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NEW QUESTION 32
A Machine Learning team uses Amazon SageMaker to train an Apache MXNet handwritten digit classifier model using a research dataset. The team wants to receive a notification when the model is overfitting. Auditors want to view the Amazon SageMaker log activity report to ensure there are no unauthorized API calls.
What should the Machine Learning team do to address the requirements with the least amount of code and fewest steps?
- A. Use AWS CloudTrail to log Amazon SageMaker API calls to Amazon S3. Add code to push a custom metric to Amazon CloudWatch. Create an alarm in CloudWatch with Amazon SNS to receive a notification when the model is overfitting.
- B. Use AWS CloudTrail to log Amazon SageMaker API calls to Amazon S3. Set up Amazon SNS to receive a notification when the model is overfitting
- C. Implement an AWS Lambda function to log Amazon SageMaker API calls to AWS CloudTrail.
Add code to push a custom metric to Amazon CloudWatch. Create an alarm in CloudWatch with Amazon SNS to receive a notification when the model is overfitting. - D. Implement an AWS Lambda function to log Amazon SageMaker API calls to Amazon S3. Add code to push a custom metric to Amazon CloudWatch. Create an alarm in CloudWatch with Amazon SNS to receive a notification when the model is overfitting.
Answer: A
Explanation:
Log Amazon SageMaker API Calls with AWS CloudTrail
https://docs.aws.amazon.com/sagemaker/latest/dg/logging-using-cloudtrail.html
NEW QUESTION 33
An employee found a video clip with audio on a company's social media feed. The language used in the video is Spanish. English is the employee's first language, and they do not understand Spanish. The employee wants to do a sentiment analysis.
What combination of services is the MOST efficient to accomplish the task?
- A. Amazon Transcribe, Amazon Translate, and Amazon SageMaker Neural Topic Model (NTM)
- B. Amazon Transcribe, Amazon Translate and Amazon SageMaker BlazingText
- C. Amazon Transcribe, Amazon Translate, and Amazon Comprehend
- D. Amazon Transcribe, Amazon Comprehend, and Amazon SageMaker seq2seq
Answer: C
Explanation:
https://aws.amazon.com/getting-started/hands-on/analyze-sentiment-comprehend/
NEW QUESTION 34
A Machine Learning Specialist is training a model to identify the make and model of vehicles in images The Specialist wants to use transfer learning and an existing model trained on images of general objects The Specialist collated a large custom dataset of pictures containing different vehicle makes and models
- A. Initialize the model with random weights in all layers and replace the last fully connected layer
- B. Initialize the model with pre-trained weights in all layers and replace the last fully connected layer.
- C. Initialize the model with pre-trained weights in all layers including the last fully connected layer
- D. Initialize the model with random weights in all layers including the last fully connected layer
Answer: B
NEW QUESTION 35
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