Free Amazon MLS-C01 Exam Questions

Question 1

A machine learning specialist is running an Amazon SageMaker endpoint using the built-in object detection algorithm on a P3 instance for real-time predictions in a company's production application. When evaluating the model's resource utilization, the specialist notices that the model is using only a fraction of the GPU.

Which architecture changes would ensure that provisioned resources are being utilized effectively?

A : deploy the model as a batch transform job on an M5 instance.

B : deploy the model on an M5 instance. Attach Amazon Elastic Inference to the instance.

C : deploy the model on a P3dn instance.

D : ploy the model onto an Amazon Elastic Container Service (Amazon ECS) cluster using a P3 instance.

Answer: D

Question 2

A Machine Learning Specialist needs to create a data repository to hold a large amount of time-based training data for a new model. In the source system, new files are added every hour Throughout a single 24-hour period, the volume of hourly updates will change significantly. The Specialist always wants to train on the last 24 hours of the data

Which type of data repository is the MOST cost-effective solution?

A : Amazon EBS-backed Amazon EC2 instance with hourly directories

B : Amazon RDS database with hourly table partitions

C : Amazon S3 data lake with hourly object prefixes

D : Amazon EMR cluster with hourly hive partitions on Amazon EBS volumes

Answer: C

Question 3

A Machine Learning Specialist is packaging a custom ResNet model into a Docker container so the company can leverage Amazon SageMaker for training. The Specialist is using Amazon EC2 P3 instances to train the model and needs to properly configure the Docker container to leverage the NVIDIA GPUs.

What does the Specialist need to do?

A : ndle the NVIDIA drivers with the Docker image.

B : ild the Docker container to be NVIDIA-Docker compatible.

C : ganize the Docker container's file structure to execute on GPU instances.

D : t the GPU flag in the Amazon SageMaker CreateTrainingJob request body

Answer: B

Question 4

A data scientist is building a new model for an ecommerce company. The model will predict how many minutes it will take to deliver a package. During model training, the data scientist needs to evaluate model performance. Which metrics should the data scientist use to meet this requirement? (Select TWO.)

A : InferenceLatency

B : Mean squared error (MSE)

C : Root mean squared error (RMSE)

D : Precision

E : Accuracy

Answer: B,C

Question 5