Do Androids Dream of Electronic Dance Music?

Slides for my RubyKaigi 2017 talk on machine learning + music, co-presented with the inimitable Julian Cheal!

Transcript

1. Do Androids Dream of
   Electronic Dance Music?
   Julian Cheal and Eric Weinstein
   # Ruby Kaigi 2017
   # Hiroshima, Japan
   # 18 September 2017
   

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2. Do Androids What now?
   

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3. Part 0: Hello! こんにちは!
   

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4. Who Are We?
   

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5. Julian Cheal
   Rubyist
   RedHat
   

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6. Bath
   

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9. About Eric
   eric_weinstein = { # エリック
   employer: 'Fox Networks Group',
   github: 'ericqweinstein',
   twitter: 'ericqweinstein',
   website: 'ericweinste.in'
   }
   30% off with KAIGI30!
   

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10. Agenda
    • Introduction to machine learning
    • Neural networks, RNNs, and LSTM RNNs
    • Midi
    • Demo! Synths!?
    • Questions?
    

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11. Part 1: Machine Learning
    

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12. bit.ly/EricsMLTalk
    

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13. What Is It?
    • Machine learning is generalization
    • Supervised learning is generalizing from

    labeled data to unlabeled data
    

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14. Supervised Learning
    • Classification or regression
    • Learning patterns from labeled data, then
    generalizing to unlabeled data
    

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15. Part 2: Neural Networks
    

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16. • An artificial neural network is a machine learning
    model that mimics the structure and function of a
    biological brain
    • In our case, we’re interested in a particular kind
    of recurrent neural network:

    LSTM (long/short-term memory) network
    What Is It?
    

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17. Image credit: https://github.com/cdipaolo/goml/tree/master/perceptron
    

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18. Image credit: https://en.wikipedia.org/wiki/Artificial_neural_network
    

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19. Image credit: https://leonardoaraujosantos.gitbooks.io/artificial-
    inteligence/content/recurrent_neural_networks.html
    

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20. Part 3: Midi
    

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21. bit.ly/JuliansMusicTalk
    

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22. What is Midi?
    Dave Smith
    “Father of Midi”
    Midi invented in 1983
    

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23. Midi Note Data
    

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24. Midi Note Data
    

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25. Find some Data
    

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26. deadmau5 - Chimaera
    https://splice.com/sounds/
    splice/deadmau5-chimaera
    

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27. Convert the Data
    Midi TFRecord
    

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28. Convert the Data
    

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29. Moar Data
    

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30. Bring your Own Data
    

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32. Show me the Code
    

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33. Part 4: Dance Party
    

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34. Overview
    • The technology (Python, Ruby, Tensorflow, Magenta)
    • The architecture of our neural network
    • How did training go?
    • Demo time/dance party!
    

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35. We need More Ruby!
    • Python 93.4%
    • Ruby 4.8%
    • Shell 1.8%
    WTF!
    This is Ruby Kaigi
    

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37. Summary
    • Machine learning is generalization
    • Neural networks are machine learning models based on
    biological brains
    • RNNs are a kind of NN with “loop”; feedback allows
    modeling for text prediction, music generation, and
    more
    • We can do this all with Ruby, we just need the library
    support!
    

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38. 3.times { puts 'ありがとう!' }
    

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39. Questions?
    @ericqweinstein
    @juliancheal
    

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