Generative Models

Generative models are a class of machine learning models that are designed to generate new data instances that resemble a given training dataset. Unlike discriminative models, which focus on differentiating between classes, generative models learn the underlying distribution of the data. Key characteristics include their ability to create diverse outputs, such as images, text, or audio, based on learned patterns. Common use cases include generating realistic images, creating synthetic data for training purposes, and enhancing creative processes in art and music. They are pivotal in fields like computer vision, natural language processing, and generative AI.