gated recurrent unit (gru)

A gated recurrent unit (GRU) is a type of recurrent neural network (RNN) architecture that is used in machine learning and natural language processing tasks. It is designed to efficiently capture and store relevant information over time by using a gating mechanism. This gating mechanism allows the GRU to decide how much of the previous information should be forgotten and how much of the new information should be retained, enabling it to effectively model long-term dependencies in sequential data.

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