Algoliterary Encounters: Difference between revisions
From Algolit
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===A few outputs to see how it works=== | ===A few outputs to see how it works=== | ||
* CHARNN text generator | * CHARNN text generator | ||
| − | * [[talking_about_machine_learning]] - exploring the vocabulary of machine learning textbooks in 7 stages with word2vec | + | * [[human & view & power in 5 landscapes]] - Five word2vec graphs, each of them containing the words 'human', 'view' and 'power'. (Before: [[talking_about_machine_learning]] - exploring the vocabulary of machine learning textbooks in 7 stages with word2vec) |
===Parts of NN process=== | ===Parts of NN process=== | ||
Revision as of 20:13, 16 October 2017
Start of the Algoliterary Encounters catalog.
General Introduction
Algoliterary works
- Oulipo scripts
- i-could-have-written-that interfaces
- Obama, model for a politician
- ClueBotNG, a special Algolit edition
Algoliterary explorations
A few outputs to see how it works
- CHARNN text generator
- human & view & power in 5 landscapes - Five word2vec graphs, each of them containing the words 'human', 'view' and 'power'. (Before: talking_about_machine_learning - exploring the vocabulary of machine learning textbooks in 7 stages with word2vec)
Parts of NN process
Datasets
From words to numbers
Different views on the data
- tensorflow projector visualisation of high dimensional data
- 5 dimensions 32 graphs
- GloVe dataset sorted alphabetically
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
- AI script showing racist bias using supervised classical ML & NN embeddings
Algoliterary Toolkit
- cgi interface template
- text-punctuation-clean-up.py
Bibliography
- Algoliterary Bibliography - Reading Room texts