Overview: Introduction to Generative Models
Get an overview of the topics covered in this chapter.
We'll cover the following
In this chapter, we will learn the basics of generative models. We will start with a brief description of and comparison between discriminative and generative models, in which we will learn about the properties of these models. Then, we will focus on a comparison between generative models, and briefly describe how they have been used to achieve state-of-the-art models in fields such as computer vision and audio.
We will also cover other models, and then we will focus on the building blocks of GANs, their strengths, and limitations. This information is valuable because it can inform our decisions when approaching a machine learning problem with GANs, or when learning some new development in GANs.
Topics covered in this chapter
We will cover the following topics as we progress with this chapter:
Discriminative and generative models compared
Generative models
GANs: building blocks
GANs: strengths and weaknesses
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