Rencontres Algolittéraires: Difference between revisions
From Algolit
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* [[In the company of CluebotNG]] = [[En compagnie de CluebotNG]] - translated! | * [[In the company of CluebotNG]] = [[En compagnie de CluebotNG]] - translated! | ||
| − | ==Algoliterary explorations== | + | ==Algoliterary explorations / Explorations Algolittéraires== |
| − | === What the Machine Writes: a closer look at the output === | + | === What the Machine Writes: a closer look at the output / Ce que la machine écrit: point de vue sur la sortie=== |
* [[CHARNN text generator]] | * [[CHARNN text generator]] | ||
* [[You shall know a word by the company it keeps]] | * [[You shall know a word by the company it keeps]] | ||
| − | === How the Machine Reads: Dissecting Neural Networks === | + | === How the Machine Reads: Dissecting Neural Networks / Comment la machine lit: dissection des réseaux neuronaux=== |
| − | ==== Datasets ==== | + | ==== Datasets / Ensemble de données ==== |
* [[Many many words]] = [[Beaucoup, beaucoup de mots]] - translated! | * [[Many many words]] = [[Beaucoup, beaucoup de mots]] - translated! | ||
* [[The data (e)speaks]] = [[La donnée (e)parle]]- translated! | * [[The data (e)speaks]] = [[La donnée (e)parle]]- translated! | ||
| − | =====Common public datasets===== | + | =====Common public datasets / Ensembles de données publics communs===== |
* [[Common Crawl]] = [[Common Crawl FR]]- translated! | * [[Common Crawl]] = [[Common Crawl FR]]- translated! | ||
* [[WikiHarass]] = [[WikiHarass FR]]- translated! | * [[WikiHarass]] = [[WikiHarass FR]]- translated! | ||
| − | =====Algoliterary datasets===== | + | =====Algoliterary datasets / Ensembles de données Algolittéraires ===== |
* [[Frankenstein]] = [[Frankenstein FR]] - translated! | * [[Frankenstein]] = [[Frankenstein FR]] - translated! | ||
* [[Learning from Deep Learning]] = [[Apprendre de l'apprentissage automatique]]- translated! | * [[Learning from Deep Learning]] = [[Apprendre de l'apprentissage automatique]]- translated! | ||
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* [[Tristes Tropiques]] | * [[Tristes Tropiques]] | ||
| − | ==== From words to numbers ==== | + | ==== From words to numbers / Des mots aux nombres ==== |
* [[A Bag of Words]] = [[Un sac de mots]] - translated! | * [[A Bag of Words]] = [[Un sac de mots]] - translated! | ||
* [[A One Hot Vector]] = [[Un vecteur one-hot]] - translated! | * [[A One Hot Vector]] = [[Un vecteur one-hot]] - translated! | ||
| − | ==== Special Focus: Word Embeddings ==== | + | ==== Special Focus: Word Embeddings / Focus spécial: le plongement lexical ==== |
* [[About Word embeddings]] = [[Sur le plongement lexical]] - translated! | * [[About Word embeddings]] = [[Sur le plongement lexical]] - translated! | ||
* [[Crowd Embeddings]] = [[Crowd Embeddings FR]] - translated! | * [[Crowd Embeddings]] = [[Crowd Embeddings FR]] - translated! | ||
| − | ===== Different portraits of word embeddings ===== | + | ===== Different portraits of word embeddings / Différents portraits du plongement lexical ===== |
* [[Word embedding Projector]] = [[Projecteur de plongement lexical]] - translated! | * [[Word embedding Projector]] = [[Projecteur de plongement lexical]] - translated! | ||
* [[5 dimensions 32 graphs]] | * [[5 dimensions 32 graphs]] | ||
* [[The GloVe Reader]] = [[Le Lecteur GloVe]] - translated! | * [[The GloVe Reader]] = [[Le Lecteur GloVe]] - translated! | ||
| − | ===== Inspecting the technique ===== | + | ===== Inspecting the technique / Inspection de la technique ===== |
* [[word2vec_basic.py]] = [[word2vec_basic.py FR]] - translated! | * [[word2vec_basic.py]] = [[word2vec_basic.py FR]] - translated! | ||
* [[Reverse Algebra]] | * [[Reverse Algebra]] | ||
Revision as of 11:55, 28 October 2017
Hey Emma,
This is a start of the French version of the Algoliterary Encounters catalog. We marked the pages below that are ready to be translated.
It would be nice to translate the titles of the works into French as well, the titles below are still the English ones. And it would be great if you could do the headers as well.
Thanks a lot!
---
General Introduction / Introduction Générale
Algoliterary works / Travaux Algolittéraires
- Oulipo recipes = Recettes Oulipo - already translated!
- i-could-have-written-that = i-could-have-written that FR - translated!
- Obama, model for a politician
- In the company of CluebotNG = En compagnie de CluebotNG - translated!
Algoliterary explorations / Explorations Algolittéraires
What the Machine Writes: a closer look at the output / Ce que la machine écrit: point de vue sur la sortie
How the Machine Reads: Dissecting Neural Networks / Comment la machine lit: dissection des réseaux neuronaux
Datasets / Ensemble de données
- Many many words = Beaucoup, beaucoup de mots - translated!
- The data (e)speaks = La donnée (e)parle- translated!
Common public datasets / Ensembles de données publics communs
- Common Crawl = Common Crawl FR- translated!
- WikiHarass = WikiHarass FR- translated!
Algoliterary datasets / Ensembles de données Algolittéraires
- Frankenstein = Frankenstein FR - translated!
- Learning from Deep Learning = Apprendre de l'apprentissage automatique- translated!
- AnarchFem
- Tristes Tropiques
From words to numbers / Des mots aux nombres
- A Bag of Words = Un sac de mots - translated!
- A One Hot Vector = Un vecteur one-hot - translated!
Special Focus: Word Embeddings / Focus spécial: le plongement lexical
- About Word embeddings = Sur le plongement lexical - translated!
- Crowd Embeddings = Crowd Embeddings FR - translated!
Different portraits of word embeddings / Différents portraits du plongement lexical
- Word embedding Projector = Projecteur de plongement lexical - translated!
- 5 dimensions 32 graphs
- The GloVe Reader = Le Lecteur GloVe - translated!
Inspecting the technique / Inspection de la technique
- word2vec_basic.py = word2vec_basic.py FR - translated!
- Reverse Algebra
How a Machine Might Speak / Comment une machine pourrait parler
Sources
- Algoliterary Toolkit - no translation needed!
- Algoliterary Bibliography = Bibliographie Algolittéraire - translated!