|:--:|
|All the above gathered in one place|
## Website
This material is also available on a dedicated [website](https://stanford.edu/~shervine/teaching/cs-229), so that you can enjoy reading it from any device.
## Translation
Would you like to see these cheatsheets in your native language? You can help us translating them on [this dedicated repo](https://github.com/shervinea/cheatsheet-translation)!
## Authors
[Afshine Amidi](https://twitter.com/afshinea) (Ecole Centrale Paris, MIT) and [Shervine Amidi](https://twitter.com/shervinea) (Ecole Centrale Paris, Stanford University)
================================================
FILE: ar/LICENSE
================================================
MIT License
Copyright (c) 2018 Afshine Amidi and Shervine Amidi
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
================================================
FILE: ar/README.md
================================================
<span dir="rtl" align="right">
# أدلة تعلم الآلة القصيرة لـ CS ۲۲۹
متوفر في
</span>
**العربية** - [English](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/en) - [Español](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/es) - [فارسی](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/fa) - [Français](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/fr) - [한국어](https://stanford.edu/~shervine/l/ko/teaching/cs-229/cheatsheet-machine-learning-tips-and-tricks) - [Português](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/pt) - [Türkçe](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/tr) - [Tiếng Việt](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/vi) - [简中](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/zh) - [繁中](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/zh-tw)
<span dir="rtl" align="right">
## محتوى
#### دليل قصير خاص
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/ar/cheatsheet-supervised-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/fa-001.png?" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/ar/cheatsheet-unsupervised-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/fa-002.png?" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/ar/cheatsheet-deep-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/fa-003.png?" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/ar/cheatsheet-machine-learning-tips-and-tricks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/fa-004.png?" alt="Illustration" width="220px"/></a>|
|:--:|:--:|:--:|:--:|
|تعلم مراقب|تعلم غير مراقب|تعلم متعمق|لنصائح وحيل تعلّم الآلة
#### تذكير خاص
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/ar/refresher-probabilities-statistics.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/fa-005.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/ar/refresher-algebra-calculus.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/fa-006.png" alt="Illustration" width="220px"/></a>|
|:--:|:--:|
|للاحتمالات والإحصاء|الجبر الخطي و التفاضل و التكامل
#### دليل قصير خاص جدا
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/ar/super-cheatsheet-machine-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/fa-007.png" alt="Illustration" width="400px"/></a>|
|:--:|
|مثل في مكان واحد
## المؤلفون الأصليون
[افشین عمیدی](https://twitter.com/afshinea) (سنترال پاریس، ام آی تی) و [شروین عمیدی](https://twitter.com/shervinea) (سنترال پاریس، استنفرد).
## ترجمة
زيد اليافعي، فارس القنيعير، أمجد الخطابي، مازن مليباري، محمود أصلان، رضوان لغوينسات، امجد الخطابي
</span>
================================================
FILE: en/LICENSE
================================================
MIT License
Copyright (c) 2018 Afshine Amidi and Shervine Amidi
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
================================================
FILE: en/README.md
================================================
# Machine Learning cheatsheets for Stanford's CS 229
Available in [العربية](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/ar) - **English** - [Español](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/es) - [فارسی](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/fa) - [Français](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/fr) - [한국어](https://stanford.edu/~shervine/l/ko/teaching/cs-229/cheatsheet-machine-learning-tips-and-tricks) - [Português](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/pt) - [Türkçe](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/tr) - [Tiếng Việt](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/vi) - [简中](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/zh) - [繁中](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/zh-tw)
## Goal
This 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:
- **Refreshers** in related topics that highlight the key points of the **prerequisites of the course**.
- **Cheatsheets for each machine learning field**, as well as another dedicated to tips and tricks to have in mind when training a model.
- All elements of the above combined in an **ultimate compilation of concepts**, to have with you at all times!
