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Amazon Web Services MLS-C01 Exam With Confidence Using Practice Dumps

Exam Code:
MLS-C01
Exam Name:
AWS Certified Machine Learning - Specialty
Certification:
Questions:
322
Last Updated:
Apr 24, 2025
Exam Status:
Stable
Amazon Web Services MLS-C01

MLS-C01: AWS Certified Specialty Exam 2025 Study Guide Pdf and Test Engine

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AWS Certified Machine Learning - Specialty Questions and Answers

Question 1

A Machine Learning Specialist previously trained a logistic regression model using scikit-learn on a local

machine, and the Specialist now wants to deploy it to production for inference only.

What steps should be taken to ensure Amazon SageMaker can host a model that was trained locally?

Options:

A.

Build the Docker image with the inference code. Tag the Docker image with the registry hostname andupload it to Amazon ECR.

B.

Serialize the trained model so the format is compressed for deployment. Tag the Docker image with theregistry hostname and upload it to Amazon S3.

C.

Serialize the trained model so the format is compressed for deployment. Build the image and upload it toDocker Hub.

D.

Build the Docker image with the inference code. Configure Docker Hub and upload the image to Amazon ECR.

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Question 2

A sports analytics company is providing services at a marathon. Each runner in the marathon will have their race ID printed as text on the front of their shirt. The company needs to extract race IDs from images of the runners.

Which solution will meet these requirements with the LEAST operational overhead?

Options:

A.

Use Amazon Rekognition.

B.

Use a custom convolutional neural network (CNN).

C.

Use the Amazon SageMaker Object Detection algorithm.

D.

Use Amazon Lookout for Vision.

Question 3

A company wants to forecast the daily price of newly launched products based on 3 years of data for older product prices, sales, and rebates. The time-series data has irregular timestamps and is missing some values.

Data scientist must build a dataset to replace the missing values. The data scientist needs a solution that resamptes the data daily and exports the data for further modeling.

Which solution will meet these requirements with the LEAST implementation effort?

Options:

A.

Use Amazon EMR Serveriess with PySpark.

B.

Use AWS Glue DataBrew.

C.

Use Amazon SageMaker Studio Data Wrangler.

D.

Use Amazon SageMaker Studio Notebook with Pandas.