AWS Certified Machine Learning – Specialty — Question 110

A data scientist has developed a machine learning translation model for English to Japanese by using Amazon SageMaker's built-in seq2seq algorithm with
500,000 aligned sentence pairs. While testing with sample sentences, the data scientist finds that the translation quality is reasonable for an example as short as five words. However, the quality becomes unacceptable if the sentence is 100 words long.
Which action will resolve the problem?

Answer options

• A. Change preprocessing to use n-grams.
• B. Add more nodes to the recurrent neural network (RNN) than the largest sentence's word count.
• C. Adjust hyperparameters related to the attention mechanism.
• D. Choose a different weight initialization type.

Correct answer: C

Explanation

The correct answer is C because adjusting the hyperparameters of the attention mechanism can help the model focus better on relevant parts of longer sentences, improving translation quality. The other options do not directly address the attention mechanism's role in handling longer sequences, making them less effective for this specific problem.