April 2017
Intermediate to advanced
318 pages
7h 40m
English
Generative models are models that learn to create data similar to data it is trained on. We saw one example of a generative model that learns to write prose similar to Alice in Wonderland in Chapter 6, Recurrent Neural Network — RNN. In that example, we trained a model to predict the 11th character of text given the first 10 characters. Yet another type of generative model is generative adversarial models (GAN) that have recently emerged as a very powerful class of models—you saw examples of GANs in Chapter 4, Generative Adversarial Networks and WaveNet. The intuition for generative models is that it learns a good internal representation of its training data, and is therefore able to generate similar data during the prediction ...