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Answer Posted / Satendra Singh
A Boltzmann Machine (BM) is a type of stochastic artificial neural network that can learn the probability distribution of its input data. It was proposed by Geoffrey Hinton and Simon Becker in 1986 as an extension of the Hopfield network. BMs are binary-state, undirected, fully connected networks with hidden units. Each unit has a bias term, and connections between units have associated weights. During training, the network learns to reproduce the input probability distribution by adjusting the weights and biases.
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