Algoliterary Encounters: Difference between revisions
From Algolit
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* [[Google News]] (used by word2vec) | * [[Google News]] (used by word2vec) | ||
* [[Frankenstein]] | * [[Frankenstein]] | ||
| − | * [[Learning from Deep Learning]] | + | * [[Learning from Deep Learning]] |
| − | * [[HG Wells personal dataset]] | + | * [[HG Wells personal dataset]] |
* Jules Verne (FR), Shakespeare (FR) -> download from Gutenberg & clean up | * Jules Verne (FR), Shakespeare (FR) -> download from Gutenberg & clean up | ||
| − | * [[AnarchFem]] | + | * [[AnarchFem]] |
* [[WikiHarass]] | * [[WikiHarass]] | ||
* [[Tristes Tropiques]] | * [[Tristes Tropiques]] | ||
Revision as of 22:09, 24 October 2017
Start of the Algoliterary Encounters catalog.
General Introduction
Algoliterary works
- Oulipo scripts
- i-could-have-written-that
- Obama, model for a politician
- ClueBotNG, a special Algolit edition
Algoliterary explorations
A few outputs to see how it works
- CHARNN text generator
- You shall know a word by the company it keeps - Five word2vec graphs, each of them containing the words 'collective', 'being' and 'social'.
Parts of NN process
Datasets
- Many many words - introduction to the datasets with calculation exercise
- The data (e)speaks - espeak installation
- The Enron email archive
- Common Crawl (used by GloVe): selection of urls (Constant, Maison du Livre...)
- Google News (used by word2vec)
- Frankenstein
- Learning from Deep Learning
- HG Wells personal dataset
- Jules Verne (FR), Shakespeare (FR) -> download from Gutenberg & clean up
- AnarchFem
- WikiHarass
- Tristes Tropiques
From words to numbers
Different views on the data
Creating word embeddings using word2vec
- word2vec applications - this can serve as an introduction to word2vec?
- word2vec_basic.py - in piles of paper
- softmax annotated
- chatbot for word mathematics
Autonomous machine as inspection
Algoliterary Toolkit
Bibliography
- Algoliterary Bibliography - Reading Room texts