AWS Certified Machine Learning – Specialty — Question 252

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?

Answer options

• 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

Correct answer: B

Explanation

The Amazon SageMaker XGBoost algorithm is well-suited for structured data and excels in classification tasks, making it ideal for predicting product quality. The other options either focus on time series forecasting (A), topic modeling (C), or are more complex neural network architectures (D) that may not be necessary for this classification challenge.