A. Option B
B. Option D
C. Option F
D. Option G
E. Option E
F. Option C
G. Option A
Answer: A,E,G
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NEW QUESTION: 1
A. Option B
B. Option D
C. Option F
D. Option G
E. Option E
F. Option C
G. Option A
Answer: A,E,G
NEW QUESTION: 2
Based on the information shown in the exhibit, which of the following is TRUE when the PGW receives a
"Create Session Request" with the "APN Restriction" set to "Private1"? Assume everything else is in working condition.
A. None of the above answers are correct.
B. The "Create Session Request" is rejected by the PGW and no bearer is created.
C. The "Create Session Request" cannot have an "APN Restriction" value of "Private1".
D. The APN cannot be configured with an "APN Restriction" value of "Private1".
E. The "Create Session Request" is accepted by the PGW and the bearer is created successfully.
Answer: B
NEW QUESTION: 3
企業は、複数のAmazonEC2インスタンス間で大量のデータを処理する分散アプリケーションを実行する必要があります。このアプリケーションは、処理の中断を許容するように設計されています。
これらの要件に対して最も費用効果の高いAmazonEC2価格設定モデルは何ですか？
A. リザーブドインスタンス
B. オンデマンドインスタンス
C. 専用ホスト
D. スポットインスタンス
Answer: D
Explanation:
https://aws.amazon.com/blogs/big-data/best-practices-for-running-apache-spark-applications- using-amazon-ec2-spot-instances-with-amazon-emr/
NEW QUESTION: 4
A large consumer goods manufacturer has the following products on sale
* 34 different toothpaste variants
* 48 different toothbrush variants
* 43 different mouthwash variants
The entire sales history of all these products is available in Amazon S3 Currently, the company is using custom-built autoregressive integrated moving average (ARIMA) models to forecast demand for these products The company wants to predict the demand for a new product that will soon be launched Which solution should a Machine Learning Specialist apply?
A. Train a custom ARIMA model to forecast demand for the new product.
B. Train an Amazon SageMaker DeepAR algorithm to forecast demand for the new product
C. Train a custom XGBoost model to forecast demand for the new product
D. Train an Amazon SageMaker k-means clustering algorithm to forecast demand for the new product.
Answer: B
Explanation:
Explanation
The Amazon SageMaker DeepAR forecasting algorithm is a supervised learning algorithm for forecasting scalar (one-dimensional) time series using recurrent neural networks (RNN). Classical forecasting methods, such as autoregressive integrated moving average (ARIMA) or exponential smoothing (ETS), fit a single model to each individual time series. They then use that model to extrapolate the time series into the future.