In Ng's machine translation example of rich-output learning, what serves as the INPUT to the end-to-end system?

End-to-end machine translation trains directly on (English, French) labeled pairs without requiring hand-crafted intermediate representations.

Machine translation is a rich-output learning problem because the output is a _____ rather than a single number.

Match each component of Ng's machine translation example to its correct description.

Order the reasoning steps for deciding whether a new task qualifies for end-to-end rich-output learning.

Which statement best captures the 'accelerating trend in deep learning' Ng describes using machine translation as an example?

According to ML Yearning, 'rich outputs' in end-to-end deep learning are restricted to text sentences only.

Ng states that with the right (input, output) _____ pairs, you can sometimes learn end-to-end even when the output is rich.

Match each output type to its correct classification as a 'rich output' or 'simple output' in Ng's framework.

Order the stages of an end-to-end machine translation system as described in Ng's rich-output learning framework.