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NEW QUESTION: 1
セキュリティアナリストは、アクティブなホストのネットワークをスキャンする必要があります。 仮想ホストと物理ホストを区別するのに役立つホスト特性はどれですか？
A. DNS routing tables
B. Host IPs
C. Gateway settings
D. Reserved MACs
Answer: D

NEW QUESTION: 2

A. Option A
B. Option B
C. Option C
D. Option F
E. Option D
F. Option E
Answer: A,C
Explanation:
Each node must have at least two network adapters or network interface cards (NICs): one for the public network interface, and one for the private network interface (the interconnect).
References:

NEW QUESTION: 3
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 k-means clustering algorithm to forecast demand for the new product.
C. Train an Amazon SageMaker DeepAR algorithm to forecast demand for the new product.
D. Train a custom XGBoost model to forecast demand for the new product.
Answer: C
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.
https://docs.aws.amazon.com/sagemaker/latest/dg/deepar.html