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

One-Shot learning is an AI approach that enables models to learn from only one or a few examples. This approach is advantageous in tasks…
Expert Systems are AI systems that emulate human expertise in specific domains. By capturing and codifying human knowledge, Expert Systems assist businesses in decision-making,…
Cybersecurity in Artificial Intelligence addresses the protection of AI systems from security threats and vulnerabilities. It involves implementing strategies and technologies to safeguard AI…
Incremental Learning is an AI technique that allows models to continuously learn from new data without retraining from scratch. Instead of training the model…