Modeling Classes

Learn about modeling classes and making discriminative models.

What are generative models

This chapter is an introduction to the important topic of building generative models. These are models that are aimed at understanding the variety of a class, such as cars or trees. A generative model should be able to do the following:

  • Generate feature vectors for the instances of the class they represent.
  • Characterize the class with all its variations.

We’ll discuss this subject both in a Bayesian and a deep learning context and also within a supervised and unsupervised context.

The following important algorithms are discussed in this chapter:

  • kk-means clustering
  • Expectation maximization (EM)\text{(EM)}
  • Naïve Bayes
  • Generative adversarial networks (GANs)\text{(GANs)}
  • Variational autoencoders (VAE)(\text{VAE})

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