Rencontres Algolittéraires: Difference between revisions
From Algolit
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==== Datasets ==== | ==== Datasets ==== | ||
| − | * [[Many many words]] | + | * [[Many many words]] = [[Beaucoup, beaucoup de mots]] - translated! |
| − | * [[The data (e)speaks]] - | + | * [[The data (e)speaks]] = [[La donnée (e)parle]]- translated! |
=====Common public datasets===== | =====Common public datasets===== | ||
| − | * [[Common Crawl]] - | + | * [[Common Crawl]] = [[Crawl Commun]]- translated! |
| − | * [[WikiHarass]] - | + | * [[WikiHarass]] = [[WikiHarass FR]]- translated! |
=====Algoliterary datasets===== | =====Algoliterary datasets===== | ||
| − | * [[Frankenstein]] - | + | * [[Frankenstein]] = [[Frankenstein FR]] - translated! |
| − | * [[Learning from Deep Learning]] - | + | * [[Learning from Deep Learning]] = [[Apprendre de l'apprentissage automatique]]- translated! |
* [[AnarchFem]] | * [[AnarchFem]] | ||
* [[Tristes Tropiques]] | * [[Tristes Tropiques]] | ||
Revision as of 13:47, 27 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
Algoliterary works
- Oulipo recipes = Oulipo recettes - 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
What the Machine Writes: a closer look at the output
How the Machine Reads: Dissecting Neural Networks
Datasets
- Many many words = Beaucoup, beaucoup de mots - translated!
- The data (e)speaks = La donnée (e)parle- translated!
Common public datasets
- Common Crawl = Crawl Commun- translated!
- WikiHarass = WikiHarass FR- translated!
Algoliterary datasets
- Frankenstein = Frankenstein FR - translated!
- Learning from Deep Learning = Apprendre de l'apprentissage automatique- translated!
- AnarchFem
- Tristes Tropiques
From words to numbers
- A Bag of Words - ready!
- A One Hot Vector - ready!
Special Focus: Word Embeddings
- About Word embeddings - ready!
- Crowd Embeddings - ready!
Different portraits of word embeddings
- Word embedding Projector - ready!
- 5 dimensions 32 graphs
- The GloVe Reader - ready!
Inspecting the technique
- word2vec_basic.py - ready!
- Reverse Algebra
How a Machine Might Speak
- We Are A Sentiment Thermometer - ready!
Sources
- Algoliterary Toolkit - no translation needed!
- Algoliterary Bibliography - ready!