Explaining Seq2Seq Encoding-Decoding Processes
The Sequence-to-Sequence (Seq2Seq) model is a deep learning architecture widely used in tasks like machine translation, text summarization, and chatbot responses. Fundamentally, the model consists of two core components: Encoder: Processes the input sequence into a fixed-size context representation (also called a thought vector or context vector). Decoder: Uses the encoded representation to generate an […]