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Download AWS Certified Machine Learning - Specialty Exam Dumps
NEW QUESTION 43
A large mobile network operating company is building a machine learning model to predict customers who are likely to unsubscribe from the service. The company plans to offer an incentive for these customers as the cost of churn is far greater than the cost of the incentive.
The model produces the following confusion matrix after evaluating on a test dataset of 100 customers:
Based on the model evaluation results, why is this a viable model for production?
- A. The precision of the model is 86%, which is greater than the accuracy of the model.
- B. The model is 86% accurate and the cost incurred by the company as a result of false positives is less than the false negatives.
- C. The precision of the model is 86%, which is less than the accuracy of the model.
- D. The model is 86% accurate and the cost incurred by the company as a result of false negatives is less than the false positives.
Answer: D
NEW QUESTION 44
A Machine Learning Specialist is given a structured dataset on the shopping habits of a company's customer base. The dataset contains thousands of columns of data and hundreds of numerical columns for each customer. The Specialist wants to identify whether there are natural groupings for these columns across all customers and visualize the results as quickly as possible.
What approach should the Specialist take to accomplish these tasks?
- A. Run k-means using the Euclidean distance measure for different values of k and create box plots for each numerical column within each cluster.
- B. Embed the numerical features using the t-distributed stochastic neighbor embedding (t-SNE) algorithm and create a scatter plot.
- C. Embed the numerical features using the t-distributed stochastic neighbor embedding (t-SNE) algorithm and create a line graph.
- D. Run k-means using the Euclidean distance measure for different values of k and create an elbow plot.
Answer: D
NEW QUESTION 45
A Machine Learning Specialist is using an Amazon SageMaker notebook instance in a private subnet of a corporate VPC. The ML Specialist has important data stored on the Amazon SageMaker notebook instance's Amazon EBS volume, and needs to take a snapshot of that EBS volume. However the ML Specialist cannot find the Amazon SageMaker notebook instance's EBS volume or Amazon EC2 instance within the VPC.
Why is the ML Specialist not seeing the instance visible in the VPC?
- A. Amazon SageMaker notebook instances are based on the Amazon ECS service within customer accounts.
- B. Amazon SageMaker notebook instances are based on AWS ECS instances running within AWS service accounts.
- C. Amazon SageMaker notebook instances are based on EC2 instances running within AWS service accounts.
- D. Amazon SageMaker notebook instances are based on the EC2 instances within the customer account but they run outside of VPCs.
Answer: D
NEW QUESTION 46
When submitting Amazon SageMaker training jobs using one of the built-in algorithms, which common parameters MUST be specified? (Choose three.)
- A. Hyperparameters in a JSON array as documented for the algorithm used.
- B. The IAM role that Amazon SageMaker can assume to perform tasks on behalf of the users.
- C. The Amazon EC2 instance class specifying whether training will be run using CPU or GPU.
- D. The output path specifying where on an Amazon S3 bucket the trained model will persist.
- E. The training channel identifying the location of training data on an Amazon S3 bucket.
- F. The validation channel identifying the location of validation data on an Amazon S3 bucket.
Answer: C,D,E
NEW QUESTION 47
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