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What kind of outputs can end-to-end deep learning learn?
Question: When enough correctly labeled training data is available, what broader kind of target output can end-to-end deep learning learn?
Sample answer: It can learn rich, structured outputs rather than only a single numeric prediction, such as full sentences, images, or audio clips.
Key points:
- The target does not have to be just one number.
- End-to-end models can learn structured or high-dimensional outputs.
- Examples include sentences, images, and audio.
Rubric: The answer must mention that end-to-end deep learning can learn complex or rich outputs beyond a single scalar value.
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What kind of outputs can end-to-end deep learning learn?