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Exam AWS Certified Machine Learning - Specialty topic 1 question 192 discussion

Exam question from Amazon's AWS Certified Machine Learning - Specialty
Question #: 192
Topic #: 1
[All AWS Certified Machine Learning - Specialty Questions]

A newspaper publisher has a table of customer data that consists of several numerical and categorical features, such as age and education history, as well as subscription status. The company wants to build a targeted marketing model for predicting the subscription status based on the table data.

Which Amazon SageMaker built-in algorithm should be used to model the targeted marketing?

  • A. Random Cut Forest (RCF)
  • B. XGBoost
  • C. Neural Topic Model (NTM)
  • D. DeepAR forecasting
Show Suggested Answer Hide Answer
Suggested Answer: B 🗳️
by VinceCar at Nov. 27, 2022, 8:45 a.m.
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hichemck
Highly Voted 1 year, 5 months ago
Selected Answer: B
B is correct. IMO A - No, Random cut forest is for anomaly detection B - Yes, exactly was XGBoost is good for. Binary classification based on a variety of input features C - No, NTM is unsupervised. The problem states the table already has subscription status, therefore we need a supervised algorithm D - No, DeepAR is used for time-series data
upvoted 7 times
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Peeking
Highly Voted 1 year, 4 months ago
Selected Answer: B
Whether subscription status is binary or multi-class XGBoost can handle the problem in this case problem.
upvoted 6 times
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loict
Most Recent 7 months, 3 weeks ago
Selected Answer: B
A. NO - Random Cut Forest (RCF) used for anomalities B. YES - XGBoost is good for classification C. NO - Neural Topic Model (NTM) is to find topics, not classify D. NO - that is for timeseries
upvoted 4 times
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Mickey321
8 months, 1 week ago
Selected Answer: B
XGboost
upvoted 2 times
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kaike_reis
8 months, 3 weeks ago
Selected Answer: B
Letter B is correct as we have a supervised classification problem here.
upvoted 1 times
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Mickey321
9 months, 2 weeks ago
Selected Answer: B
XGboost for Binary classification
upvoted 1 times
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blanco750
1 year, 1 month ago
Selected Answer: B
XGBoost is a popular and powerful algorithm for binary classification problems such as this one, where the goal is to predict a binary outcome (e.g. whether a customer subscribes or not). It is particularly effective when the dataset has a mix of numerical and categorical features.
upvoted 2 times
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blobfishtu
1 year, 5 months ago
The answer is B: A. Random Cut Forest (RCF): anomaly detection B. XGBoost: allows classification tasks like the use case in the question C. Neural Topic Model (NTM): topic modelling D. DeepAR forecasting: time series
upvoted 3 times
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dunhill
1 year, 5 months ago
I think the answer is B. It looks like no time serials condition, so it may be not suitable to A and D.
upvoted 4 times
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VinceCar
1 year, 5 months ago
Selected Answer: D
D. Refer to https://docs.aws.amazon.com/forecast/latest/dg/aws-forecast-recipe-deeparplus.html
upvoted 1 times
Amit11011996
1 year, 5 months ago
can you please let us know, where in question it states that date/time column is available. It is all about numerical or categorical columns and we need to predict subscription status which can be done by the use XG-BOOST
upvoted 3 times
VinceCar
1 year, 4 months ago
you're right. there is no time series.
upvoted 4 times
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