Difference between revisions of "Machine Learning Experiments"
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* Chinese receipt OCR using Tensorflow | SpikeFlow ([https://deeperic.wordpress.com/2017/02/18/chinese-ocr-tensorflow/ Blog] | [https://github.com/deeperic/SpikeFlow Github]) | * Chinese receipt OCR using Tensorflow | SpikeFlow ([https://deeperic.wordpress.com/2017/02/18/chinese-ocr-tensorflow/ Blog] | [https://github.com/deeperic/SpikeFlow Github]) | ||
* [https://github.com/karpathy/recurrentjs 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." | * [https://github.com/karpathy/recurrentjs 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 [https://www.datascienceweekly.org/data-scientist-interviews/training-deep-learning-models-browser-andrej-karpathy-interview interview] on why javascript and machine learning. | ||
* Re-appropriation of Recurrentjs by [http://artist.ai/index.php/home/poems/ UCL Creative Hub] | * Re-appropriation of Recurrentjs by [http://artist.ai/index.php/home/poems/ UCL Creative Hub] | ||
[Image related] | [Image related] | ||
Revision as of 10:04, 10 August 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
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
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]
- Image paint: 1/ ConvNetJS Library by Andrej Karpathy 2/ Synaptic.js by Synaptic
Projects
[Text related]
- 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 Jhava Johnston
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)
- Machine Learning resource list by David Jhave Johnston
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)
