In machine learning, a deep belief network (DBN) is a generative graphical model, or alternatively a class of deep neural network, composed of multiple layers of latent variables ("hidden units"), with connections between the layers but not between units within each layer. When trained without supervision on a set of examples, a DBN can learn to probabilistically reconstruct its inputs.
In machine learning, a deep belief network (DBN) is a generative graphical model, or alternatively a class of deep neural network, composed of multiple layers of latent variables ("hidden units"), with connections between the layers but not between units within each layer. When trained without supervision on a set of examples, a DBN can learn to probabilistically reconstruct its inputs.
Source: Wikipedia "Deep belief network" · CC BY-SA 4.0
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