Answer-first summary for fast verification
Answer: No
The question asks whether using a Convolutional Neural Network (CNN) is suitable for building a machine translation model that must learn text sequences. CNNs are primarily designed for spatial data like images, where local patterns and hierarchies are important, but they are not optimal for sequential data like text where the order and context across the entire sequence matter. For machine translation, which involves sequence-to-sequence (seq2seq) learning, architectures like Recurrent Neural Networks (RNNs) or, more modernly, Transformers are preferred. The community discussion strongly supports this, with comments noting that CNNs are for images and RNNs/Transformers are for text sequences, and the consensus answer is 'No' (B) with 100% agreement. Thus, the recommendation does not satisfy the requirements.
Author: LeetQuiz Editorial Team
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You are building a machine learning model to translate text from one language to another. The model must be constructed and trained to learn the sequence of the text.
Recommendation: Use a Convolutional Neural Network (CNN).
Does this recommendation satisfy the requirements?
A
Yes
B
No
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