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What is Generative Adversarial Networks (GANs)?

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Generative Adversarial Networks are a type of Machine Learning model that consists of two neural networks: a generator and a discriminator. GANs are used to generate synthetic data that resembles real data by learning from training examples. They find applications in image generation, video synthesis, and data augmentation.

Other Definitions

Clustering

Clustering in AI refers to the process of grouping similar data points together based on their inherent characteristics or attributes. By identifying patterns or…

Dimensionality Reduction

Dimensionality Reduction is the process of reducing the number of variables or features in a dataset while retaining its essential information. By eliminating irrelevant…

Backpropagation

Backpropagation is a technique used in training Artificial Neural Networks. It involves propagating error information backward through the network, allowing adjustments to be made…
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