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Amazon Exam MLS-C01 Topic 1 Question 72 Discussion

Actual exam question for Amazon's MLS-C01 exam
Question #: 72
Topic #: 1
[All MLS-C01 Questions]

A university wants to develop a targeted recruitment strategy to increase new student enrollment. A data scientist gathers information about the academic performance history of students. The data scientist wants to use the data to build student profiles. The university will use the profiles to direct resources to recruit students who are likely to enroll in the university.

Which combination of steps should the data scientist take to predict whether a particular student applicant is likely to enroll in the university? (Select TWO)

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Hollis
5 hours ago
I'm not so sure about that. Shouldn't we be using something like k-means clustering to group the students first before running any predictions? That could give us better insights into the key characteristics of the 'enrolled' and 'not enrolled' groups.
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Mel
6 days ago
I think options C and D are the way to go. Using a regression algorithm to predict enrollment probability and a classification algorithm to directly classify students as 'enrolled' or 'not enrolled' seems like the most logical approach.
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Merilyn
9 days ago
I'm not sure. Maybe we should also consider using Amazon SageMaker Ground Truth to sort the data first.
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Tandra
14 days ago
I agree with Eden. Using a classification algorithm would be the best approach.
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Eden
15 days ago
I think we should use a classification algorithm to predict enrollment.
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