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Match each end-to-end application with the kind of rich output it produces.
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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.
Match each output type to a concrete example of a rich prediction.
Order the reasoning steps for deciding whether an end-to-end system can predict a rich output.
What most enables end-to-end learning to handle outputs such as sentences, images, or audio?
A language model can be trained to generate a complete sentence directly from labeled examples.
Learning rich outputs directly with one model is described as an accelerating _____ in deep learning.
Match each end-to-end application with the kind of rich output it produces.
Steps for Training an End-to-End System That Produces a Rich Output
Why End-to-End Models Need Labeled Structured Targets
Training a Document-to-Summary Model
What kind of outputs can end-to-end deep learning learn?