Sequence to sequence learning

Many, many NLP problems can be formulated as sequence to sequence tasks. This is a type of task where an input sequence is transformed into another, different output sequence, not necessarily with the same length as the input. To better understand this concept, let's look at some examples:

  • Machine translation is the most popular type of seq2seq task. The input sequences are the words of a sentence in one language and the output sequences are the words of the same sentence, translated into another language. For example, we can translate the English sequence "Tourist attraction" to the German "Touristenattraktion." Not only is the output sentence a different length there is no direct correspondence between the ...

Get Python Deep Learning - Second Edition now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.