Topic 2 Question 21
2 つ選択Which of the following statements about the Wide & Deep Learning model are true?
The wide model is used for memorization, while the deep model is used for generalization.
A good use for the wide and deep model is a recommender system.
The wide model is used for generalization, while the deep model is used for memorization.
A good use for the wide and deep model is a small-scale linear regression problem.
解説
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
コメント(3)
Answer: A, B Description: Wide model is used for memorization and deep model is used for generalization to make model think like human, both needs to be used to create a recommender system like search.
👍 9[Removed]2020/03/28Answer : AB
👍 5[Removed]2020/03/21- 👍 1daghayeghi2021/03/13
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