One of the quiz questions was about whether or not word embeddings are learned by predicting surrounding words given a word. My understanding was that we could think of NLP tasks as follows:
Learn the word embeddings from a word corpus. This steps learns a feature space into which each word is then embedded, instead of being considered independent.
Use the word embeddings to predict things like which words come next in a sentence.
If this is the right intuition, I think the quiz question is misleading or incorrect. If not, and someone could explain why, I’d appreciate it! Thanks.