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Direct Translation Is a Rich-Output Learning Problem
In machine translation, the model takes a sentence in one language as input and produces a full sentence in another language, so it is learning to generate a rich structured output rather than a single label.
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Data Science
Foundations of Large Language Models Course
Computing Sciences
D2L
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Machine Learning
Deep Learning
Supervised Learning
Machine Learning Strategy
Machine Learning Yearning @ DeepLearning.AI
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Direct Translation Is a Rich-Output Learning Problem
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What kinds of outputs can an end-to-end model learn directly?
End-to-end deep learning can only be used when the target is a single numeric value.
To train an end-to-end system that produces detailed outputs, you need the right labeled _____ pairs.
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Match each end-to-end application with the kind of rich output it produces.
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Why End-to-End Models Need Labeled Structured Targets
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What kind of outputs can end-to-end deep learning learn?
Learn After
In a text translation system that converts Spanish emails into English, what is the INPUT to the end-to-end model?
Direct Sentence-Pair Learning in Machine Translation
Rich-output learning in machine translation.
Match each part of a sequence-to-sequence translation task to its best description.
Order the reasoning steps for deciding whether a task is a good candidate for end-to-end learning with rich outputs.
Which statement best describes the trend in deep learning illustrated by a task with rich outputs such as speech-to-text or translation?
In end-to-end learning, rich outputs are limited to a single numeric score.
With the right (input, output) _____ pairs, a model can learn end to end even when the output is rich.
Match each example output to the correct classification as a rich output or a simple output.
Order the stages of a direct text translation system trained from paired examples.
End-to-End Translation as an Example of Rich Outputs
Classifying a Rich-Output Learning Problem
What Counts as a Rich Output?