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NEW QUESTION: 1
When forwarding a multicast frame, the normal behavior for a LAN switch with IGMP snooping enabled is
to forward the frame based on the similar rules as if it were:
A. A unicast frame with a known destination in the forwarding table
B. A unicast frame with an unknown source in the forwarding table
C. A unicast frame with a known source in the forwarding table
D. A unicast frame with an unknown destination in the forwarding table
Answer: A

NEW QUESTION: 2
You are creating a document in InDesign CS5. You want to apply tags on your document. Which of the following commands can be used to import tags? Each correct answer represents a complete solution. Choose all that apply.
A. Choose File > Import XML
B. Choose File > import
C. Choose Window > Tags
D. Choose Object > Tags
Answer: A,C
Explanation:
There are two places where you can import tags.
1.The Tags panel (choose Window > Tags)
2.The Import XML dialog box (choose File > Import XML).
Answer A and D are incorrect. These are invalid answer options.

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. Yes
B. No
Answer: A
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

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