Amazon Exam MLS-C01 Topic 3 Question 110 Discussion

Actual exam question for Amazon's MLS-C01 exam

Question #: 110
Topic #: 3

A company stores its documents in Amazon S3 with no predefined product categories. A data scientist needs to build a machine learning model to categorize the documents for all the company's products.

Which solution will meet these requirements with the MOST operational efficiency?

ABuild a custom clustering model. Create a Dockerfile and build a Docker image. Register the Docker image in Amazon Elastic Container Registry (Amazon ECR). Use the custom image in Amazon SageMaker to generate a trained model.

BTokenize the data and transform the data into tabulai data. Train an Amazon SageMaker k-means mode to generate the product categories.

CTrain an Amazon SageMaker Neural Topic Model (NTM) model to generate the product categories.

DTrain an Amazon SageMaker Blazing Text model to generate the product categories.

Show Suggested Answer

Suggested Answer: C

Amazon SageMaker's Neural Topic Model (NTM) is designed to uncover underlying topics within text data by clustering documents based on topic similarity. For document categorization, NTM can identify product categories by analyzing and grouping the documents, making it an efficient choice for unsupervised learning where predefined categories do not exist.

by Dana at Jan 13, 2025, 07:50 AM

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