Machine Learning for Artists @ OpenDot, November 2016

Course taught by @genekogan

Why machine learning for artists
  • Overview of the class, why ML for artists
  • Micro-history of AI, machine learning, and deep learning
  • Some examples of artistic ML works
  • Resources +
Neural networks
  • How neural networks work
  • Visualizing neural networks during training
  • General applications of neural nets
Real-time ML for performance
  • Basic Processing + Wekinator application
  • Using neural nets to control audio synths
  • Making music with a face tracker
Convolutional neural networks + t-SNE
  • How convnets work
  • Activations are useful; reverse image search
  • t-SNE for organizing image collections
  • t-SNE in text and audio domains
Applications of t-SNE
  • Discussion of image-to-image translation
  • Transfer learning with convnets
  • How to make audio t-SNEs
Applications of deep learning
  • Generative images; Deepdream and style transfer
  • Image to image mapping
  • LSTMs, text generation, and dense captioning