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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

Decision Networks

Decision networks, also known as Probabilistic Graphical Models, are a type of AI model that represents uncertain knowledge using a graph structure. Decision Networks…

Neural Networks

Neural Networks are a type of Machine Learning model inspired by the human brain. They are composed of interconnected nodes, or “neurons,” that process…

Graph Neural Networks

Graph Neural Networks are machine learning models designed to handle data structured as graphs. They can capture relationships and dependencies between entities and perform…

Deep Reinforcement Learning

Deep Reinforcement Learning is a subset of Machine Learning that combines Deep Learning and Reinforcement Learning. It involves training AI models to make decisions…
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