Free Amazon MLS-C01 Exam Questions
Absolute Free MLS-C01 Exam Practice for Comprehensive Preparation
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Amazon MLS-C01 Exam Questions
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Provided By: Amazon
- Exam: AWS Certified Machine Learning - Specialty
- Certification: AWS Certified Machine Learning
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Total Questions: 392
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Updated On: Dec 07, 2025
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Rated: 4.9 |
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Online Users: 784
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Question 1
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A company is running an Amazon SageMaker training job that will access data stored in its Amazon S3 bucket A compliance policy requires that the data never be transmitted across the internet How should the company set up the job?
Answer: D
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A company is running an Amazon SageMaker training job that will access data stored in its Amazon S3 bucket A compliance policy requires that the data never be transmitted across the internet How should the company set up the job?
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Question 2
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An analytics company has an Amazon SageMaker hosted endpoint for an image classification model. The
model is a custom-built convolutional neural network (CNN) and uses the PyTorch deep learning framework.
The company wants to increase throughput and decrease latency for customers that use the model.
Which solution will meet these requirements MOST cost-effectively?
Answer: C
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An analytics company has an Amazon SageMaker hosted endpoint for an image classification model. The
model is a custom-built convolutional neural network (CNN) and uses the PyTorch deep learning framework.
The company wants to increase throughput and decrease latency for customers that use the model.
Which solution will meet these requirements MOST cost-effectively?
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Question 3
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A retail company collects customer comments about its products from social media, the company website, and customer call logs. A team of data scientists and engineers wants to find common topics and determine which products the customers are referring to in their comments. The team is using natural language processing (NLP) to build a model to help with this classification. Each product can be classified into multiple categories that the company defines. These categories are related but are not mutually exclusive. For example, if there is mention of "Sample Yogurt" in the document of customer comments, then "Sample Yogurt" should be classified as "yogurt," "snack," and "dairy product." The team is using Amazon Comprehend to train the model and must complete the project as soon as possible. Which functionality of Amazon Comprehend should the team use to meet these requirements?
Answer: B
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Question 4
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A company wants to create an artificial intelligence (Al) yoga instructor that can lead large classes of students. The company needs to create a feature that can accurately count the number of students who are in a class. The company also needs a feature that can differentiate students who are performing a yoga stretch correctly from students who are performing a stretch incorrectly. ...etermine whether students are performing a stretch correctly, the solution needs to measure the location and angle of each student's arms and legs A data scientist must use Amazon SageMaker to ...ss video footage of a yoga class by extracting image frames and applying computer vision models. Which combination of models will meet these requirements with the LEAST effort? (Select TWO.)
Answer: C,D
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Question 5
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A company hosts a public web application on AWS. The application provides a user feedback feature that consists of free-text fields where users can submit text to provide feedback. The company receives a large amount of free-text user feedback from the online web application. The product managers at the company classify the feedback into a set of fixed categories including user interface issues, performance issues, new feature request, and chat issues for further actions by the company's engineering teams.
A machine learning (ML) engineer at the company must automate the classification of new user feedback into these fixed categories by using Amazon SageMaker. A large set of accurate data is available from the historical user feedback that the product managers previously classified.
Which solution should the ML engineer apply to perform multi-class text classification of the user feedback?
Answer: B
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A company hosts a public web application on AWS. The application provides a user feedback feature that consists of free-text fields where users can submit text to provide feedback. The company receives a large amount of free-text user feedback from the online web application. The product managers at the company classify the feedback into a set of fixed categories including user interface issues, performance issues, new feature request, and chat issues for further actions by the company's engineering teams.