Intermediate · Generative AI
Generative model
Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.
TL;DR. A type of machine learning model that can create new data instances similar to the data it was trained on, or estimate the likelihood of a given data point originating from the training distribution.
Technical Definition
A type of machine learning model that can create new data instances similar to the data it was trained on, or estimate the likelihood of a given data point originating from the training distribution.
How it works
Generative models learn the underlying probability distribution of a dataset, enabling them to generate new, synthetic data samples that resemble the original data. They can also be used to determine how likely a new data point is to belong to the distribution learned from the training set. This capability makes them useful for tasks like data augmentation, anomaly detection, and content creation.
Related Concepts
- Deep Learning — A subset of machine learning using neural networks with many layers to learn hierarchical representations from large datasets.
- Generative Adversarial Network (GAN) — Two neural networks — a generator and discriminator — compete against each other to produce increasingly realistic synthetic data.
- Data Augmentation — Techniques that artificially expand training datasets by applying transformations to existing samples.