<ul><li>Encoder-decoder architecture is designed to handle sequence-to-sequence problems and is commonly used in machine translation.</li><li>Handling variable-length sequences in both input and output is a key challenge in this domain.</li><li>The encoder encodes the input sequence into a fixed-length context vector, while the decoder generates the output sequence based on the context vector.</li><li>Training involves techniques like teacher forcing to ensure faster convergence and better predictions.</li></ul>

Understanding Sequence-to-Sequence Models and Encoder-Decoder Architecture

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