Algoliterary Encounters: Difference between revisions
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*[https://gitlab.constantvzw.org/algolit/algolit/tree/master/algoliterary_encounter Algoliterary Gitlab] | *[https://gitlab.constantvzw.org/algolit/algolit/tree/master/algoliterary_encounter Algoliterary Gitlab] | ||
*[https://gitlab.constantvzw.org/algolit/algolit/tree/master/algoliterary_encounter/algoliterary-toolkit/cgi-example jinja-cgi interface template] | *[https://gitlab.constantvzw.org/algolit/algolit/tree/master/algoliterary_encounter/algoliterary-toolkit/cgi-example jinja-cgi interface template] | ||
Revision as of 16:06, 25 October 2017
Start of the Algoliterary Encounters catalog.
Introduction
Algoliterary works
- Oulipo recipes
- i-could-have-written-that
- Obama, model for a politician
- In the company of CluebotNG
Algoliterary explorations
What the Machine Writes: a closer look at the output
- 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'.
How the Machine Reads: Dissecting Neural Networks
Datasets
- Many many words - introduction to the datasets with calculation exercise
- The data (e)speaks - espeak installation
From words to numbers
Special Focus: Word Embeddings
- word embeddings
- Crowd Embeddings - case studies, still needs fine tuning
Different portraits of word embeddings
Inspecting the technique
- word2vec_basic.py - in piles of paper
- softmax annotated
- Reverse Algebra
How a Machine Might Speak
Sources
Code
Bibliography
- Algoliterary Bibliography - Reading Room texts