MLS-C01 · Question #134
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 wi
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Question
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?
Options
- AChange preprocessing to use n-grams.
- BAdd more nodes to the recurrent neural network (RNN) than the largest sentence's word count.
- CAdjust hyperparameters related to the attention mechanism.
- DChoose a different weight initialization type.
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