What is a “generative adversarial network” (GAN)?
a) A class of neural networks used for generating new data by competing against each other
b) A method to reduce the dimensionality of data
c) A type of reinforcement learning algorithm
d) A network architecture used to classify data
Answer:
a) A class of neural networks used for generating new data by competing against each other
Explanation:
Generative Adversarial Networks (GANs) consist of two neural networks, a generator and a discriminator, that compete against each other. The generator creates new data, while the discriminator evaluates how well the generated data matches the real data.
The goal of the generator is to create data that is indistinguishable from real data, while the discriminator aims to correctly identify whether the data is real or fake. This adversarial process helps the generator improve its ability to create realistic data over time.
GANs are used in applications such as image generation, style transfer, and data augmentation, where the ability to generate new, high-quality data is important.