GANs in a nutshell
GANs were theorized in a famous paper that dates back to 2014 (https://arxiv.org/abs/1406.2661), written by a team of researchers including Ian Goodfellow and Yoshua Bengio, which described the potential and characteristics of a special category of adversarial processes, called GANs.
The basic idea behind GANs is simple, as they consist of putting two neural networks in competition with one another, until a balanced condition of results is achieved; however at the same time, the possibilities of using these intuitions are almost unlimited, since GANs are able to learn how to imitate and artificially reproduce any data distribution, whether it represents faces, voices, texts, or even works of art.
In this chapter, we will ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Read now
Unlock full access