What is Generative Adversarial Networks (GANs)?

Skill Level:

Generative Adversarial Networks are a type of Machine Learning model that consists of two neural networks: a generator and a discriminator. GANs are used to generate synthetic data that resembles real data by learning from training examples. They find applications in image generation, video synthesis, and data augmentation.

Other Definitions

Artificial Neural Networks are computational models inspired by the human brain’s structure and function. They consist of interconnected nodes that process and transmit data,…
Neuroevolution is a type of AI learning that combines neural networks and evolutionary algorithms. Neuroevolution algorithms evolve neural networks over generations, adapting them to…
Quantum Computing and AI are two fields that can complement and enhance each other. Quantum Computing can perform calculations faster and more efficiently than…
Ontologies are a representation of knowledge that defines concepts and the relationships among them. Ontologies enable machines to structure and reason information in a…