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?
(Choose two.)
Use Amazon SageMaker Ground Truth to sort the data into two groups named “enrolled” or “not enrolled.”
Use a forecasting algorithm to run predictions.
Use a regression algorithm to run predictions.
Use a classification algorithm to run predictions.
Use the built-in Amazon SageMaker k-means algorithm to cluster the data into two groups named “enrolled” or “not enrolled.”
I strategize that the answer is:
Use Amazon SageMaker Ground Truth to sort the data into two groups named “enrolled” or “not enrolled.”