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Repository: afshinea/stanford-cs-230-deep-learning
Branch: master
Commit: 4653bc01297b
Files: 14
Total size: 23.5 KB

Directory structure:
gitextract_vuokji89/

├── LICENSE
├── README.md
├── en/
│   ├── LICENSE
│   └── README.md
├── fa/
│   ├── LICENSE
│   └── README.md
├── fr/
│   ├── LICENSE
│   └── README.md
├── ja/
│   ├── LICENSE
│   └── README.md
├── tr/
│   ├── LICENSE
│   └── README.md
└── vi/
    ├── 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
================================================
# Deep Learning cheatsheets for Stanford's CS 230

Available in [English](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/en) -  [فارسی](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/fa) -  [Français](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/fr) - [日本語](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/ja) - [한국어](https://stanford.edu/~shervine/l/ko/teaching/cs-230/cheatsheet-convolutional-neural-networks) -  [Türkçe](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/tr) - [Tiếng Việt](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/vi)

## Goal
This repository aims at summing up in the same place all the important notions that are covered in Stanford's CS 230 Deep Learning course, and include:
- **Cheatsheets detailing everything** about convolutional neural networks, recurrent neural networks, as well as the tips and tricks to have in mind when training a deep learning 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-230-deep-learning/blob/master/en/cheatsheet-convolutional-neural-networks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/en-001.png?" alt="Illustration" width="280px"/></a>|<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/en/cheatsheet-recurrent-neural-networks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/en-002.png?" alt="Illustration" width="280px"/></a>|<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/en/cheatsheet-deep-learning-tips-tricks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/en-003.png?" alt="Illustration" width="280px"/></a>|
|:--:|:--:|:--:|
|Convolutional Neural Networks|Recurrent Neural Networks|Tips and tricks|

#### Super VIP Cheatsheet
|<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/en/super-cheatsheet-deep-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/en-004.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-230), 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: 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
================================================
# Deep Learning cheatsheets for Stanford's CS 230
Available in **English** -  [فارسی](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/fa) -  [Français](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/fr) - [日本語](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/ja) - [한국어](https://stanford.edu/~shervine/l/ko/teaching/cs-230/cheatsheet-convolutional-neural-networks) -  [Türkçe](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/tr) - [Tiếng Việt](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/vi)

## Goal
This repository aims at summing up in the same place all the important notions that are covered in Stanford's CS 230 Deep Learning course, and include:
- **Cheatsheets detailing everything** about convolutional neural networks, recurrent neural networks, as well as the tips and tricks to have in mind when training a deep learning 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-230-deep-learning/blob/master/en/cheatsheet-convolutional-neural-networks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/en-001.png?" alt="Illustration" width="280px"/></a>|<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/en/cheatsheet-recurrent-neural-networks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/en-002.png?" alt="Illustration" width="280px"/></a>|<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/en/cheatsheet-deep-learning-tips-tricks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/en-003.png?" alt="Illustration" width="280px"/></a>|
|:--:|:--:|:--:|
|Convolutional Neural Networks|Recurrent Neural Networks|Tips and tricks|

#### Super VIP Cheatsheet
|<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/en/super-cheatsheet-deep-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/en-004.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-230), 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: fa/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: fa/README.md
================================================
<span dir="rtl" align="right">

# راهنماهای کوتاه یادگیری عمیق برای کلاس CS ۲۳۰ استنفرد

قابل دسترسی هم در

</span>

[English](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/en) -  **فارسی** -  [Français](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/fr) - [日本語](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/ja) - [한국어](https://stanford.edu/~shervine/l/ko/teaching/cs-230/cheatsheet-convolutional-neural-networks) -  [Türkçe](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/tr) - [Tiếng Việt](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/vi)

<span dir="rtl" align="right">

## محتوا
#### راهنمای کوتاه ویژه
|<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/fa/cheatsheet-convolutional-neural-networks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/fa-001.png?" alt="Illustration" width="280px"/></a>|<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/fa/cheatsheet-recurrent-neural-networks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/fa-002.png?" alt="Illustration" width="280px"/></a>|<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/fa/cheatsheet-deep-learning-tips-tricks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/fa-003.png?" alt="Illustration" width="280px"/></a>|
|:--:|:--:|:--:|
|شبکه‌های عصبی پیچشی|شبکه‌های عصبی برگشتی|نکات و ترفندها


#### راهنمای کوتاه بسیار ویژه
|<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/fa/super-cheatsheet-deep-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/fa-004.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، الیستر، احسان کرمانی.


