Definition
A type of machine learning model designed to learn the underlying distribution of the training data, enabling it to synthesize new data points that resemble the original samples.
In short: A type of machine learning model designed to learn the underlying distribution of the training data, enabling it to synthesize new data points that resemble the original samples.