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Free Practice Amazon MLS-C01 Exam Questions 2025

Stay ahead with 100% Free AWS Certified Machine Learning - Specialty MLS-C01 Dumps Practice Questions

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Total 385 Questions | Updated On: Aug 25, 2021
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Question 1

A bank wants to use a machine learning (ML) model to predict if users will default on credit card payments. The
training data consists of 30,000 labeled records and is evenly balanced between two categories. For the model,
an ML specialist selects the Amazon SageMaker built-in XGBoost algorithm and configures a SageMaker
automatic hyperparameter optimization job with the Bayesian method. The ML specialist uses the validation
accuracy as the objective metric.
When the bank implements the solution with this model, the prediction accuracy is 75%. The bank has given
the ML specialist 1 day to improve the model in production.
Which approach is the FASTEST way to improve the model's accuracy?


Answer: A
Question 2

An insurance company developed a new experimental machine learning (ML) model to replace an existing model that is in production. The company must validate the quality of predictions from the new experimental model in a production environment before the company uses the new experimental model to serve general user requests.

New one model can serve user requests at a time. The company must measure the performance of the new experimental model without affecting the current live traffic.

Which solution will meet these requirements?


Answer: D
Question 3

A data scientist receives a collection of insurance claim records. Each record includes a claim ID. the final outcome of the insurance claim, and the date of the final outcome.

The final outcome of each claim is a selection from among 200 outcome categories. Some claim records include only partial information. However, incomplete claim records include only 3 or 4 outcome categories from among the 200 available outcome categories. The collection includes hundreds of records for each outcome category. The records are from the previous 3 years.

The data scientist must create a solution to predict the number of claims that will be in each outcome category every month, several months in advance.

Which solution will meet these requirements?


Answer: C
Question 4

n online delivery company wants to choose the fastest courier for each delivery at the moment an order is placed. The company wants to implement this feature for existing users and new users of its application. Data scientists have trained separate models with XGBoost for this purpose, and the models are stored in Amazon S3. There is one model for each city where the company operates.

Operation engineers are hosting these models in Amazon EC2 for responding to the web client requests, with one instance for each model, but the instances have only a 5% utilization in CPU and memory. The operation engineers want to avoid managing unnecessary resources.

Which solution will enable the company to achieve its goal with the LEAST operational overhead?


Answer: B
Question 5

A Machine Learning Specialist is building a convolutional neural network (CNN) that will classify 10 types of animals. The Specialist has built a series of layers in a neural network that will take an input image of an animal, pass it through a series of convolutional and pooling layers, and then finally pass it through a dense and fully connected layer with 10 nodes The Specialist would like to get an output from the neural network that is a probability distribution of how likely it is that the input image belongs to each of the 10 classes
Which function will produce the desired output?


Answer: C
Page:    1 / 77      
Total 385 Questions | Updated On: Aug 25, 2021
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