## Content
#### VIP Cheatsheets
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-supervised-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/en-001.png?" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-unsupervised-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/en-002.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-deep-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/en-003.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-machine-learning-tips-and-tricks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/en-004.png" alt="Illustration" width="220px"/></a>|
|:--:|:--:|:--:|:--:|
|Supervised Learning|Unsupervised Learning|Deep Learning|Tips and tricks|
#### VIP Refreshers
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/refresher-probabilities-statistics.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/en-005.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/refresher-algebra-calculus.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/en-006.png#1" alt="Illustration" width="220px"/></a>|
|:--:|:--:|
|Probabilities and Statistics|Algebra and Calculus|
#### Super VIP Cheatsheet
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/super-cheatsheet-machine-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/en-007.png" alt="Illustration" width="400px"/></a>|
|:--:|
|All the above gathered in one place|
## Website
This material is also available on a dedicated [website](https://stanford.edu/~shervine/teaching/cs-229), so that you can enjoy reading it from any device.
## Translation
Would you like to see these cheatsheets in your native language? You can help us translating them on [this dedicated repo](https://github.com/shervinea/cheatsheet-translation)!
## Authors
[Afshine Amidi](https://twitter.com/afshinea) (Ecole Centrale Paris, MIT) and [Shervine Amidi](https://twitter.com/shervinea) (Ecole Centrale Paris, Stanford University)
================================================
FILE: es/LICENSE
================================================
MIT License
Copyright (c) 2018 Afshine Amidi and Shervine Amidi
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
================================================
FILE: es/README.md
================================================
# Hojas de referencia de Machine Learning (CS 229 Stanford)
Disponible en [العربية](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/ar) - [English](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/en) - **Español** - [فارسی](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/fa) - [Français](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/fr) - [한국어](https://stanford.edu/~shervine/l/ko/teaching/cs-229/cheatsheet-machine-learning-tips-and-tricks) - [Português](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/pt) - [Türkçe](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/tr) - [Tiếng Việt](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/vi) - [简中](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/zh) - [繁中](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/zh-tw)
## Contenido
#### Hojas de referencia VIP
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/es/hoja-referencia-aprendizaje-supervisado.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/es-001.png?" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/es/hoja-referencia-aprendizaje-no-supervisado.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/es-002.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/es/hoja-referencia-aprendizaje-profundo.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/es-003.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/es/hoja-referencia-aprendizaje-automatico-consejos-trucos.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/es-004.png" alt="Illustration" width="220px"/></a>|
|:--:|:--:|:--:|:--:|
|Aprendizaje supervisado|Aprendizaje no supervisado|Aprendizaje profundo|Consejos y trucos|
#### Repaso VIP
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/es/repaso-probabilidades-estadisticas.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/es-005.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/es/repaso-algebra-lineal-calculo.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/es-006.png#1" alt="Illustration" width="220px"/></a>|
|:--:|:--:|
|Probabilidades y estadísticas|Álgebra y cálculo|
#### Super hoja de referencia VIP
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/es/super-hoja-referencia-machine-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/es-007.png" alt="Illustration" width="400px"/></a>|
|:--:|
|Todo|
## Autores
[Afshine Amidi](https://twitter.com/afshinea) (Ecole Centrale Paris, MIT) y [Shervine Amidi](https://twitter.com/shervinea) (Ecole Centrale Paris, Stanford University)
## Traductores
Fernando Diaz, Juan P. Chavat, Erick Gabriel Mendoza Flores, Fernando González- Herrera, Mariano Ramirez, Alonso Melgar López, Gustavo Velasco-Hernández, David Jiménez Paredes, Fermin Ordaz, Jaime Noel Alvarez Luna y Juan Manuel Nava Zamudio.