</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 Deep Learning pour CS 230 de Stanford
Disponible en [English](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/en) -  [فارسی](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/fa) -  **Français** - [日本語](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/ja) - [한국어](https://stanford.edu/~shervine/l/ko/teaching/cs-230/cheatsheet-convolutional-neural-networks) -  [Türkçe](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/tr) - [Tiếng Việt](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/vi)

## But
Ce repo a pour but de résumer toutes les notions importantes du cours de Deep Learning (CS 230) de Stanford, et inclut en particulier :
- **Pense-bêtes pour chaque domaine de Deep 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-230-deep-learning/blob/master/fr/pense-bete-reseaux-neurones-convolutionnels.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/fr-001.png?" alt="Illustration" width="280px"/></a>|<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/fr/pense-bete-reseaux-neurones-recurrents.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/fr-002.png?" alt="Illustration" width="280px"/></a>|<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/fr/pense-bete-petites-astuces-apprentissage-profond.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/fr-003.png?" alt="Illustration" width="280px"/></a>|
|:--:|:--:|:--:|
|Réseaux de neurones convolutionnels|Réseaux de neurones récurrents|Petites astuces|

#### Super Pense-bête VIP
|<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/fr/super-pense-bete-apprentissage-profond.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/fr-004.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-230), 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: ja/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: ja/README.md
================================================
# スタンフォードのCS 230のディープラーニングのチートシート

[English](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/en) -  [فارسی](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/fa) -  [Français](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/fr) - **日本語** - [한국어](https://stanford.edu/~shervine/l/ko/teaching/cs-230/cheatsheet-convolutional-neural-networks) -  [Türkçe](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/tr) - [Tiếng Việt](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/vi) で利用可能になりました

## コンテンツ
#### VIP チートシート
|<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/ja/cheatsheet-convolutional-neural-networks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/ja-001.png?" alt="Illustration" width="280px"/></a>|<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/ja/cheatsheet-recurrent-neural-networks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/ja-002.png?" alt="Illustration" width="280px"/></a>|<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/ja/cheatsheet-deep-learning-tips-tricks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/ja-003.png?" alt="Illustration" width="280px"/></a>|
|:--:|:--:|:--:|
|畳み込みニューラルネットワーク|リカレントニューラルネットワーク|アドバイスやコツ|

#### Super VIP チートシート
|<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/ja/super-cheatsheet-deep-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/ja-004.png?" alt="Illustration" width="400px"/></a>|
|---|

## 原著者
[アフシンアミディ](https://twitter.com/afshinea) (エコール・サントラル・パリ, マサチューセッツ工科大学) ・ [シェルビンアミディ](https://twitter.com/shervinea) (エコール・サントラル・パリ, スタンフォード大学)

## 訳
トラントゥアンアン・中井義之・リンダン・浜野・カムエララウ・森裕樹


================================================
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
================================================
# Derin Öğrenme El Kitabı (Stanford CS 230)

Içinde mevcut [English](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/en) -  [فارسی](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/fa) -  [Français](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/fr) - [日本語](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/ja) - [한국어](https://stanford.edu/~shervine/l/ko/teaching/cs-230/cheatsheet-convolutional-neural-networks) -  **Türkçe** - [Tiếng Việt](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/vi)

## Içindekiler
#### El Kitabı VIP
|<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/tr/cheatsheet-convolutional-neural-networks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/tr-001.png?" alt="Illustration" width="280px"/></a>|<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/tr/cheatsheet-recurrent-neural-networks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/tr-002.png?" alt="Illustration" width="280px"/></a>|<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/tr/cheatsheet-deep-learning-tips-tricks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/tr-003.png?" alt="Illustration" width="280px"/></a>|
|:--:|:--:|:--:|
|Evrişimli Sinir Ağları|Tekrarlayan Yapay Sinir Ağları|Püf noktaları ve ipuçları|

