Difference between revisions of "Machine Learning Experiments"

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*[http://colah.github.io/posts/2015-08-Understanding-LSTMs/ Understanding LSTM Networks] (2015) by Christopher Colah
*[http://colah.github.io/posts/2015-08-Understanding-LSTMs/ Understanding LSTM Networks] (2015) by Christopher Colah
*[http://karpathy.github.io/2015/05/21/rnn-effectiveness/ The Unreasonable Effectiveness of Recurrent Neural Networks] (2015) by Andrej Karpathy
*[http://karpathy.github.io/2015/05/21/rnn-effectiveness/ The Unreasonable Effectiveness of Recurrent Neural Networks] (2015) by Andrej Karpathy
*[https://skillsmatter.com/skillscasts/6611-visualizing-and-understanding-recurrent-networks Visualizing and Understanding Recurrent Networks (Video)] (2015) by Andrej Karpathy
*[https://www.mitpressjournals.org/doi/pdf/10.1162/089976600300015015 Learning to Forget: Continual Prediction with LSTM] (2000) by Felix A. Gers, Jürgen Schmidhuber and Fred Cummins
*[https://www.mitpressjournals.org/doi/pdf/10.1162/089976600300015015 Learning to Forget: Continual Prediction with LSTM] (2000) by Felix A. Gers, Jürgen Schmidhuber and Fred Cummins
*[https://www.youtube.com/watch?v=56TYLaQN4N8 Deep Learning Lecture 12: Recurrent Neural Nets and LSTMs (video)] (2015) by Nando de Freitas (start at 4:10)
*[https://www.youtube.com/watch?v=56TYLaQN4N8 Deep Learning Lecture 12: Recurrent Neural Nets and LSTMs (video)] (2015) by Nando de Freitas (start at 4:10)

Revision as of 13:38, 7 December 2018

Introduction to Machine Learning

Cultural matters with Machine Learning

Technical explanation on Machine Learning

RNN/LSTM focus

Neural Network

Examples with source code

Mixed media (text/image)

Text related

Image related

Sound related

Projects

Text related

Artworks

Examples/Performance/Speculative design

Exhibition

Workshop

Conference

Preconference Workshop] (2018)

Demo/Experimental Projects

Learning resource

Teaching Machine Learning

Experiments/Tests

  • 11/2018: Try running LSTM/tensorflow training with Python (following text predictor)from my PhD thesis text
PhD thesis
  • 11/2018: Try running local ml5 + python training with English text (multiple manifestos) and generate 10000 characters text from multiple manifestos
manifestos
  • 06/2018: Try running LSTM ml5js with training simplied chinese data. Source from weiboscope 2012 week 1 deleted text
weiboscope text
  • 06/2018: Running LSTM ml5js example with my own training data
Training Process
Outcome Process
  • 2018: Running ml5.js example - Simple LSTM Generator Example on a local browser
Predicting what's the text
  • Running ml5.js example - Simple Image Classification Example on a local browser
Predicting what's the image with confidence level
  • Running spam data with RecurrentJS on a local browser
Running spam data with RecurrentJS
  • Running a customized neural network on a local browser
Learning XOR with Synaptic
  • Running a PNG file with Synaptic.js on a local browser
Learning a png file with Synaptic
  • Running a jpg file with ConvNetJS on a local browser
Learning a jpg file with ConvNetJS