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Amazon AWS-Certified-Machine-Learning-Specialty 認定試験の出題範囲：

トピック	出題範囲
トピック 1	Build Machine Learning Solutions For Performance, Availability, Scalability, Resiliency, And Fault Tolerance
トピック 2	Evaluate Machine Learning Models Perform Hyperparameter Optimization
トピック 3	Apply Basic AWS Security Practices To Machine Learning Solutions
トピック 4	Frame Business Problems As Machine Learning Problems Machine Learning Implementation And Operations
トピック 5	Recommend And Implement The Appropriate Machine Learning Services And Features For A Given Problem
トピック 6	Identify And Implement A Data-Transformation Solution Perform Feature Engineering
トピック 7	Analyze And Visualize Data For Machine Learning

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Amazon AWS Certified Machine Learning - Specialty 認定 AWS-Certified-Machine-Learning-Specialty 試験問題 (Q93-Q98):

質問 # 93
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?

• A. Random Cut Forest (RCF)
• B. BlazingText
• C. XGBoost
• D. K-means clustering

正解：D
質問 # 94
A Machine Learning Specialist trained a regression model, but the first iteration needs optimizing. The Specialist needs to understand whether the model is more frequently overestimating or underestimating the target.
What option can the Specialist use to determine whether it is overestimating or underestimating the target value?

• A. Confusion matrix
• B. Root Mean Square Error (RMSE)
• C. Residual plots
• D. Area under the curve

正解：D
質問 # 95
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 (PII).
The dataset:
- Must be accessible from a VPC only.
- Must not traverse the public internet.
How can these requirements be satisfied?

• A. Create a VPC endpoint and apply a bucket access policy that allows access from the given VPC endpoint and an Amazon EC2 instance.
• B. Create a VPC endpoint and apply a bucket access policy that restricts access to the given VPC endpoint and the VPC.
• C. Create a VPC endpoint and use security groups to restrict access to the given VPC endpoint and an Amazon EC2 instance
• D. 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.

正解：A 解説：
https://docs.aws.amazon.com/AmazonS3/latest/dev/example-bucket-policies-vpc-endpoint.html
質問 # 96
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 (PII).
The dataset:
* Must be accessible from a VPC only.
* Must not traverse the public internet.
How can these requirements be satisfied?

• A. Create a VPC endpoint and apply a bucket access policy that allows access from the given VPC endpoint and an Amazon EC2 instance.
• B. Create a VPC endpoint and apply a bucket access policy that restricts access to the given VPC endpoint and the VPC.
• C. Create a VPC endpoint and use security groups to restrict access to the given VPC endpoint and an Amazon EC2 instance
• D. 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.

正解：A 解説：
Explanation/Reference: https://docs.aws.amazon.com/AmazonS3/latest/dev/example-bucket-policies-vpc-endpoint.html
質問 # 97
A company's Machine Learning Specialist needs to improve the training speed of a time-series forecasting model using TensorFlow. The training is currently implemented on a single-GPU machine and takes approximately 23 hours to complete. The training needs to be run daily.
The model accuracy is acceptable, but the company anticipates a continuous increase in the size of the training data and a need to update the model on an hourly, rather than a daily, basis. The company also wants to minimize coding effort and infrastructure changes.
What should the Machine Learning Specialist do to the training solution to allow it to scale for future demand?

• A. Do not change the TensorFlow code. Change the machine to one with a more powerful GPU to speed up the training.
• B. Move the training to Amazon EMR and distribute the workload to as many machines as needed to achieve the business goals.
• C. Switch to using a built-in AWS SageMaker DeepAR model. Parallelize the training to as many machines as needed to achieve the business goals.
• D. Change the TensorFlow code to implement a Horovod distributed framework supported by Amazon SageMaker. Parallelize the training to as many machines as needed to achieve the business goals.

正解：D
質問 # 98
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