Sequence-to-Sequence (Seq2Seq) Models:

  • Seq2Seq models, often built using LSTM or GRU (Gated Recurrent Unit) layers, are used for tasks like machine translation, text summarization, and time series prediction.
  • Example: Implementing a Seq2Seq model in Keras to predict the next sequence in a conversation based on previous dialogue history, where understanding context over long conversations is crucial.

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