================================================
FILE: fa/README.md
================================================
<span dir="rtl" align="right">
# راهنماهای کوتاه یادگیری ماشین برای کلاس CS ۲۲۹ استنفرد
قابل دسترسی هم در
</span>
[العربية](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/ar) - [English](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/en) - [Español](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/es) - **فارسی** - [Français](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/fr) - [한국어](https://stanford.edu/~shervine/l/ko/teaching/cs-229/cheatsheet-machine-learning-tips-and-tricks) - [Português](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/pt) - [Türkçe](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/tr) - [Tiếng Việt](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/vi) - [简中](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/zh) - [繁中](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/zh-tw)
<span dir="rtl" align="right">
## محتوا
#### راهنمای کوتاه ویژه
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/fa/cheatsheet-supervised-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/fa-001.png?" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/fa/cheatsheet-unsupervised-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/fa-002.png?" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/fa/cheatsheet-deep-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/fa-003.png?" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/fa/cheatsheet-machine-learning-tips-and-tricks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/fa-004.png?" alt="Illustration" width="220px"/></a>|
|:--:|:--:|:--:|:--:|
|یادگیری با نظارت|یادگیری بدون نظارت|یادگیری عمیق|نکات و ترفندها
#### یادآوری ویژه
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/fa/refresher-probabilities-statistics.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/fa-005.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/fa/refresher-algebra-calculus.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/fa-006.png" alt="Illustration" width="220px"/></a>|
|:--:|:--:|
|آمار و احتمالات|جبر خطی و حسابان
#### راهنمای کوتاه بسیار ویژه
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/fa/super-cheatsheet-machine-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/fa-007.png" alt="Illustration" width="400px"/></a>|
|:--:|
|همچی در یک جا
## نویسندگان اصلی
[افشین عمیدی](https://twitter.com/afshinea) (سنترال پاریس، ام آی تی) و [شروین عمیدی](https://twitter.com/shervinea) (سنترال پاریس، استنفرد).
## ترجمه
عرفان نوری، امیرحسین کاظم نژاد، محمد کریمی، الیستر، محمد رضا.
</span>
================================================
FILE: fr/LICENSE
================================================
MIT License
Copyright (c) 2018 Afshine Amidi and Shervine Amidi
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
================================================
FILE: fr/README.md
================================================
# Pense-bêtes de Machine Learning pour CS 229 de Stanford
Disponible en [العربية](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/ar) - [English](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/en) - [Español](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/es) - [فارسی](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/fa) - **Français** - [한국어](https://stanford.edu/~shervine/l/ko/teaching/cs-229/cheatsheet-machine-learning-tips-and-tricks) - [Português](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/pt) - [Türkçe](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/tr) - [Tiếng Việt](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/vi) - [简中](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/zh) - [繁中](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/zh-tw)
## But
Ce repo a pour but de résumer toutes les notions importantes du cours de Machine Learning (CS 229) de Stanford, et inclut en particulier :
- **Rappels** de mathématiques qui soulignent les **pré-requis du cours**.
- **Pense-bêtes pour chaque domaine de Machine Learning**, accompagné d'une fiche de petites astuces, utile lorsque vous construisez un modèle en pratique.
- Tous les éléments ci-dessus **compilés**, à avoir avec vous tout le temps !
## Contenu
#### Pense-bêtes VIP
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/fr/pense-bete-apprentissage-supervise.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/fr-001.png?" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/fr/pense-bete-apprentissage-non-supervise.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/fr-002.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/fr/pense-bete-apprentissage-profond.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/fr-003.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/fr/pense-bete-machine-learning-petites-astuces.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/fr-004.png" alt="Illustration" width="220px"/></a>|
|:--:|:--:|:--:|:--:|
|Apprentissage supervisé|Apprentissage non-supervisé|Apprentissage profond|Petites astuces|
#### Rappels VIP
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/fr/rappels-probabilites-statistiques.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/fr-005.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/fr/rappels-algebre-analyse.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/fr-006.png#1" alt="Illustration" width="220px"/></a>|
|:--:|:--:|
|Probabilités and Statistiques|Algèbre et Analyse|
#### Super Pense-bête VIP
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/fr/super-pense-bete-machine-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/fr-007.png" alt="Illustration" width="400px"/></a>|
|:--:|
|Tous les concepts rassemblés à un seul endroit|
## Site
Les fiches sont aussi disponibles sur un [site dedié](https://stanford.edu/~shervine/l/fr/teaching/cs-229), de manière à ce que vous puissiez les parcourir à partir de n'importe quel appareil.
