What is the difference between embedding space and feature space?

Feature space contains original variables, while embedding space contains learned compressed representations.

Feature space refers to the original observed variables in a dataset. Embedding space is a transformed representation produced by dimensionality reduction or representation learning methods. Embeddings aim to preserve structure such as similarity, distance, or topology in fewer dimensions while discarding redundant information.