Free Amazon MLA-C01 Exam Questions
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Amazon MLA-C01 Exam Questions
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Provided By: Amazon
- Exam: AWS Certified Machine Learning Engineer Associate
- Certification: AWS Certified Machine Learning
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Total Questions: 339
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Updated On: Jun 03, 2025
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Rated: 4.9 |
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Online Users: 678
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Question 1
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A Machine Learning Specialist is preparing data for training on Amazon SageMaker.The Specialist is using one of the SageMaker built-in algorithms for the training.The dataset is stored in .CSV format and is transformed into a numpy.array, which appears to be negatively affecting the speed of the training.What should the Specialist do to optimize the data for training on SageMaker?
Answer: C
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A Machine Learning Specialist is preparing data for training on Amazon SageMaker.The Specialist is using one of the SageMaker built-in algorithms for the training.The dataset is stored in .CSV format and is transformed into a numpy.array, which appears to be negatively affecting the speed of the training.What should the Specialist do to optimize the data for training on SageMaker?
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Question 2
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A company has historical data that shows whether customers needed long-term support from
company staff. The company needs to develop an ML model to predict whether new customers will
require long-term support.
Which modeling approach should the company use to meet this requirement?
Answer: C
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A company has historical data that shows whether customers needed long-term support from
company staff. The company needs to develop an ML model to predict whether new customers will
require long-term support.
Which modeling approach should the company use to meet this requirement?
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Question 3
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A company is building a deep learning model on Amazon SageMaker. The company uses a large
amount of data as the training dataset. The company needs to optimize the model's
hyperparameters to minimize the loss function on the validation dataset. Which hyperparameter tuning strategy will accomplish this goal with the LEAST computation time?
Answer: A
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A company is building a deep learning model on Amazon SageMaker. The company uses a large
amount of data as the training dataset. The company needs to optimize the model's
hyperparameters to minimize the loss function on the validation dataset. Which hyperparameter tuning strategy will accomplish this goal with the LEAST computation time?
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Question 4
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A company has historical data that shows whether customers needed long-term support from
company staff. The company needs to develop an ML model to predict whether new customers will
require long-term support.
Which modeling approach should the company use to meet this requirement?
Answer: C
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A company has historical data that shows whether customers needed long-term support from
company staff. The company needs to develop an ML model to predict whether new customers will
require long-term support.
Which modeling approach should the company use to meet this requirement?
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Question 5
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An ML engineer has developed a binary classification model outside of Amazon SageMaker. The ML
engineer needs to make the model accessible to a SageMaker Canvas user for additional tuning.
The model artifacts are stored in an Amazon S3 bucket. The ML engineer and the Canvas user are
part of the same SageMaker domain.
Which combination of requirements must be met so that the ML engineer can share the model with
the Canvas user? (Choose two.)
Answer: B,C
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An ML engineer has developed a binary classification model outside of Amazon SageMaker. The ML
engineer needs to make the model accessible to a SageMaker Canvas user for additional tuning.
The model artifacts are stored in an Amazon S3 bucket. The ML engineer and the Canvas user are
part of the same SageMaker domain.
Which combination of requirements must be met so that the ML engineer can share the model with
the Canvas user? (Choose two.)