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Question: 1 A Machine Learning Specialist is designing a system for improving sales for a company. The objective is to use the large amount of information the company has on users’ behavior and product preferences to predict which products users would like based on the users’ similarity to other users. What should the Specialist do to meet this objective? A. Build a content-based filtering recommendation engine with Apache Spark ML on Amazon EMR B. Build a collaborative filtering recommendation engine with Apache Spark ML on Amazon EMR. C. Build a model-based filtering recommendation engine with Apache Spark ML on Amazon EMR D. Build a combinative filtering recommendation engine with Apache Spark ML on Amazon EMR Answer: B https://www.dumpsforsure.com/amazon/mls-c01-dumps.html
Question: 2 A Machine Learning Specialist is using an Amazon SageMaker notebook instance in a private subnet of a corporate VPC. The ML Specialist has important data stored on the Amazon SageMaker notebook instance's Amazon EBS volume, and needs to take a snapshot of that EBS volume. However, the ML Specialist cannot find the Amazon SageMaker notebook instance’s EBS volume or Amazon EC2 instance within the VPC. Why is the ML Specialist not seeing the instance visible in the VPC? A. Amazon SageMaker notebook instances are based on the EC2 instances within the customer account, but they run outside of VPCs. B. Amazon SageMaker notebook instances are based on the Amazon ECS service within customer accounts. C. Amazon SageMaker notebook instances are based on EC2 instances running within AWS service accounts. D. Amazon SageMaker notebook instances are based on AWS ECS instances running within AWS service accounts. Answer: C https://www.dumpsforsure.com/amazon/mls-c01-dumps.html
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