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Exam AWS Certified Machine Learning - Specialty topic 1 question 170 discussion

Exam question from Amazon's AWS Certified Machine Learning - Specialty
Question #: 170
Topic #: 1
[All AWS Certified Machine Learning - Specialty Questions]

A retail company is selling products through a global online marketplace. The company wants to use machine learning (ML) to analyze customer feedback and identify specific areas for improvement. A developer has built a tool that collects customer reviews from the online marketplace and stores them in an Amazon S3 bucket. This process yields a dataset of 40 reviews. A data scientist building the ML models must identify additional sources of data to increase the size of the dataset.
Which data sources should the data scientist use to augment the dataset of reviews? (Choose three.)

  • A. Emails exchanged by customers and the company's customer service agents
  • B. Social media posts containing the name of the company or its products
  • C. A publicly available collection of news articles
  • D. A publicly available collection of customer reviews
  • E. Product sales revenue figures for the company
  • F. Instruction manuals for the company's products
Show Suggested Answer Hide Answer
Suggested Answer: ABD 🗳️
by bluer1 at April 28, 2022, 10:30 p.m.
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spaceexplorer
Highly Voted 2 years ago
Selected Answer: ABD
ABD; Email exchange between customer and customer service would be valuable data source.
upvoted 29 times
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kaike_reis
Most Recent 8 months, 3 weeks ago
Selected Answer: ABD
Everyone explained correct.
upvoted 2 times
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Mickey321
9 months, 1 week ago
Selected Answer: ABD
In conclusion, the data scientist should use customer service emails, social media posts, and publicly available customer reviews to augment the dataset of reviews for the analysis of customer feedback and identifying specific areas for improvement.
upvoted 2 times
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AjoseO
1 year, 2 months ago
Selected Answer: ABD
A: Emails exchanged by customers and the company's customer service agents can provide additional customer feedback and opinions about the products or services. This data can be used to improve the ML model. B: Social media posts containing the name of the company or its products can provide additional customer feedback and opinions about the products or services, which can be used to improve the ML model. D: A publicly available collection of customer reviews can be used to augment the existing dataset of reviews and increase the size of the dataset. This can help to improve the accuracy of the ML model.
upvoted 4 times
AjoseO
1 year, 2 months ago
C: A publicly available collection of news articles and F: Instruction manuals for the company's products are not directly related to customer feedback and may not be relevant for improving the ML model in this context. E: Product sales revenue figures for the company can provide valuable insights into the company's financial performance, but this data is not directly related to customer feedback and may not be useful for improving the ML model in this context.
upvoted 2 times
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f4bi4n
1 year, 10 months ago
I think ABE or maybe(!) ABF A & B -> for sure C -> No glue how this should help D -> We have already reviews!? E -> Could help to find correlations between negative / positive reviews and sales F -> non-sense in the first moment and second as well, but maybe it could help to combine the information of Email, Social and Reviews to some problems.
upvoted 3 times
kaike_reis
8 months, 3 weeks ago
Don't overthink conrad.
upvoted 1 times
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Sonoko
1 year, 4 months ago
ABE makes more sense here.
upvoted 2 times
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AdolinKholin
1 year, 7 months ago
That's exactly the point though, we want more volume of reviews, or anything resembling reviews as is the case with email exchanges.
upvoted 1 times
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bluer1
2 years ago
BDF - correct answer
upvoted 1 times
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