Exam style questions across every MLS-C01 domain
Last Update 5 months ago
Total Questions : 330
Start with our free MLS-C01 practice questions, carefully crafted to mirror the domains, phrasing, and difficulty of the real AWS Certified Specialty exam. Each MLS-C01 exam question comes with a detailed rationale that explains not just which answer is correct but why the others fall short. That's how concepts stick. Use the free set to benchmark yourself: identify your Amazon Web Services weak domains, see where you're losing marks, and build a focused study plan in minutes.
A Machine Learning Specialist is configuring Amazon SageMaker so multiple Data Scientists can access notebooks, train models, and deploy endpoints. To ensure the best operational performance, the Specialist needs to be able to track how often the Scientists are deploying models, GPU and CPU utilization on the deployed SageMaker endpoints, and all errors that are generated when an endpoint is invoked.
Which services are integrated with Amazon SageMaker to track this information? (Select TWO.)
An employee found a video clip with audio on a company's social media feed. The language used in the video is Spanish. English is the employee's first language, and they do not understand Spanish. The employee wants to do a sentiment analysis.
What combination of services is the MOST efficient to accomplish the task?
A bank has collected customer data for 10 years in CSV format. The bank stores the data in an on-premises server. A data science team wants to use Amazon SageMaker to build and train a machine learning (ML) model to predict churn probability. The team will use the historical data. The data scientists want to perform data transformations quickly and to generate data insights before the team builds a model for production.
Which solution will meet these requirements with the LEAST development effort?
A machine learning (ML) specialist is running an Amazon SageMaker hyperparameter optimization job for a model that is based on the XGBoost algorithm. The ML specialist selects Root Mean Square Error (RMSE) as the objective evaluation metric.
The ML specialist discovers that the model is overfitting and cannot generalize well on the validation data. The ML specialist decides to resolve the model overfitting by using SageMaker automatic model tuning (AMT).
Which solution will meet this requirement?
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?
