2016

Introduction, neural networks

Introduction (0:00)
Machine learning and neural networks (11:03)
Demo forward pass and MNIST (23:45)
Visualizing the weights (52:17)
MNIST/CIFAR confusion matrix (1:02:50)
Convolutional neural network demo (1:21:52)
Applications of convnets (1:43:58)

Supervised and unsupervised learning
Linear classifiers
What are neural networks
- Forward pass demo
- MNIST forward pass
- visualizing weights
- Limitations of ordinary neural nets
Convolutional neural networks (quick run-through)
- Convolution + pooling layers
- ofxCcv demo
- Applications of activations
  - Probing neurons, Deepdream, Style transfer
  - t-SNE visualization