The hyperbolic tangent is a mathematical function that is commonly used as an activation function in artificial neural networks. It maps real-valued inputs into the range of -1 to 1, making it particularly useful for normalizing data and managing outputs within a neural network. Its shape resembles that of the sigmoid function but is zero-centered, which helps with optimization and convergence during the training process.
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