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

Dimensionality Reduction is the process of reducing the number of variables or features in a dataset while retaining its essential information. By eliminating irrelevant…
Backpropagation is a technique used in training Artificial Neural Networks. It involves propagating error information backward through the network, allowing adjustments to be made…
Regression Analysis is a statistical technique used to determine the relationship between independent variables and a dependent variable. By analysing historical data, businesses can…
Decision Trees are Machine Learning models that use a branching structure to make decisions or predictions. By determining the most important features and creating…