Restricted Boltzmann machines (RBMs) are a type of artificial neural network that can be used for unsupervised learning. Specifically, RBMs can be used for dimensionality reduction, feature learning, and collaborative filtering. RBMs are often used in deep learning as building blocks for deep belief networks (DBNs) and deep Boltzmann machines (DBMs). Therefore, RBMs are indeed an example of deep learning.
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