Generative Adversarial Network
A framework where two networks (generator and discriminator) compete, with the generator learning to create realistic data.
Related Concepts
- Generator: Explore how Generator relates to Generative Adversarial Network
- Discriminator: Explore how Discriminator relates to Generative Adversarial Network
- Adversarial Training: Explore how Adversarial Training relates to Generative Adversarial Network
- Generative Model: Explore how Generative Model relates to Generative Adversarial Network
Why It Matters
Understanding Generative Adversarial Network is crucial for anyone working with neural networks & deep learning. This concept helps build a foundation for more advanced topics in AI and machine learning.
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This term is part of the comprehensive AI/ML glossary. Explore related terms to deepen your understanding of this interconnected field.
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Related Terms
Adversarial Training
Training on adversarial examples to improve model robustness against attacks.
Discriminator
In GANs, the network that tries to distinguish between real and generated data, providing training signal to the generator.
Generator
In GANs, the network that creates synthetic data attempting to fool the discriminator into thinking it's real.