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Exam AWS Certified Machine Learning - Specialty topic 1 question 285 discussion

Exam question from Amazon's AWS Certified Machine Learning - Specialty
Question #: 285
Topic #: 1
[All AWS Certified Machine Learning - Specialty Questions]

A company hosts a public web application on AWS. The application provides a user feedback feature that consists of free-text fields where users can submit text to provide feedback. The company receives a large amount of free-text user feedback from the online web application. The product managers at the company classify the feedback into a set of fixed categories including user interface issues, performance issues, new feature request, and chat issues for further actions by the company's engineering teams.

A machine learning (ML) engineer at the company must automate the classification of new user feedback into these fixed categories by using Amazon SageMaker. A large set of accurate data is available from the historical user feedback that the product managers previously classified.

Which solution should the ML engineer apply to perform multi-class text classification of the user feedback?

  • A. Use the SageMaker Latent Dirichlet Allocation (LDA) algorithm.
  • B. Use the SageMaker BlazingText algorithm.
  • C. Use the SageMaker Neural Topic Model (NTM) algorithm.
  • D. Use the SageMaker CatBoost algorithm.
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Suggested Answer: B 🗳️
by aquanaveen at Dec. 17, 2023, 1:01 p.m.
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taustin2
10 months, 1 week ago
Selected Answer: B
B. Blazing Text for text classification.
upvoted 2 times
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taustin2
10 months, 2 weeks ago
Selected Answer: B
BlazingText's implements a supervised multi-class, multi-label text classification algorithm.
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aquanaveen
10 months, 2 weeks ago
Selected Answer: B
B. Use the SageMaker BlazingText algorithm. Explanation: BlazingText for Text Classification: SageMaker BlazingText is designed for efficient and scalable text classification tasks. It supports multi-class classification, making it suitable for the scenario where user feedback needs to be classified into fixed categories. BlazingText uses a fast implementation of the Word2Vec algorithm, making it highly performant.
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