What is GRU architecture in neural networks?
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What is GRU architecture in neural networks?
GRU stands for Gated Recurrent Unit. It's a type of recurrent neural network architecture that is designed to handle sequential data.
How does GRU differ from LSTM?
GRU has fewer parameters than LSTM because it combines the forget and input gates into a single update gate, making it simpler.
What are the advantages of using GRU?
GRUs are computationally more efficient and can perform just as well as LSTMs on many tasks, especially with smaller datasets.
Can you give an example of where GRU is used?
GRUs are commonly used in natural language processing tasks, such as language modeling and machine translation.
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