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

Predictive Analytics uses historical data and statistical modelling techniques to make predictions about future outcomes. By analysing patterns and trends within data, businesses can…
Time Series Analysis is an AI technique that analyses data points collected over time. This approach involves detecting trends, patterns, and seasonality in the…
Fuzzy Logic is a mathematical framework that deals with uncertainty and imprecision. By assigning degrees of truth to statements, Fuzzy Logic allows businesses to…
Multi-Modal learning refers to AI models that learn from multiple sources of data, such as text, images, and audio. By incorporating information from multiple…