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Amazon MLS-C01 Exam - Topic 7 Question 50 Discussion

Actual exam question for Amazon's MLS-C01 exam
Question #: 50
Topic #: 7
[All MLS-C01 Questions]

A machine learning (ML) specialist needs to extract embedding vectors from a text series. The goal is to provide a ready-to-ingest feature space for a data scientist to develop downstream ML predictive models. The text consists of curated sentences in English. Many sentences use similar words but in different contexts. There are questions and answers among the sentences, and the embedding space must differentiate between them.

Which options can produce the required embedding vectors that capture word context and sequential QA information? (Choose two.)

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Yuriko
4 months ago
E is interesting, combining methods could yield better results!
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Lili
4 months ago
I’m not sure about D, seems too simplistic for this task.
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Brice
4 months ago
Wait, can BlazingText really handle QA info?
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Shawnta
4 months ago
Definitely A and B! They capture context well.
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Earlean
5 months ago
I think C and E are solid choices for this.
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Kris
5 months ago
I've got a good feeling about this one. GENEX Assistant is all about automating routine network tasks, so I'm pretty sure the answer is D - Routine network optimization.
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Audra
5 months ago
Hmm, I'm not totally sure about this one. I'll have to think it through carefully. Maybe I should review my notes on project scheduling processes before deciding.
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Mirta
5 months ago
Hmm, this is a tricky one. I'll need to think carefully about the options here.
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Jill
5 months ago
I remember practicing a similar question about authentication protocols, and I think SAML was used for that one too.
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Ernestine
5 months ago
I think uploading the forms to the Web server and creating local relative links makes the most sense, but I'm not entirely sure if relative links are the right choice here.
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