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Amazon MLS-C01 認定試験の出題範囲：

>> MLS-C01的中問題集 <<

完璧Amazon MLS-C01｜一番優秀なMLS-C01的中問題集試験｜試験の準備方法AWS Certified Machine Learning - Specialtyミシュレーション問題

テストMLS-C01の認定に合格すると、あなたの就労能力が社会から認められ、良い仕事を見つけることができます。 MLS-C01クイズトレントを習得して試験に合格した場合。同僚、上司、親relative、友人、社会から尊敬されます。総じて、MLS-C01テスト準備を購入すると、試験に合格するだけでなく、キャリアと将来についての夢を実現するのに役立ちます。ですから、MLS-C01試験の教材を購入してすぐに行動を起こすことをheしないでください。

Amazon AWS Certified Machine Learning - Specialty 認定 MLS-C01 試験問題 (Q167-Q172):

質問 # 167
An aircraft engine manufacturing company is measuring 200 performance metrics in a time-series. Engineers want to detect critical manufacturing defects in near-real time during testing. All of the data needs to be stored for offline analysis.
What approach would be the MOST effective to perform near-real time defect detection?

• A. Use AWS IoT Analytics for ingestion, storage, and further analysis. Use Jupyter notebooks from within AWS IoT Analytics to carry out analysis for anomalies.
• B. Use Amazon Kinesis Data Firehose for ingestion and Amazon Kinesis Data Analytics Random Cut Forest (RCF) to perform anomaly detection. Use Kinesis Data Firehose to store data in Amazon S3 for further
• C. Use Amazon S3 for ingestion, storage, and further analysis. Use an Amazon EMR cluster to carry out Apache Spark ML k-means clustering to determine anomalies.
• D. Use Amazon S3 for ingestion, storage, and further analysis. Use the Amazon SageMaker Random Cut Forest (RCF) algorithm to determine anomalies.

正解：C

解説：
analysis.

質問 # 168
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 model is 86% accurate and the cost incurred by the company as a result of false negatives is less than the false positives.
• B. The precision of the model is 86%, which is greater than the accuracy of the model.
• 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 positives is less than the false negatives.

正解：A

質問 # 169
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?

• A. Rectified linear units (ReLU)
• B. Smooth L1 loss
• C. Dropout
• D. Softmax

正解：D

質問 # 170
A Data Scientist needs to analyze employment data. The dataset contains approximately 10 million observations on people across 10 different features. During the preliminary analysis, the Data Scientist notices that income and age distributions are not normal. While income levels shows a right skew as expected, with fewer individuals having a higher income, the age distribution also show a right skew, with fewer older individuals participating in the workforce.
Which feature transformations can the Data Scientist apply to fix the incorrectly skewed data? (Choose two.)

• A. High-degree polynomial transformation
• B. Cross-validation
• C. Numerical value binning
• D. Logarithmic transformation
• E. One hot encoding

正解：B、C

質問 # 171
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 model is 86% accurate and the cost incurred by the company as a result of false negatives is less than the false positives.
• B. The precision of the model is 86%, which is greater than the accuracy of the model.
• 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 positives is less than the false negatives.

正解：A

質問 # 172
......

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