Which type of neural network architecture is particularly effective for sequence-to-sequence tasks, such as language translation?
- Autoencoders
- Convolutional Neural Networks (CNNs)
- Generative Adversarial Networks (GANs)
- Recurrent Neural Networks (RNNs)
Recurrent Neural Networks (RNNs) are particularly effective for 'sequence-to-sequence' tasks. They are widely used in tasks like language translation and speech recognition. The ability to maintain context from previous time steps allows RNNs to generate meaningful sequences, making them suitable for these tasks.
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