AWS Certified Machine Learning - Specialty MLS-C01 — Topic 1 Question 176

Question

A machine learning (ML) specialist needs to extract embedding vectors from a text series. The goal is to provide a ready-to-ingest feature space for a data scientist to develop downstream ML predictive models. The text consists of curated sentences in English. Many sentences use similar words but in different contexts. There are questions and answers among the sentences, and the embedding space must differentiate between them. Which options can produce the required embedding vectors that capture word context and sequential QA information? (Choose two.)

Accepted Answer

Correct answer: A, C. The correct answer is A, C. Option A: Amazon SageMaker seq2seq algorithm Option C: Amazon SageMaker Object2Vec algorithm Amazon SageMaker builds, trains and deploys machine learning models in a fully managed service.

AWS Certified Machine Learning - Specialty MLS-C01 — Question 176