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Question & Answer
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They maintain hidden states that capture previous information.
They can process all input data simultaneously.
They only work with numerical data.
They are less complex than feedforward neural networks.
Understanding the Answer
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RNNs keep a hidden state that carries information from earlier steps. Other options are incorrect because Some think RNNs can read all input at once, but they actually read one element after another; RNNs do not only handle numeric data.
Key Concepts
Recurrent Neural Networks (RNN)
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Deep Dive: Recurrent Neural Networks (RNN)
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Definition
Recurrent neural networks, including LSTM and gated recurrent networks, have been widely used for sequence modeling and transduction tasks. These networks factor computation along symbol positions and generate hidden states sequentially, limiting parallelization and efficiency.
Topic Definition
Recurrent neural networks, including LSTM and gated recurrent networks, have been widely used for sequence modeling and transduction tasks. These networks factor computation along symbol positions and generate hidden states sequentially, limiting parallelization and efficiency.
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