deep belief networks
Deep belief networks are a type of artificial neural networks that are capable of representing and learning complex patterns and relationships in data. They consist of multiple layers of interconnected nodes that can extract relevant features from the input and generate higher-level representations. These networks are trained in an unsupervised manner, allowing them to capture the underlying structure of the data and make accurate predictions or classifications.
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