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cheatsheet-translation's Introduction

Translation of VIP Cheatsheets

Goal

This repository aims at collaboratively translating our Machine Learning, Deep Learning and Artificial Intelligence cheatsheets into a ton of languages, so that this content can be enjoyed by anyone from any part of the world!

Contribution guidelines

The translation process of each cheatsheet contains two steps:

  • the translation step, where contributors follow a template of items to translate,
  • the review step, where contributors go through each expression translated by their peers, on top of which they add their suggestions and remarks.

Translators

  1. Check for existing pull requests to see which cheatsheet is yet to be translated.

  2. Fork the repository.

  3. Copy the template of the cheatsheet you wish to translate into the language folder with a naming that follows the ISO 639-1 notation (e.g. [es] for Spanish, [zh] for Mandarin Chinese).

  4. Translate sentences by keeping the following structure:

  1. English blabla

⟶ Translated blabla

  1. Commit the changes to your forked repository.

  2. Submit a pull request and call it [language code] file-name. For example, the PR related to the translation in Spanish of the template/cs-229-deep-learning.md cheatsheet will be entitled [es] cs-229-deep-learning.

Reviewers

  1. Go to the list of pull requests and filter them by your native language.

  2. Locate pull requests where help is needed. Those contain the tag reviewer wanted.

  3. Review the content line per line and add comments and suggestions when necessary.

Important note

Please make sure to propose the translation of only one cheatsheet per pull request -- it simplifies a lot the review process.

Progression

CS 221 (Artificial Intelligence)

Reflex models States models Variables models Logic models
Deutsch not started not started not started not started
Español not started not started not started not started
فارسی in progress not started not started not started
Français done done done done
עִבְרִית not started not started not started not started
Italiano not started not started not started not started
日本語 not started not started not started not started
한국어 not started not started not started not started
Português not started not started not started not started
Русский in progress in progress in progress in progress
Türkçe done done done done
Tiếng Việt not started not started not started done
简体中文 not started not started not started not started
繁體中文 not started not started not started not started

CS 229 (Machine Learning)

Deep learning Supervised Unsupervised ML tips Probabilities Algebra
العَرَبِيَّة done done done done done done
Català not started not started not started in progress in progress in progress
Deutsch done not started not started in progress not started in progress
Ελληνικά not started not started not started in progress not started not started
Español done done done done done done
Eesti not started not started not started done not started not started
فارسی done done done done done done
Suomi in progress not started not started not started not started not started
Français done done done done done done
עִבְרִית in progress not started not started not started not started not started
हिन्दी in progress in progress not started in progress not started not started
Magyar in progress in progress in progress in progress in progress in progress
Bahasa Indonesia in progress not started in progress not started done done
Italiano in progress in progress not started not started done done
日本語 done done done done done done
한국어 done done done done done done
Polski in progress in progress not started in progress in progress not started
Português done done done done done done
Русский in progress in progress in progress in progress in progress in progress
Türkçe done done done done done done
Українська not started not started not started not started done in progress
Tiếng Việt done done done done done done
简体中文 in progress done in progress in progress in progress in progress
繁體中文 done done done done done done

CS 230 (Deep Learning)

Convolutional Neural Networks Recurrent Neural Networks Deep Learning tips
العَرَبِيَّة not started not started not started
Català not started not started not started
Deutsch not started not started not started
Español not started not started in progress
فارسی done done done
Suomi not started not started not started
Français done done done
עִבְרִית not started not started not started
हिन्दी not started not started not started
Magyar not started not started not started
Bahasa Indonesia done in progress in progress
Italiano not started not started not started
日本語 done done done
한국어 done in progress in progress
Polski not started not started not started
Português done not started not started
Русский in progress in progress in progress
Türkçe done done done
Українська not started not started not started
Tiếng Việt done done done
简体中文 in progress in progress not started
繁體中文 done not started not started

Acknowledgements

Thank you everyone for your help! Please do not forget to add your name to the CONTRIBUTORS file so that we can give you proper credit in the cheatsheets' official website.

cheatsheet-translation's People

Contributors

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cheatsheet-translation's Issues

No templates for CS230

Hello there,

Great work with the cheat sheets. I want to contribute to the translations of the CS 230 but I do not see the templates for it.
Can you add them?

Thanks

Typos and improvements

Hi. I think in this issue we can discuss explanations that could be improved or typos that we have found. For example. while I was translating the Deep Learning cheatsheet to Spanish, I came across a few things:

  • [IMPROVEMENT] in [21], instead of:

... F the size of the convolutional layer neurons

I would say " ... F the size of the convolution kernel". This is the word that is most commonly used in deep learning frameworks like Keras.

  • [IMPROVEMENT] also in [21], instead of:

... the number of neurons N that fit in a given volume is such that

I would say something like "... the size N of the output volume, is".

  • [TYPO] in [22]:

Batch normalization ― It is a step of hyperparameter γ,β that normalizes the batch {xi}.

Do you mean "It is a set of hyperparameters ... "?

Possible typo in Supervised Learning file?

In the item 77 of the supervised learning file is written the following:
77. Hoeffding inequality ― Let Z1,..,Zm be m iid variables drawn from a Bernoulli distribution of parameter ϕ. Let ˆϕ be their sample mean and γ>0 fixed. We have:

Is the part m iid variables right?

Refresher Linear Algebra

In the line 25 of the file refresher-linear-algebra.md the text below is written:
5. Matrix ― We note A∈Rm×n a matrix with n rows and m, where Ai,j∈R is the entry located in the ith row and jth column:

In my opinion, m should refer to rows and n to columns as stated below:
5. Matrix ― We note A∈Rm×n a matrix with m rows and n columns, where Ai,j∈R is the entry located in the ith row and jth column:

Chinese[zh] Translation

Some minor terminology correction:
On the first page of Supervised Learning——

“Model Type”

would better be translated to

“模型类型”

instead of

"型号类型"

[en] Deep learning - possible typo?

Shouldn't line:
39. Remark: we say that we execute a given policy π if given a state a we take the action a=π(s).
be:
39. Remark: we say that we execute a given policy π if given a state s we take the action a=π(s).

Separator errors

75. [E-step: Evaluate the posterior probability q(h) that each data point e came from a particular cluster h as follows:,M-step: Use the posterior probabilities q(h) as cluster specific weights on data points e to determine θ through maximum likelihood.]

⟶ [Шаг E: Оценить апостериорную вероятность q(h) того, что каждая точка данных e из определенного кластера h следующим образом:, M-шаг: использовать апостериорные вероятности q(h) в качестве весовых коэффициентов для конкретных кластеров точек данных e, чтобы определить θ через максимальное правдоподобие.]

A comma in English is required only if the sentence can be misunderstood without it. In Russian, a punctuation mark appears regardless of the length of simple sentences that make up a complex one.
I paint and she writes. Я рисую, а она пишет.

Maybe it's better to use a different separator in arrays, for example, a semicolon «;»?

Standarization of certain terms

For example, there is not a word in Spanish for "cheatsheet". There exist some words but they are used by certain regions, (In my opinion). I was thinking of translations as "Hoja de ayuda" but I found a translator used "Hoja de trucos", which seems better to me.

Like "cheatsheet", there are other terms/words that don't have a simple translation and 2 translator could use different words. I propose to standardize some expressions looking for the consistency across all the material.

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