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NEW QUESTION 35
A machine learning (ML) specialist wants to secure calls to the Amazon SageMaker Service API. The specialist has configured Amazon VPC with a VPC interface endpoint for the Amazon SageMaker Service API and is attempting to secure traffic from specific sets of instances and IAM users. The VPC is configured with a single public subnet.
Which combination of steps should the ML specialist take to secure the traffic? (Choose two.)

A. Add a SageMaker Runtime VPC endpoint interface to the VPC.B. Modify the ACL on the endpoint network interface to restrict access to the instances.C. Modify the users' IAM policy to allow access to Amazon SageMaker Service API calls only.D. Add a VPC endpoint policy to allow access to the IAM users.E. Modify the security group on the endpoint network interface to restrict access to the instances.

Answer: D,E

Explanation:
Explanation/Reference: https://aws.amazon.com/blogs/machine-learning/private-package-installation-in-amazon- sagemaker-running-in-internet-free-mode/

 

NEW QUESTION 36
A company's Machine Learning Specialist needs to improve the training speed of a time-series forecasting model using TensorFlow. The training is currently implemented on a single-GPU machine and takes approximately 23 hours to complete. The training needs to be run daily.
The model accuracy is acceptable, but the company anticipates a continuous increase in the size of the training data and a need to update the model on an hourly, rather than a daily, basis. The company also wants to minimize coding effort and infrastructure changes.
What should the Machine Learning Specialist do to the training solution to allow it to scale for future demand?

A. Do not change the TensorFlow code. Change the machine to one with a more powerful GPU to speed up the training.B. Change the TensorFlow code to implement a Horovod distributed framework supported by Amazon SageMaker. Parallelize the training to as many machines as needed to achieve the business goals.C. Switch to using a built-in AWS SageMaker DeepAR model. Parallelize the training to as many machines as needed to achieve the business goals.D. Move the training to Amazon EMR and distribute the workload to as many machines as needed to achieve the business goals.

Answer: B

 

NEW QUESTION 37
A Machine Learning Specialist needs to be able to ingest streaming data and store it in Apache Parquet files for exploration and analysis. Which of the following services would both ingest and store this data in the correct format?

A. AWSDMSB. Amazon Kinesis Data StreamsC. Amazon Kinesis Data FirehoseD. Amazon Kinesis Data Analytics

Answer: C

 

NEW QUESTION 38
A company is observing low accuracy while training on the default built-in image classification algorithm in Amazon SageMaker. The Data Science team wants to use an Inception neural network architecture instead of a ResNet architecture.
Which of the following will accomplish this? (Select TWO.)

A. Create a support case with the SageMaker team to change the default image classification algorithm to Inception.B. Customize the built-in image classification algorithm to use Inception and use this for model training.C. Bundle a Docker container with TensorFlow Estimator loaded with an Inception network and use this for model training.D. Use custom code in Amazon SageMaker with TensorFlow Estimator to load the model with an Inception network and use this for model training.E. Download and apt-get install the inception network code into an Amazon EC2 instance and use this instance as a Jupyter notebook in Amazon SageMaker.

Answer: D,E

 

NEW QUESTION 39
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