Difference between revisions of "Machine Learning Experiments"
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*[https://www.youtube.com/watch?v=POrPIABj2MI A Return to Machine Learning] [Video] by Kyle McDonald | *[https://www.youtube.com/watch?v=POrPIABj2MI A Return to Machine Learning] [Video] by Kyle McDonald | ||
*[http://www.r2d3.us/visual-intro-to-machine-learning-part-1/ A visual introduction to machine learning] by r2d3. | *[http://www.r2d3.us/visual-intro-to-machine-learning-part-1/ A visual introduction to machine learning] by r2d3. | ||
* [http://blog.otoro.net/2017/01/01/recurrent-neural-network-artist/ Recurrent Neural Network Tutorial for Artists - with handwriting generation demo in p5.js] | *[http://blog.otoro.net/2017/01/01/recurrent-neural-network-artist/ Recurrent Neural Network Tutorial for Artists - with handwriting generation demo in p5.js] | ||
*[https://www.youtube.com/watch?v=nKW8Ndu7Mjw&index=2&list=PLIivdWyY5sqJxnwJhe3etaK7utrBiPBQ2 The 7 steps of Machine Learning] (2017) by Yufeng/Google Cloud | |||
==Cultural matters with Machine Learning== | ==Cultural matters with Machine Learning== | ||
Revision as of 07:48, 4 September 2017
Introduction to Machine Learning
- A Return to Machine Learning [Video] by Kyle McDonald
- A visual introduction to machine learning by r2d3.
- Recurrent Neural Network Tutorial for Artists - with handwriting generation demo in p5.js
- The 7 steps of Machine Learning (2017) by Yufeng/Google Cloud
Cultural matters with Machine Learning
- Entanglement: Machine learning and human ethics in driver-less car crashes (2017) by Maya Indira Ganesh
- Biased bots: Human prejudices sneak into AI systems by Joanna Bryson
- The Temporality of Artificial Intelligence (2017) by Kathryn Hume
Technical explanation on Machine Learning
RNN focus
- The Unreasonable Effectiveness of Recurrent Neural Networks (2015) by Andrej Karpathy
Neural Network
- How to create a Neural Network in JavaScript in only 30 lines of code (2017) by Per Harald Borgen, see sceencast here. Source code here
Examples with source code
- 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 paint: 1/ ConvNetJS Library by Andrej Karpathy 2/ Synaptic.js by Synaptic
Projects
- THE TEXT-GENERATING RNN DEMO by Ilya Sutskever
- Handwriting Generation Demo by Alex Graves
- Obama RNN by Samim
- RNN Bible on Twitter
Artworks
- Cloud index by James Bridle | Read his interview here on James Bridle: Machine Learning in Practice
- Big Data Poetry by David Jhave Johnston
Exhibition
- Artists & Robots (2017) at the Astana Contemporary Art Center in Kazakhstan
- Artificial Intelligence: The Other I (2017) Ars Electronica
Learning resource
- Daniel Shiffman's Nature of Code: Neural networks| video
- Machine Learning for Artists by Gene Kogan and Francis Tseng
- Machine Learning A-Z™: Hands-On Python & R In Data Science
- Neural Network Evolution Playground with Backprop NEAT
- ConvNetJS: Deep Learning in the Browser [Video] by Christoph Körner (more technical)
- CS231n: Convolutional Neural Networks for Visual Recognition by Standford
- Machine Learning resource list by David Jhave Johnston
Teaching Machine Learning
Experiments/Tests
- Running spam data with RecurrentJS in a local browser (Winnie)
- Running a jpg file with ConvNetJS in a local browser (Winnie)
- Running a PNG file with Synaptic.js in a local browser (Winnie)
- Running a customized neural network in a local browser (Winnie)
