Exam AWS Certified Machine Learning - Specialty All Questions

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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

Suggested Answer: B 🗳️

by VinceCar at Nov. 27, 2022, 8:45 a.m.

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hichemck

Highly Voted 1 year, 7 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, 6 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 9 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

10 months, 1 week ago

Selected Answer: B

XGboost

upvoted 2 times

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kaike_reis

10 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

11 months, 3 weeks ago

Selected Answer: B

XGboost for Binary classification

upvoted 1 times

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blanco750

1 year, 3 months 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, 7 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, 7 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, 7 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, 7 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, 7 months ago

you're right. there is no time series.

upvoted 4 times

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