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NEW QUESTION: 1
次のインシデント処理プロセスフェーズのうち、ルールの定義、人的労働力のコラボレーション、バックアップ計画の作成、および組織の計画のテストを担当しているのはどれですか？
A. 準備段階
B. 封じ込めフェーズ
C. 識別フェーズ
D. 回復フェーズ
Answer: A

NEW QUESTION: 2
You have a Dynamics CHM organization that uses folder tracking.
You have a folder named Customers that is currently being tracked- Customers contains a folder for The main contact named Contact1.
A new email message from Contact1 is delivered to your Inbox.
You need to identity what will occur when you move the message to the Customer1 folder.
What should you identify?
A. An email activity will be created in CRM rhat has the Set regarding field Set to Customer1
B. An email act.v.Ty will be created in CRM that has a connection to Contact1 only.
C. An email activity will be created in CRM that has a connection to Customer1 and to Contact1
D. An email activity will be created in CRM that has the Set regarding field set to Contact1
E. An email activity will be created m CRM that has a connection To Customer1 only.
Answer: D

NEW QUESTION: 3
A Machine Learning Specialist is developing a custom video recommendation model for an application. The dataset used to train this model is very large with millions of data points and is hosted in an Amazon S3 bucket. The Specialist wants to avoid loading all of this data onto an Amazon SageMaker notebook instance because it would take hours to move and will exceed the attached 5 GB Amazon EBS volume on the notebook instance.
Which approach allows the Specialist to use all the data to train the model?
A. Load a smaller subset of the data into the SageMaker notebook and train locally. Confirm that the training code is executing and the model parameters seem reasonable. Initiate a SageMaker training job using the full dataset from the S3 bucket using Pipe input mode.
B. Use AWS Glue to train a model using a small subset of the data to confirm that the data will be compatible with Amazon SageMaker. Initiate a SageMaker training job using the full dataset from the S3 bucket using Pipe input mode.
C. Load a smaller subset of the data into the SageMaker notebook and tram locally. Confirm that the training code is executing and the model parameters seem reasonable. Launch an Amazon EC2 instance with an AWS Deep Learning AMI and attach the S3 bucket to train the full dataset.
D. Launch an Amazon EC2 instance with an AWS Deep Learning AMI and attach the S3 bucket to the instance. Train on a small amount of the data to verify the training code and hyperparameters. Go back to Amazon SageMaker and train using the full dataset
Answer: C

NEW QUESTION: 4
Select the two data formats supported by Oracle WMS Cloud with its built-in interfaces and APIs. (Choose two.)
A. pdf
B. JSON
C. XML
D. EDI
E. Delimited Flat File
Answer: C,E
Explanation:
Explanation/Reference:
Reference: https://docs.oracle.com/cloud/latest/owmcs_gs-cloud/OWMAP/OWMAP.pdf (6)