Generative Adversarial Networks Tutorial - How do GANs work?
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Generative Adversarial Networks (GANs) refers to a new architecture for neural networks in unsupervised machine learning. It contains two independent models working separately and acting as adversaries. In this Generative Adversarial Networks Tutorial, we explain the concept and framework of GANs and use an interesting analogy to illustrate the training processes of models.
Watch this video to learn:
- What are Generative Adversarial Networks
- How GANs work
- GANs applications and use cases
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Generative Adversarial Networks
GANs
Generative Adversarial Networks Tutorial
unsupervised machine learning