Algoliterary Encounters: Difference between revisions
From Algolit
(→multidimensionality) |
|||
| Line 3: | Line 3: | ||
Start of the Algoliterary Encounters catalog. | Start of the Algoliterary Encounters catalog. | ||
| − | + | == General Introduction == | |
* [[Introduction Algolit]] | * [[Introduction Algolit]] | ||
| − | |||
| − | ==== | + | ==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 | ||
| + | * [[talking_about_machine_learning]] - exploring the vocabulary of machine learning textbooks in 7 stages with word2vec | ||
| + | |||
| + | ===Parts of NN process=== | ||
| + | |||
| + | ==== Datasets ==== | ||
| + | * [[the data speaks]] | ||
| − | * [[ | + | ==== From words to numbers ==== |
| − | * [[ | + | * [[bag-of-words]] |
| − | + | * [[one-hot-vector script]] & [[word embeddings]] | |
| − | |||
| − | ==== | + | ==== Different views on the data ==== |
| + | * tensorflow projector visualisation of high dimensional data | ||
| + | * [[5 dimensions 32 graphs]] | ||
| + | * GloVe dataset sorted alphabetically | ||
| − | * [[introduction | + | ==== 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 | ||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
===== multidimensionality ===== | ===== multidimensionality ===== | ||
| Line 54: | Line 60: | ||
* digital interactive visualisation & printed visualisation 1 poster for 1 dimension (total could be 30 posters) | * digital interactive visualisation & printed visualisation 1 poster for 1 dimension (total could be 30 posters) | ||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
===== output ===== | ===== output ===== | ||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
Revision as of 15:54, 6 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
- 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
multidimensionality
"In most of the cases the meaning will come through multiple dimensions." (Richard Socher, CS224D Lecture 2)
- digital interactive visualisation & printed visualisation 1 poster for 1 dimension (total could be 30 posters)