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

Regression Analysis is a statistical technique used to determine the relationship between independent variables and a dependent variable. By analysing historical data, businesses can…
Deep Reinforcement Learning is a subset of Machine Learning that combines Deep Learning and Reinforcement Learning. It involves training AI models to make decisions…
Zero-Shot Learning is an AI approach that enables models to learn to recognise new classes or concepts without explicit training examples. This is achieved…
Data Science encompasses the collection, analysis, interpretation, and visualisation of data to extract valuable insights and make informed decisions. It combines statistical techniques, Machine…