Chapter 6. Autoencoders
"People worry that computers will get too smart and take over the world, but the real problem is that they're too stupid and they've already taken over the world." | ||
| --Pedro Domingos | ||
In the last chapter, we discussed a generative model called Restricted Boltzmann machine. In this chapter, we will introduce one more generative model called autoencoder. Autoencoder, a type of artificial neural network, is generally used for dimensionality reduction, feature learning, or extraction.
As we move on with this chapter, we will discuss the concept of autoencoder and its various forms in detail. We will also explain the terms regularized autoencoder and sparse autoencoder. The concept of sparse coding, and selection criteria of the sparse factor in a sparse autoencoder will be taken up. Later, we will talk about the deep learning model, deep autoencoder, and its implementation using Deeplearning4j. Denoising autoencoder is one...
