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Exam AWS Certified Machine Learning - Specialty All Questions

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Exam AWS Certified Machine Learning - Specialty topic 1 question 249 discussion

A manufacturing company has a production line with sensors that collect hundreds of quality metrics. The company has stored sensor data and manual inspection results in a data lake for several months. To automate quality control, the machine learning team must build an automated mechanism that determines whether the produced goods are good quality, replacement market quality, or scrap quality based on the manual inspection results.

Which modeling approach will deliver the MOST accurate prediction of product quality?

  • A. Amazon SageMaker DeepAR forecasting algorithm
  • B. Amazon SageMaker XGBoost algorithm
  • C. Amazon SageMaker Latent Dirichlet Allocation (LDA) algorithm
  • D. A convolutional neural network (CNN) and ResNet
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Suggested Answer: B 🗳️

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Chosen Answer:
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endeesa
5 months ago
Selected Answer: B
We have a supervised classification problem + numerical features, clearly XGBoost is the best candidate
upvoted 2 times
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loict
7 months, 2 weeks ago
Selected Answer: B
A. NO - it is not a foreacasting problem B. YES - it is a supervised classification problem C. NO - LDA is for topic modeling, sentiment analysis D. NO - ResNet (a type of CNN) is for image recognition
upvoted 4 times
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Mickey321
8 months, 1 week ago
Selected Answer: B
A bit confusing. Depends on sensor data. if it is images then D for sure but if it is tabular data then B
upvoted 1 times
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kaike_reis
8 months, 1 week ago
Selected Answer: B
We have a tabular multiclass classification problem. Letter B is the correct solution for this.
upvoted 2 times
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ADVIT
9 months, 3 weeks ago
Selected Answer: B
Definitely B.
upvoted 1 times
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kukreti18
10 months, 1 week ago
It's B
upvoted 1 times
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