Difference between revisions of "Machine Learning Experiments"

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*Running ml5.js example - Simple Image Classification Example on a local browser (Winnie)
*Running ml5.js example - Simple Image Classification Example on a local browser (Winnie)
[[File:Ml5.png|none|400px|Predicting what's the image with confidence level]]
[[File:Ml5.png|none|400px|Predicting what's the image with confidence level]]
*Running ml5.js example - Simple LSTM Generator Example on a local browser (Winnie)
[[File:LSTMText.png|none|400px|Predicting what's the text]]

Revision as of 10:13, 5 April 2018

Introduction to Machine Learning

Cultural matters with Machine Learning

Technical explanation on Machine Learning

RNN focus

Neural Network

Examples with source code

Mixed media (text/image)

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

Sound related

Projects

Text related

Artworks

Exhibition

Workshop

Demo/Experimental Projects

Learning resource

Teaching Machine Learning

Experiments/Tests

  • Running spam data with RecurrentJS on a local browser (Winnie)
Running spam data with RecurrentJS
  • Running a jpg file with ConvNetJS on a local browser (Winnie)
Learning a jpg file with ConvNetJS
  • Running a PNG file with Synaptic.js on a local browser (Winnie)
Learning a png file with Synaptic
  • Running a customized neural network on a local browser (Winnie)
Learning XOR with Synaptic
  • Running ml5.js example - Simple Image Classification Example on a local browser (Winnie)
Predicting what's the image with confidence level
  • Running ml5.js example - Simple LSTM Generator Example on a local browser (Winnie)
Predicting what's the text