Lecture 13 - AsyDynamics/CS231n Wiki
Unsupervised learning
Supervised learning
Data(x,y); x is data, y is label Goal: train function, to map from x to y
Unsupervised learning
Data, no label; cheap! Goal: learn underlying hidden structure of the data Example: Clustering, dimensionality reduction, feature learning, density estimation
Generative model
Given training data, generate new samples from same distribution
- GAN
- PixelRNN/CNN
- Variational autoecoder VAE