The Neural Aesthetic @ ITP-NYU, Fall 2019

Lectures        Syllabus

03 Sep 2019
The whole class "in 60 minutes"
Description
  • Course goals, logistics, and resources
  • Introduction to AI, machine learning, and deep learning
  • The whole class "in 60 minutes"
  • Getting setup with Runway and ml5.js
Supplementary / links
10 Sep 2019
Neural networks
Description
  • How convolutional neural networks work (forward pass)
  • Transfer learning
  • Demos and applications of transfer learning
17 Sep 2019
How neural nets are trained
Description
  • How neural nets are trained (backward pass)
  • Overfitting, regularization, optimization
  • ml4a-ofx demos: ConvnetPredictor, AudioClassifier, DoodleClassifier
Supplementary / links
24 Sep 2019
Applications of neural nets
Description
  • Feature extraction
  • Reverse image search and X degrees
  • t-SNE of images/sounds & visualization
  • Transfer learning
27 Sep 2019
Terminal velocity
Description
  • Basic terminal navigation
  • Python shell and bash scripting
  • Connecting to remote VM
01 Oct 2019
Visualization, deepdream, style & texture synthesis
Description
  • Visualizing convnet features
  • Pixel-optimization, Deepdream, neural-synth
  • Style transfer and textur synthesis
Practical
08 Oct 2019
Neural-style, Paperspace, and PCA
Description
  • Principal component analysis
  • Paperspace tutorial
  • neural-style
Practical
Supplementary / links
22 Oct 2019
Generative models I
Description
  • Autoencoders & Generative adversarial networks
  • Compiling, scraping, and processing datasets
Supplementary / links
29 Oct 2019
Generative models II
Description
  • Review of generative models and GANs
  • BigGAN tutorial
  • Scraping and preparing datasets
Supplementary / links
05 Nov 2019
Generative models III
Description
  • Image-to-image translation (pix2pix/CycleGAN)
  • Tutorial on StyleGAN and DCGAN
Supplementary / links
26 Nov 2019
Music information retrieval, BIGGAN & GLOW
Description
  • GLOW and reversible generative models
  • BigGAN tutorial
  • Music information retrieval
03 Dec 2019
Reinforcement Learning & Natural Language Processing
Description
  • Natural language processing
  • Agent-environment systems & games
  • AlphaGo and AlphaZero
Supplementary / links
10 Dec 2019
Final presentations
Description
  • tbd
Practical
Supplementary / links
The whole class "in 60 minutes"
3 Sep 2019 [slides]
  • Course goals, logistics, and resources
  • Introduction to AI, machine learning, and deep learning
  • The whole class "in 60 minutes"
  • Getting setup with Runway and ml5.js