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NEW QUESTION 52
A manufacturing company has structured and unstructured data stored in an Amazon S3 bucket. A Machine Learning Specialist wants to use SQL to run queries on this data.
Which solution requires the LEAST effort to be able to query this data?
- A. Use AWS Lambda to transform the data and Amazon Kinesis Data Analytics to run queries.
- B. Use AWS Data Pipeline to transform the data and Amazon RDS to run queries.
- C. Use AWS Glue to catalogue the data and Amazon Athena to run queries.
- D. Use AWS Batch to run ETL on the data and Amazon Aurora to run the queries.
Answer: D
NEW QUESTION 53
An interactive online dictionary wants to add a widget that displays words used in similar contexts. A Machine Learning Specialist is asked to provide word features for the downstream nearest neighbor model powering the widget.
What should the Specialist do to meet these requirements?
- A. Create one-hot word encoding vectors.
- B. Download word embeddings pre-trained on a large corpus.
- C. Create word embedding vectors that store edit distance with every other word.
- D. Produce a set of synonyms for every word using Amazon Mechanical Turk.
Answer: B
Explanation:
As it is a interactive online dictionary, we need pre-trained word embedding thus the answer is D.
In addition, there is no mention that the online dictonary is unique and does not have a pre- trained word embedding.
NEW QUESTION 54
A Machine Learning Specialist is configuring Amazon SageMaker so multiple Data Scientists can access notebooks, train models, and deploy endpoints. To ensure the best operational performance, the Specialist needs to be able to track how often the Scientists are deploying models, GPU and CPU utilization on the deployed SageMaker endpoints, and all errors that are generated when an endpoint is invoked.
Which services are integrated with Amazon SageMaker to track this information? (Select TWO.)
- A. AWS Config
- B. Amazon CloudWatch
- C. AWS Health
- D. AWS CloudTrail
- E. AWS Trusted Advisor
Answer: B,D
NEW QUESTION 55
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