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Directly Learning Rich Outputs
End-to-end deep learning can directly learn outputs that are more complex than a number. With the right labeled input-output pairs, end-to-end learning can sometimes learn outputs such as a sentence, an image, audio, or other outputs richer than a single number.
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Machine Learning
Deep Learning
Supervised Learning
Dive into Deep Learning @ D2L
Data Science
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Directly Learning Rich Outputs
What structure does end-to-end learning typically replace in a machine learning system?
Neural networks are commonly used in end-to-end learning systems.
The term 'end-to-end' refers to the learning algorithm going directly from the _____ to the desired output.
Match each output type to its description as an example of what end-to-end deep learning can produce.
Order the steps of an end-to-end sentiment classification system as described in Machine Learning Yearning.
Given the right labeled input-output pairs, what can end-to-end deep learning sometimes produce as output?
End-to-end deep learning is limited to producing outputs that are a single number.
End-to-end deep learning is an accelerating trend that allows directly learning _____ that are much more complex than a number.
Match each end-to-end learning concept to its definition from Machine Learning Yearning.
Order the reasoning steps that explain how end-to-end deep learning enables rich outputs beyond a single number.
Learn After
End-to-End Image Captioning
End-to-End Text-to-Speech
End-to-End Question Answering
End-to-End Machine Translation as Rich Output Learning
End-to-End Speech Recognition as Rich Output Learning
Which of the following best describes the outputs that end-to-end deep learning can directly learn?
End-to-end deep learning is limited to predicting outputs that are single numbers.
To train an end-to-end system that produces rich outputs, you need the right labeled _____ pairs.
Match each output category to an example of a rich output in end-to-end deep learning.
Order the reasoning steps a practitioner follows when deciding whether end-to-end learning can produce a rich output.
Which condition does ML Yearning identify as the key prerequisite for end-to-end learning to produce rich outputs?
A sentence is an example of a rich output that end-to-end deep learning can learn to produce directly.
ML Yearning describes the ability to learn rich outputs end-to-end as 'an accelerating _____ in deep learning.'
Match each end-to-end deep learning application to the type of rich output it produces.
Order the steps for building an end-to-end deep learning system that produces a rich output such as a translated sentence.