Which of the following statements about the Wide & Deep Learning model are true? (Select 2 answers.)

Which of the following statements about the Wide & Deep Learning model are true? (Select 2 answers.)
A . The wide model is used for memorization, while the deep model is used for generalization.
B . A good use for the wide and deep model is a recommender system.
C . The wide model is used for generalization, while the deep model is used for memorization.
D . A good use for the wide and deep model is a small-scale linear regression problem.

Answer: A,B

Explanation:

Can we teach computers to learn like humans do, by combining the power of memorization and generalization? It’s not an easy question to answer, but by jointly training a wide linear model (for memorization) alongside a deep neural network (for generalization), one can combine the strengths of both to bring us one step closer. At Google, we call it Wide & Deep Learning. It’s useful for generic large-scale regression and classification problems with sparse inputs (categorical features with a large number of possible feature values), such as recommender systems, search, and ranking problems.

Reference: https://research.googleblog.com/2016/06/wide-deep-learning-better-together-with.html