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

Pattern Recognition is an AI technique that recognises patterns and structures in data. This approach involves identifying common features or characteristics and using these…
Adversarial machine learning involves studying and defending AI models against attacks or adversarial examples designed to deceive the system. By understanding vulnerabilities and deploying…
Knowledge Graphs are a structured representation of knowledge that captures relationships between entities. They organise information in a way that allows machines to understand…
Transfer Learning is a technique that allows AI models to apply knowledge gained from one task to another related task. By leveraging pre-trained models…