Free AWS Certified Machine Learning - Specialty (MLS-C01) Exam Questions and Answers

A Machine Learning Specialist at a company sensitive to security is preparing a dataset for model training. The dataset is stored in Amazon S3 and contains Personally Identifiable Information (Pll). The dataset: * Must be accessible from a VPC only. * Must not traverse the public internet. How can these requirements be satisfied?

• AA. Create a VPC endpoint and apply a bucket access policy that restricts access to the given VPC endpoint and the VPC.
• BB. Create a VPC endpoint and apply a bucket access policy that allows access from the given VPC endpoint and an Amazon EC2 instance.
• CC. Create a VPC endpoint and use Network Access Control Lists (NACLs) to allow traffic between only the given VPC endpoint and an Amazon EC2 instance.
• DD. Create a VPC endpoint and use security groups to restrict access to the given VPC endpoint and an Amazon EC2 instance.

A Machine Learning Specialist built an image classification deep learning model. However the Specialist ran into an overfitting problem in which the training and testing accuracies were 99% and 75%r respectively. How should the Specialist address this issue and what is the reason behind it?

• AA. The learning rate should be increased because the optimization process was trapped at a local minimum.
• BB. The dropout rate at the flatten layer should be increased because the model is not generalized enough.
• CC. The dimensionality of dense layer next to the flatten layer should be increased because the model is not complex enough.
• DD. The epoch number should be increased because the optimization process was terminated before it reached the global minimum.

A Data Science team within a large company uses Amazon SageMaker notebooks to access data stored in Amazon S3 buckets. The IT Security team is concerned that internet-enabled notebook instances create a security vulnerability where malicious code running on the instances could compromise data privacy. The company mandates that all instances stay within a secured VPC with no internet access, and data communication traffic must stay within the AWS network. How should the Data Science team configure the notebook instance placement to meet these requirements?

• AA. Associate the Amazon SageMaker notebook with a private subnet in a VP
• BB. Place the Amazon SageMaker endpoint and S3 buckets within the same VPC.
• CC. Associate the Amazon SageMaker notebook with a private subnet in a VP
• DD. Use 1AM policies to grant access to Amazon S3 and Amazon SageMaker.
• EE. Associate the Amazon SageMaker notebook with a private subnet in a VP
• FF. Ensure the VPC has S3 VPC endpoints and Amazon SageMaker VPC endpoints attached to it.
• GG. Associate the Amazon SageMaker notebook with a private subnet in a VP
• HH. Ensure the VPC has a NAT gateway and an associated security group allowing only outbound connections to Amazon S3 and Amazon SageMaker

A Machine Learning Specialist wants to determine the appropriate SageMakerVariant Invocations Per Instance setting for an endpoint automatic scaling configuration. The Specialist has performed a load test on a single instance and determined that peak requests per second (RPS) without service degradation is about 20 RPS As this is the first deployment, the Specialist intends to set the invocation safety factor to 0 5 Based on the stated parameters and given that the invocations per instance setting is measured on a per-minute basis, what should the Specialist set as the sageMakervariantinvocationsPerinstance setting?

• AA. 10
• BB. 30
• CC. 600
• DD. 2,400

A Machine Learning Specialist was given a dataset consisting of unlabeled data The Specialist must create a model that can help the team classify the data into different buckets What model should be used to complete this work?

• AA. K-means clustering
• BB. Random Cut Forest (RCF)
• CC. XGBoost
• DD. BlazingText

A Machine Learning Specialist is working for a credit card processing company and receives an unbalanced dataset containing credit card transactions. It contains 99,000 valid transactions and 1,000 fraudulent transactions The Specialist is asked to score a model that was run against the dataset The Specialist has been advised that identifying valid transactions is equally as important as identifying fraudulent transactions What metric is BEST suited to score the model?

• AA. Precision
• BB. Recall
• CC. Area Under the ROC Curve (AUC)
• DD. Root Mean Square Error (RMSE)

While working on a neural network project, a Machine Learning Specialist discovers thai some features in the data have very high magnitude resulting in this data being weighted more in the cost function What should the Specialist do to ensure better convergence during backpropagation?

• AA. Dimensionality reduction
• BB. Data normalization
• CC. Model regulanzation
• DD. Data augmentation for the minority class

A company is running a machine learning prediction service that generates 100 TB of predictions every day A Machine Learning Specialist must generate a visualization of the daily precision-recall curve from the predictions, and forward a read-only version to the Business team. Which solution requires the LEAST coding effort?

• AA. Run a daily Amazon EMR workflow to generate precision-recall data, and save the results in Amazon S3 Give the Business team read-only access to S3
• BB. Generate daily precision-recall data in Amazon QuickSight, and publish the results in a dashboard shared with the Business team
• CC. Run a daily Amazon EMR workflow to generate precision-recall data, and save the results in Amazon S3 Visualize the arrays in Amazon QuickSight, and publish them in a dashboard shared with the Business team
• DD. Generate daily precision-recall data in Amazon ES, and publish the results in a dashboard shared with the Business team.

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 do1?

• AA. Bundle the NVIDIA drivers with the Docker image
• BB. Build the Docker container to be NVIDIA-Docker compatible
• CC. Organize the Docker container's file structure to execute on GPU instances.
• DD. Set the GPU flag in the Amazon SageMaker Create TrainingJob request body

A company is running an Amazon SageMaker training job that will access data stored in its Amazon S3 bucket A compliance policy requires that the data never be transmitted across the internet How should the company set up the job?

• AA. Launch the notebook instances in a public subnet and access the data through the public S3 endpoint
• BB. Launch the notebook instances in a private subnet and access the data through a NAT gateway
• CC. Launch the notebook instances in a public subnet and access the data through a NAT gateway
• DD. Launch the notebook instances in a private subnet and access the data through an S3 VPC endpoint.