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Amazon AWS Certified Machine Learning - Specialty Exam Questions
AWS Certified Machine Learning - Specialty (MLS-C01) (Page 11 )

Updated On: 5-Mar-2026
Page 11 of 57
PDF with 370 Questions

An online reseller has a large, multi-column dataset with one column missing 30% of its data. A Machine Learning Specialist believes that certain columns in the dataset could be used to reconstruct the missing data.

Which reconstruction approach should the Specialist use to preserve the integrity of the dataset?

  1. Listwise deletion
  2. Last observation carried forward
  3. Multiple imputation
  4. Mean substitution

Answer(s): C


Reference:

https://worldwidescience.org/topicpages/i/imputing+missing+values.html



A company is setting up an Amazon SageMaker environment. The corporate data security policy does not allow communication over the internet.

How can the company enable the Amazon SageMaker service without enabling direct internet access to Amazon SageMaker notebook instances?

  1. Create a NAT gateway within the corporate VPC.
  2. Route Amazon SageMaker traffic through an on-premises network.
  3. Create Amazon SageMaker VPC interface endpoints within the corporate VP
  4. Create VPC peering with Amazon VPC hosting Amazon SageMaker.

Answer(s): C


Reference:

https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-dg.pdf (516)
https://docs.aws.amazon.com/zh_tw/vpc/latest/userguide/vpc-endpoints.html



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.

What should the Specialist do to initialize the model to re-train it with the custom data?

  1. Initialize the model with random weights in all layers including the last fully connected layer.
  2. Initialize the model with pre-trained weights in all layers and replace the last fully connected layer.
  3. Initialize the model with random weights in all layers and replace the last fully connected layer.
  4. Initialize the model with pre-trained weights in all layers including the last fully connected layer.

Answer(s): B



An office security agency conducted a successful pilot using 100 cameras installed at key locations within the main office. Images from the cameras were uploaded to Amazon S3 and tagged using Amazon Rekognition, and the results were stored in Amazon ES. The agency is now looking to expand the pilot into a full production system using thousands of video cameras in its office locations globally. The goal is to identify activities performed by non-employees in real time

Which solution should the agency consider?

  1. Use a proxy server at each local office and for each camera, and stream the RTSP feed to a unique Amazon Kinesis Video Streams video stream. On each stream, use Amazon Rekognition Video and create a stream processor to detect faces from a collection of known employees, and alert when non-employees are detected.
  2. Use a proxy server at each local office and for each camera, and stream the RTSP feed to a unique Amazon Kinesis Video Streams video stream. On each stream, use Amazon Rekognition Image to detect faces from a collection of known employees and alert when non-employees are detected.
  3. Install AWS DeepLens cameras and use the DeepLens_Kinesis_Video module to stream video to Amazon Kinesis Video Streams for each camera. On each stream, use Amazon Rekognition Video and create a stream processor to detect faces from a collection on each stream, and alert when non-employees are detected.
  4. Install AWS DeepLens cameras and use the DeepLens_Kinesis_Video module to stream video to Amazon Kinesis Video Streams for each camera. On each stream, run an AWS Lambda function to capture image fragments and then call Amazon Rekognition Image to detect faces from a collection of known employees, and alert when non-employees are detected.

Answer(s): A


Reference:

As mentioned in below user comment, DeepLens is not offered as a commercial product.
https://aws.amazon.com/deeplens/device-terms-of-use/



A Marketing Manager at a pet insurance company plans to launch a targeted marketing campaign on social media to acquire new customers. Currently, the company has the following data in Amazon Aurora:

•Profiles for all past and existing customers
•Profiles for all past and existing insured pets
•Policy-level information
•Premiums received
•Claims paid

What steps should be taken to implement a machine learning model to identify potential new customers on social media?

  1. Use regression on customer profile data to understand key characteristics of consumer segments. Find similar profiles on social media
  2. Use clustering on customer profile data to understand key characteristics of consumer segments. Find similar profiles on social media
  3. Use a recommendation engine on customer profile data to understand key characteristics of consumer segments. Find similar profiles on social media.
  4. Use a decision tree classifier engine on customer profile data to understand key characteristics of consumer segments. Find similar profiles on social media.

Answer(s): C



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