## Auteurs
[Afshine Amidi](https://twitter.com/afshinea) (Ecole Centrale Paris, MIT) et [Shervine Amidi](https://twitter.com/shervinea) (Ecole Centrale Paris, Stanford University)
================================================
FILE: pt/LICENSE
================================================
MIT License
Copyright (c) 2018 Afshine Amidi and Shervine Amidi
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
================================================
FILE: pt/README.md
================================================
# Dicas de Machine Learning (CS 229 Stanford)
Disponível em [العربية](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/ar) - [English](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/en) - [Español](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/es) - [فارسی](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/fa) - [Français](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/fr) - [한국어](https://stanford.edu/~shervine/l/ko/teaching/cs-229/cheatsheet-machine-learning-tips-and-tricks) - **Português** - [Türkçe](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/tr) - [Tiếng Việt](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/vi) - [简中](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/zh) - [繁中](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/zh-tw)
## Conteúdo
#### Dicas VIP
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/pt/dicas-aprendizado-supervisionado.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/pt-001.png?" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/pt/dicas-aprendizado-nao-supervisionado.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/pt-002.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/pt/dicas-aprendizado-profundo.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/pt-003.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/pt/dicas-truques-aprendizado-maquina.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/pt-004.png" alt="Illustration" width="220px"/></a>|
|:--:|:--:|:--:|:--:|
|Aprendizado supervisionado|Aprendizado não supervisionado|Aprendizado profundo|Dicas e truques|
#### Revisão VIP
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/pt/revisao-probabilidades-estatistica.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/pt-005.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/pt/revisao-algebra-linear-calculo.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/pt-006.png#1" alt="Illustration" width="220px"/></a>|
|:--:|:--:|
|Probabilidades e estatística|Álgebra e cálculo|
#### Super dica VIP
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/pt/super-dicas-machine-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/pt-007.png" alt="Illustration" width="400px"/></a>|
|:--:|
|Tudo|
## Autores
[Afshine Amidi](https://twitter.com/afshinea) (Ecole Centrale Paris, MIT) e [Shervine Amidi](https://twitter.com/shervinea) (Ecole Centrale Paris, Stanford University)
## Tradutores
Gabriel Fonseca, Leticia Portella, Fernando Santos, Flavio Clesio, Tiago Danin
================================================
FILE: tr/LICENSE
================================================
MIT License
Copyright (c) 2019 Afshine Amidi and Shervine Amidi
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
================================================
FILE: tr/README.md
================================================
# Makine Öğrenimi El Kitabı (Stanford CS 229)
Içinde mevcut [العربية](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/ar) - [English](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/en) - [Español](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/es) - [فارسی](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/fa) - [Français](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/fr) - [한국어](https://stanford.edu/~shervine/l/ko/teaching/cs-229/cheatsheet-machine-learning-tips-and-tricks) - [Português](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/pt) - **Türkçe** - [Tiếng Việt](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/vi) - [简中](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/zh) - [繁中](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/zh-tw)
## Içindekiler
#### El Kitabı VIP
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/tr/cheatsheet-supervised-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/tr-001.png?" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/tr/cheatsheet-unsupervised-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/tr-002.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/tr/cheatsheet-deep-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/tr-003.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/tr/cheatsheet-machine-learning-tips-and-tricks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/tr-004.png" alt="Illustration" width="220px"/></a>|
