Difference between revisions of "Machine Learning Experiments"

From Software Studies
Jump to navigation Jump to search
Line 9: Line 9:
*[http://www.bath.ac.uk/research/news/2017/04/13/biased-bots-artificial-intelligence/ Biased bots: Human prejudices sneak into AI systems] by Joanna Bryson   
*[http://www.bath.ac.uk/research/news/2017/04/13/biased-bots-artificial-intelligence/ Biased bots: Human prejudices sneak into AI systems] by Joanna Bryson   
*[https://quamproxime.com/2017/07/30/the-temporality-of-artificial-intelligence/ The Temporality of Artificial Intelligence (2017)] by Kathryn Hume
*[https://quamproxime.com/2017/07/30/the-temporality-of-artificial-intelligence/ The Temporality of Artificial Intelligence (2017)] by Kathryn Hume
*Mackenzie Adrian, [http://www.realtechsupport.org/UB/ML+CT/papers/Mackenzie_Production_of_Prediction_2015.pdf The production of prediction: What does  machine learning want?],European Journal of Cultural Studies2015, Vol.18(4-5) 429–445
*[https://www.academia.edu/34471806/Automating_Aesthetics_Artificial_Intelligence_and_Image_Culture?auto=download&campaign=weekly_digest Automating Aesthetics: Artificial Intelligence and Image Culture] (2017) by Lev Manovich
*[https://www.academia.edu/34471806/Automating_Aesthetics_Artificial_Intelligence_and_Image_Culture?auto=download&campaign=weekly_digest Automating Aesthetics: Artificial Intelligence and Image Culture] (2017) by Lev Manovich
*Ed Finn, "Building the Star Trek Computer," in [https://mitpress.mit.edu/books/what-algorithms-want What Algorithms Want], MIT Press, 2017, pp. 57-85.
*Ed Finn, "Building the Star Trek Computer," in [https://mitpress.mit.edu/books/what-algorithms-want What Algorithms Want], MIT Press, 2017, pp. 57-85.

Revision as of 14:17, 21 November 2017

Introduction to Machine Learning

Cultural matters with Machine Learning

Technical explanation on Machine Learning

RNN focus

Neural Network

Examples with source code

Text related

  • Chinese receipt OCR using Tensorflow | SpikeFlow (Blog | Github)
  • Recurrentjs by Andrej Karpathy, mainly for text training. "Sentences are input data and the networks are trained to predict the next character in a sentence." + his interview on why javascript and machine learning.
  • Re-appropriation of Recurrentjs by UCL Creative Hub

Image related

Projects

Text related

Artworks

Exhibition

Workshop

Demo/Experimental Projects

Learning resource

Teaching Machine Learning

Experiments/Tests

  • Running spam data with RecurrentJS in a local browser (Winnie)
Running spam data with RecurrentJS
  • Running a jpg file with ConvNetJS in a local browser (Winnie)
Learning a jpg file with ConvNetJS
  • Running a PNG file with Synaptic.js in a local browser (Winnie)
Learning a png file with Synaptic
  • Running a customized neural network in a local browser (Winnie)
Learning XOR with Synaptic