gated recurrent units (gru)

Gated Recurrent Units (GRUs) are a type of recurrent neural network (RNN) architecture that use specialized units to regulate and control information flow within the network. They have gating mechanisms that allow them to selectively remember, forget, and update information at each time step, making them effective in capturing long-term dependencies in sequential data. GRUs are widely used in various tasks, including natural language processing, speech recognition, and time series analysis.

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