#### El Kitabı Super VIP
|<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/tr/super-cheatsheet-deep-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/tr-004.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
Ayyüce Kızrak, Yavuz Kömeçoğlu ve Başak Buluz


================================================
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 sâu cheatsheets (Stanford CS 230)

Có sẵn bằng [English](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/en) -  [فارسی](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/fa) -  [Français](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/fr) - [日本語](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/ja) - [한국어](https://stanford.edu/~shervine/l/ko/teaching/cs-230/cheatsheet-convolutional-neural-networks) -  [Türkçe](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/tr) - **Tiếng Việt**

## Nội dung
#### VIP cheatsheets
|<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/vi/cheatsheet-convolutional-neural-networks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/vi-001.png?" alt="Illustration" width="280px"/></a>|<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/vi/cheatsheet-recurrent-neural-networks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/vi-002.png?" alt="Illustration" width="280px"/></a>|<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/vi/cheatsheet-deep-learning-tips-tricks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/vi-003.png?" alt="Illustration" width="280px"/></a>|
|:--:|:--:|:--:|
|Mạng neural tích chập|Mạng neural hồi quy|Mẹo và thủ thuật trong|

#### Super VIP cheatsheet
|<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/vi/super-cheatsheet-deep-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/vi-004.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, Nguyễn Trí Minh, Hung Nguyễn, Đàm Minh Tiến, Hoàng Minh Tuấn và Phạm Hồng Vinh
Download .txt 
gitextract_vuokji89/

├── LICENSE
├── README.md
├── en/
│   ├── LICENSE
│   └── README.md
├── fa/
│   ├── LICENSE
│   └── README.md
├── fr/
│   ├── LICENSE
│   └── README.md
├── ja/
│   ├── LICENSE
│   └── README.md
├── tr/
│   ├── LICENSE
│   └── README.md
└── vi/
    ├── LICENSE
    └── README.md
Download .json
Condensed preview — 14 files, each showing path, character count, and a content snippet. Download the .json file or copy for the full structured content (25K chars). 
[
  {
    "path": "LICENSE",
    "chars": 1089,
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    "path": "en/LICENSE",
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    "preview": "# Deep Learning cheatsheets for Stanford's CS 230\nAvailable in **English** -  [فارسی](https://github.com/afshinea/stanfo"
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    "path": "fa/LICENSE",
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    "preview": "<span dir=\"rtl\" align=\"right\">\n\n# راهنماهای کوتاه یادگیری عمیق برای کلاس CS ۲۳۰ استنفرد\n\nقابل دسترسی هم در\n\n</span>\n\n[En"
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    "path": "fr/LICENSE",
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    "preview": "# Pense-bêtes de Deep Learning pour CS 230 de Stanford\nDisponible en [English](https://github.com/afshinea/stanford-cs-2"
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    "path": "ja/LICENSE",
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  },
  {
    "path": "ja/README.md",
    "chars": 1912,
    "preview": "# スタンフォードのCS 230のディープラーニングのチートシート\n\n[English](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/en) -"
  },
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    "path": "tr/LICENSE",
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    "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": 2027,
    "preview": "# Derin Öğrenme El Kitabı (Stanford CS 230)\n\nIçinde mevcut [English](https://github.com/afshinea/stanford-cs-230-deep-le"
  },
  {
    "path": "vi/LICENSE",
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    "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": 2078,
    "preview": "# Học sâu cheatsheets (Stanford CS 230)\n\nCó sẵn bằng [English](https://github.com/afshinea/stanford-cs-230-deep-learning"
  }
]

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This page contains the full source code of the afshinea/stanford-cs-230-deep-learning GitHub repository, extracted and formatted as plain text for AI agents and large language models (LLMs). The extraction includes 14 files (23.5 KB), approximately 7.1k 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.

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