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NEW QUESTION: 1
A network administrator wants to apply a critical PoE priority to any ArubaOS switch port that connects to an Aruba AR The priority should be applied dynamically based on LLDP messages received from the AP.
Which step should the administrator take to meet this goal?
A. Enable LLDP MED TLV extensions on the switch port.
B. Configure the PoE usage setting on all ports as class and make sure that Aruba APs are defined as
Class 4 devices.
C. Enable the default AP profile bound to the Aruba AP device type.
D. Configure the PoE usage setting on all ports as tfdp.
Answer: C
NEW QUESTION: 2
What happens when two EIGRP peers have mismatched K values?
A. The two devices are unable to correctly perform unequal-cost load balancing.
B. The two devices fail to form an adjacency.
C. The two devices are unable to correctly perform equal-cost routing.
D. The two devices fail to perform EIGRP graceful shutdown when one device goes down.
Answer: D
NEW QUESTION: 3
ユニバーサルコンテナーはコンテナーを販売し、1回出荷し、支払いは毎月行われます。何をスケジューリングする必要がありますか?
A. クォータ
B. 数量
C. 収益と数量
D. 収益
Answer: D
NEW QUESTION: 4
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. Yes
B. No
Answer: B
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