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AI Engineering

Page 1 of 671

Chapter 2.4

Seq2Seq Architecture

The encoder-decoder architecture is conditioned on both the final hidden state of the input and the previously generated token. A visualization of the seq2seq architecture  is shown in Figure 2.4.

There are two problems with seq2seq that Vaswani et al. (2017) addresses. First, the vanilla seq2seq decoder generates output tokens using only the final hidden state of the input.

The transformer attention mechanism addresses this by allowing the decoder to attend to all input tokens when generating each output token.

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5:23 / 12:40

Linear Algebra for Machine Learning

freeCodeCamp.org 10:48:43 0:00 / 10:48:43 (12%) 2/26/2025
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this in-depth course provides a

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comprehensive exploration of all

0:14

critical linear algebra concepts

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necessary for machine learning you'll

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Talimio was build form the ground up with education in mind, meaning you don't have to juggle couple of conversations in paralle, and you have futures on top of that; like progress tracking interactivity and quizzes and exerices!
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Yes! Talimio is open source and available for self-hosting. We provide Docker images and comprehensive setup instructions on our GitHub RREADME.

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