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NEW QUESTION: 1
How can EIGRP topologies be designed to converge as fast as possible in the event of a point-to-point link failure?
A. Limit the query domain by use of distribute lists.
B. Build neighbor adjacencies in a triangulated fashion
C. Limit the query domain by use of default routes
D. Limit the query domain by use of summarization
E. Build neighbor adjacencies in a squared fashion
Answer: D
Explanation:
Explanation
https://blog.ine.com/2009/08/02/eigrp-query-scoping

NEW QUESTION: 2
엑사 바이트 규모의 데이터 세트를 AWS로 마이그레이션하거나 전송하는 안전하고 빠르며 비용 효율적인 방법을 제공하는 AWS 서비스는 무엇입니까?
A. AWS Migration Hub
B. AWS Snowball
C. AWS Batch
D. AWS Snowmobile
Answer: D
Explanation:
AWS Snowmobile is an exabyte-scale data transfer service that can move extremely large amounts of data to AWS in a fast, secure, and cost-effective manner. You can transfer up to 100PB per Snowmobile, a 45-foot long ruggedized shipping container, pulled by a semi-trailer truck. Snowmobile makes it easy to move massive volumes of data to the cloud, including video libraries, image repositories, or even a complete data center migration. All data is encrypted with 256-bit encryption and you can manage your encryption keys with AWS Key Management Service (AWS KMS). Snowmobile includes GPS tracking, alarm monitoring, 24/7 video surveillance and an optional escort security vehicle while in transit.

NEW QUESTION: 3
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have a Python script named train.py in a local folder named scripts. The script trains a regression model by using scikit-learn. The script includes code to load a training data file which is also located in the scripts folder.
You must run the script as an Azure ML experiment on a compute cluster named aml-compute.
You need to configure the run to ensure that the environment includes the required packages for model training. You have instantiated a variable named aml-compute that references the target compute cluster.
Solution: Run the following code:

Does the solution meet the goal?
A. No
B. Yes
Answer: A
Explanation:
Explanation
The scikit-learn estimator provides a simple way of launching a scikit-learn training job on a compute target. It is implemented through the SKLearn class, which can be used to support single-node CPU training.
Example:
from azureml.train.sklearn import SKLearn
}
estimator = SKLearn(source_directory=project_folder,
compute_target=compute_target,
entry_script='train_iris.py'
)
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-train-scikit-learn

NEW QUESTION: 4
When is masking data in the test environments NOT an important consideration?
A. A majority of the data is personally identifiable information
B. The client does not have any sensitive data
C. Outsourced application testing requires personally identifying information being sent overseas
D. Testers and developers have access to sensitive data
Answer: B