|:--:|:--:|:--:|:--:|
|Gözetimli Öğrenme|Gözetimsiz Öğrenme|Derin Öğrenme|Ipuçları ve püf noktaları|
#### Hatırlatma VIP
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/tr/refresher-probabilities-statistics.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/tr-005.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/tr/refresher-algebra-calculus.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/tr-006.png#1" alt="Illustration" width="220px"/></a>|
|:--:|:--:|
|Olasılık ve İstatistik|Doğrusal Cebir ve Kalkülüs|
#### El Kitabı Super VIP
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/tr/super-cheatsheet-machine-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/tr-007.png" alt="Illustration" width="400px"/></a>|
|---|
## Yazarlar
[Afshine Amidi](https://twitter.com/afshinea) (Ecole Centrale Paris, MIT) ve [Shervine Amidi](https://twitter.com/shervinea) (Ecole Centrale Paris, Stanford University)
## Tercümanlar
Başak Buluz, Ayyüce Kızrak, Yavuz Kömeçoğlu, Ekrem Çetinkaya, Omer Bukte, Seray Beşer ve Kadir Tekeli
================================================
FILE: vi/LICENSE
================================================
MIT License
Copyright (c) 2018 Afshine Amidi and Shervine Amidi
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
================================================
FILE: vi/README.md
================================================
# Học máy cheatsheets (Stanford CS 229)
Có sẵn bằng [العربية](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/ar) - [English](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/en) - [Español](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/es) - [فارسی](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/fa) - [Français](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/fr) - [한국어](https://stanford.edu/~shervine/l/ko/teaching/cs-229/cheatsheet-machine-learning-tips-and-tricks) - [Português](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/pt) - [Türkçe](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/tr) - **Tiếng Việt** - [简中](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/zh) - [繁中](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/zh-tw)
## Nội dung
#### VIP cheatsheets
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/vi/cheatsheet-supervised-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/vi-001.png?" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/vi/cheatsheet-unsupervised-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/vi-002.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/vi/cheatsheet-deep-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/vi-003.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/vi/cheatsheet-machine-learning-tips-and-tricks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/vi-004.png" alt="Illustration" width="220px"/></a>|
|:--:|:--:|:--:|:--:|
|Học có giám sát|Học không giám sát|Học sâu|Các mẹo và thủ thuật|
#### VIP refreshers
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/vi/refresher-probabilities-statistics.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/vi-005.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/vi/refresher-algebra-calculus.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/vi-006.png#1" alt="Illustration" width="220px"/></a>|
|:--:|:--:|
|Xác suất và Thống kê cơ bản|Đại số tuyến tính và Giải tích cơ bản|
#### Super VIP cheatsheet
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/vi/super-cheatsheet-machine-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/vi-007.png" alt="Illustration" width="400px"/></a>|
|---|
## Các tác giả
[Afshine Amidi](https://twitter.com/afshinea) (Ecole Centrale Paris, Viện Công nghệ Massachusetts) và [Shervine Amidi](https://twitter.com/shervinea) (Ecole Centrale Paris, Đại học Stanford)
## Dịch thuật
Trần Tuấn Anh, Hoàng Vũ Đạt, Nguyễn Khánh Hưng, Nguyễn Trí Minh, Hung Nguyễn, Vinh Pham, Đàm Minh Tiến, Hoàng Minh Tuấn và Phạm Hồng Vinh
================================================
FILE: zh/LICENSE
================================================
MIT License
Copyright (c) 2018 Afshine Amidi and Shervine Amidi
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
================================================
FILE: zh/README.md
================================================
