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NEW QUESTION: 1
To collect per client NFS statistics on a storage system, the option nfs.per_client_stats.enable must be set on.
A. True
B. False
Answer: A
Explanation:
https://library.netapp.com/ecmdocs/ECMP1196979/html/man1/na_options.1.html
nfs.per_client_stats.enable Enables/disables the collection and display of perclient NFS statistics, as described in na_nfsstat(1). Validvalues for this option are on or off. The default value for this option is off.

NEW QUESTION: 2
Cisco AMP for Endpointsの2つの機能で、アップロードされたファイルをブロックできますか？ （2つ選択してください。）
A. ファイルリポジトリ
B. 簡単なカスタム検出
C. アプリケーションのブロック
D. アプリケーションのホワイトリスト
E. 除外
Answer: B,C

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 an Amazon SageMaker k-means clustering algorithm 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 ARIMA model to forecast demand for the new product.
D. Train a custom XGBoost model 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.