Rencontres Algolittéraires: Difference between revisions
From Algolit
| Line 29: | Line 29: | ||
==== Datasets / Ensemble de données ==== | ==== Datasets / Ensemble de données ==== | ||
* [[Many many words]] = [[Beaucoup, beaucoup de mots]] | * [[Many many words]] = [[Beaucoup, beaucoup de mots]] | ||
| − | * [[The data (e)speaks]] = [[La donnée (e)parle]] | + | * [[The data (e)speaks]] = [[La donnée (e)parle]] - needs to be completed |
=====Common public datasets / Ensembles de données publics communs===== | =====Common public datasets / Ensembles de données publics communs===== | ||
| − | * [[Common Crawl]] = [[Common Crawl FR]] | + | * [[Common Crawl]] = [[Common Crawl FR]] |
| − | * [[WikiHarass]] = [[WikiHarass FR]] | + | * [[WikiHarass]] = [[WikiHarass FR]] |
=====Algoliterary datasets / Ensembles de données Algolittéraires ===== | =====Algoliterary datasets / Ensembles de données Algolittéraires ===== | ||
| − | * [[Frankenstein]] = [[Frankenstein FR]] | + | * [[Frankenstein]] = [[Frankenstein FR]] |
| − | * [[Learning from Deep Learning]] = [[Apprendre de l'apprentissage automatique]] | + | * [[Learning from Deep Learning]] = [[Apprendre de l'apprentissage automatique]] |
| − | * [[nearbySaussure]] | + | * [[nearbySaussure]] |
| − | * [[astroBlackness]] | + | * [[astroBlackness]] |
==== From words to numbers / Des mots aux nombres ==== | ==== From words to numbers / Des mots aux nombres ==== | ||
Revision as of 12:08, 31 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 / Oeuvres Algolittéraires
- Oulipo recipes = Recettes Oulipo
- i-could-have-written-that = i-could-have-written-that FR
- The Weekly Address, A model for a politician - needs check
- In the company of CluebotNG = En compagnie de CluebotNG
Algoliterary explorations / Explorations Algolittéraires
What the Machine Writes: a closer look at the output / Ce que la machine écrit: mise au point sur la sortie
- CHARNN text generator = Générateur de texte CHARNN - needs check
- You shall know a word by the company it keeps = Vous connaîtrez un mot par la compagnie qu'il tient
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
- The data (e)speaks = La donnée (e)parle - needs to be completed
Common public datasets / Ensembles de données publics communs
Algoliterary datasets / Ensembles de données Algolittéraires
- Frankenstein = Frankenstein FR
- Learning from Deep Learning = Apprendre de l'apprentissage automatique
- nearbySaussure
- astroBlackness
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!
- The GloVe Reader = Le Lecteur GloVe - translated!
Inspecting the technique / Inspection de la technique
- word2vec_basic.py = word2vec_basic.py FR - translated! > small updates around the change of dataset, perhaps good to check?
- Reverse Algebra - ready!
How a Machine Might Speak / Comment une machine pourrait parler
Sources
- Algoliterary Toolkit = Boîte à outils Algolittéraire- translated!
- Algoliterary Bibliography = Bibliographie Algolittéraire - translated! > updated, would be nice to translate the headers