# 机器学习 (CS 229 Stanford)
可得到 [العربية](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/ar) - [English](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/en) - [Español](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/es) - [فارسی](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/fa) - [Français](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/fr) - [한국어](https://stanford.edu/~shervine/l/ko/teaching/cs-229/cheatsheet-machine-learning-tips-and-tricks) - [Português](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/pt) - [Türkçe](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/tr) - [Tiếng Việt](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/vi) - **简中** - [繁中](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/zh-tw)
## 内容
#### VIP Cheatsheets
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/zh/cheatsheet-supervised-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/zh-001.png?" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/zh/cheatsheet-unsupervised-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/zh-002.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/zh/cheatsheet-deep-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/zh-003.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/zh/cheatsheet-machine-learning-tips-and-tricks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/zh-004.png" alt="Illustration" width="220px"/></a>|
|:--:|:--:|:--:|:--:|
|监督学习|无监督学习|深度学习|机器学习技巧和秘诀|
#### VIP Refreshers
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/zh/refresher-probabilities-statistics.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/zh-005.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/zh/refresher-algebra-calculus.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/zh-006.png#1" alt="Illustration" width="220px"/></a>|
|:--:|:--:|
|概率和统计|线性代数和微积分|
## 作者
[Afshine Amidi](https://twitter.com/afshinea) (Ecole Centrale Paris, MIT) 和 [Shervine Amidi](https://twitter.com/shervinea) (Ecole Centrale Paris, Stanford University)
## 译者
Wang Hongnian, Xiaohu Zhu, Chaoying Xue
================================================
FILE: zh-tw/LICENSE
================================================
MIT License
Copyright (c) 2018 Afshine Amidi and Shervine Amidi
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
================================================
FILE: zh-tw/README.md
================================================
# 機器學習 (CS 229 Stanford)
可得到 [العربية](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/ar) - [English](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/en) - [Español](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/es) - [فارسی](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/fa) - [Français](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/fr) - [한국어](https://stanford.edu/~shervine/l/ko/teaching/cs-229/cheatsheet-machine-learning-tips-and-tricks) - [Português](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/pt) - [Türkçe](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/tr) - [Tiếng Việt](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/vi) - [简中](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/zh) - **繁中**
## 內容
#### VIP Cheatsheets
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/zh-tw/cheatsheet-supervised-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/zh-001.png?" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/zh-tw/cheatsheet-unsupervised-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/zh-002.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/zh-tw/cheatsheet-deep-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/zh-003.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/zh-tw/cheatsheet-machine-learning-tips-and-tricks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/zh-004.png" alt="Illustration" width="220px"/></a>|
|:--:|:--:|:--:|:--:|
|監督學習|無監督學習|深度學習|機器學習技巧和秘訣|
#### VIP Refreshers
|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/zh-tw/refresher-probabilities-statistics.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/zh-005.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/zh-tw/refresher-algebra-calculus.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/zh-006.png#1" alt="Illustration" width="220px"/></a>|
|:--:|:--:|
|概率和統計|線性代數和微積分|
## 作者
[Afshine Amidi](https://twitter.com/afshinea) (Ecole Centrale Paris, MIT) 和 [Shervine Amidi](https://twitter.com/shervinea) (Ecole Centrale Paris, Stanford University)
## 譯者
kevingo, TobyOoO, kentropy, 詹志傑, imironhead, 徐承漢 和 Miyaya
gitextract_6swhify8/
├── LICENSE
├── README.md
├── ar/
│ ├── LICENSE
│ └── README.md
├── en/
│ ├── LICENSE
│ └── README.md
├── es/
│ ├── LICENSE
│ └── README.md
├── fa/
│ └── README.md
├── fr/
│ ├── LICENSE
│ └── README.md
├── pt/
│ ├── LICENSE
│ └── README.md
├── tr/
│ ├── LICENSE
│ └── README.md
├── vi/
│ ├── LICENSE
│ └── README.md
├── zh/
│ ├── LICENSE
│ └── README.md
└── zh-tw/
├── LICENSE
└── README.md
Condensed preview — 21 files, each showing path, character count, and a content snippet. Download the .json file or copy for the full structured content (51K chars).
[
{
"path": "LICENSE",
"chars": 1089,
"preview": "MIT License\n\nCopyright (c) 2018 Afshine Amidi and Shervine Amidi\n\nPermission is hereby granted, free of charge, to any p"
},
{
"path": "README.md",
"chars": 4178,
"preview": "# Machine Learning cheatsheets for Stanford's CS 229\n\nAvailable in [العربية](https://github.com/afshinea/stanford-cs-229"
},
{
"path": "ar/LICENSE",
"chars": 1089,
"preview": "MIT License\n\nCopyright (c) 2018 Afshine Amidi and Shervine Amidi\n\nPermission is hereby granted, free of charge, to any p"
},
{
"path": "ar/README.md",
"chars": 3336,
"preview": "<span dir=\"rtl\" align=\"right\">\n\n# أدلة تعلم الآلة القصيرة لـ CS ۲۲۹\n\nمتوفر في\n\n</span>\n\n**العربية** - [English](https:/"
},
{
"path": "en/LICENSE",
"chars": 1089,
"preview": "MIT License\n\nCopyright (c) 2018 Afshine Amidi and Shervine Amidi\n\nPermission is hereby granted, free of charge, to any p"
},
{
"path": "en/README.md",
"chars": 4102,
"preview": "# Machine Learning cheatsheets for Stanford's CS 229\nAvailable in [العربية](https://github.com/afshinea/stanford-cs-229-"
},
{
"path": "es/LICENSE",
"chars": 1089,
"preview": "MIT License\n\nCopyright (c) 2018 Afshine Amidi and Shervine Amidi\n\nPermission is hereby granted, free of charge, to any p"
},
{
"path": "es/README.md",
"chars": 3535,
"preview": "# Hojas de referencia de Machine Learning (CS 229 Stanford)\nDisponible en [العربية](https://github.com/afshinea/stanford"
},
{
"path": "fa/README.md",
"chars": 3324,
"preview": "<span dir=\"rtl\" align=\"right\">\n\n# راهنماهای کوتاه یادگیری ماشین برای کلاس CS ۲۲۹ استنفرد\n\nقابل دسترسی هم در\n\n</span>\n\n[ا"
},
{
"path": "fr/LICENSE",
"chars": 1089,
"preview": "MIT License\n\nCopyright (c) 2018 Afshine Amidi and Shervine Amidi\n\nPermission is hereby granted, free of charge, to any p"
},
{
"path": "fr/README.md",
"chars": 3924,
"preview": "# Pense-bêtes de Machine Learning pour CS 229 de Stanford\nDisponible en [العربية](https://github.com/afshinea/stanford-c"
},
{
"path": "pt/LICENSE",
"chars": 1089,
"preview": "MIT License\n\nCopyright (c) 2018 Afshine Amidi and Shervine Amidi\n\nPermission is hereby granted, free of charge, to any p"
},
{
"path": "pt/README.md",
"chars": 3279,
"preview": "# Dicas de Machine Learning (CS 229 Stanford)\nDisponível em [العربية](https://github.com/afshinea/stanford-cs-229-machin"
},
{
"path": "tr/LICENSE",
"chars": 1089,
"preview": "MIT License\n\nCopyright (c) 2019 Afshine Amidi and Shervine Amidi\n\nPermission is hereby granted, free of charge, to any p"
},
{
"path": "tr/README.md",
"chars": 3304,
"preview": "# Makine Öğrenimi El Kitabı (Stanford CS 229)\n\nIçinde mevcut [العربية](https://github.com/afshinea/stanford-cs-229-machi"
},
{
"path": "vi/LICENSE",
"chars": 1089,
"preview": "MIT License\n\nCopyright (c) 2018 Afshine Amidi and Shervine Amidi\n\nPermission is hereby granted, free of charge, to any p"
},
{
"path": "vi/README.md",
"chars": 3358,
"preview": "# Học máy cheatsheets (Stanford CS 229)\n\nCó sẵn bằng [العربية](https://github.com/afshinea/stanford-cs-229-machine-learn"
},
{
"path": "zh/LICENSE",
"chars": 1089,
"preview": "MIT License\n\nCopyright (c) 2018 Afshine Amidi and Shervine Amidi\n\nPermission is hereby granted, free of charge, to any p"
},
{
"path": "zh/README.md",
"chars": 2812,
"preview": "# 机器学习 (CS 229 Stanford)\n可得到 [العربية](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/ar) - ["
},
{
"path": "zh-tw/LICENSE",
"chars": 1089,
"preview": "MIT License\n\nCopyright (c) 2018 Afshine Amidi and Shervine Amidi\n\nPermission is hereby granted, free of charge, to any p"
},
{
"path": "zh-tw/README.md",
"chars": 2845,
"preview": "# 機器學習 (CS 229 Stanford)\n可得到 [العربية](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/ar) - ["
}
]
About this extraction
This page contains the full source code of the afshinea/stanford-cs-229-machine-learning GitHub repository, extracted and formatted as plain text for AI agents and large language models (LLMs). The extraction includes 21 files (47.7 KB), approximately 14.5k tokens. Use this with OpenClaw, Claude, ChatGPT, Cursor, Windsurf, or any other AI tool that accepts text input. You can copy the full output to your clipboard or download it as a .txt file.
Extracted by GitExtract — free GitHub repo to text converter for AI. Built by Nikandr Surkov.