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NEW QUESTION: 1
Which statement is correct?
A. Fan-in is the ratio of host ports to storage ports; an indication of host traffic load at a single storage port.
B. Fan-in is the ratio of switch ports to host ports; and indication of switch load at a single host port.
C. Fan-in is the ratio of storage ports to host ports; an indication of storage load at a single host port.
D. Fan-in is the ratio of switch ports to storage ports; an indication of switch load at a single storage port.
Answer: C
NEW QUESTION: 2
A. Option A
B. Option D
C. Option C
D. Option B
Answer: A
Explanation:
If you perform work that involves sharing documents or collaborating directly with vendors, clients, or customers, then you might want to use your sites to share content with people outside your organization who do not have licenses for your Office 365 subscription.
There are three ways that you can do this:
*You can send users a guest link that they can use to view individual documents on your site anonymously.
*You can share an entire site by inviting external users to sign in to your site using a Microsoft account* or a work account.
*You can share individual documents by inviting external users to sign in to your site using a Microsoft account* or a workacct_short.
Reference: Share sites or documents with people outside your organization
https://support.office.com/en-AU/article/Share-sites-or-documents-with-people-outsideyour-organization-5f4cee39-5c91-4dc8-8fb1-96bca76f4eb0
NEW QUESTION: 3
A. Burn-in
B. Artifacts
C. Dead pixels
D. incorrect patterns incorrect
E. Distorted image
F. Distorted geometry
Answer: B,E
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 plan to use a Python script to run an Azure Machine Learning experiment. The script creates a reference to the experiment run context, loads data from a file, identifies the set of unique values for the label column, and completes the experiment run:
from azureml.core import Run
import pandas as pd
run = Run.get_context()
data = pd.read_csv('data.csv')
label_vals = data['label'].unique()
# Add code to record metrics here
run.complete()
The experiment must record the unique labels in the data as metrics for the run that can be reviewed later.
You must add code to the script to record the unique label values as run metrics at the point indicated by the comment.
Solution: Replace the comment with the following code:
run.upload_file('outputs/labels.csv', './data.csv')
Does the solution meet the goal?
A. No
B. Yes
Answer: A
Explanation:
Explanation
label_vals has the unique labels (from the statement label_vals = data['label'].unique()), and it has to be logged.
Note:
Instead use the run_log function to log the contents in label_vals:
for label_val in label_vals:
run.log('Label Values', label_val)
Reference:
https://www.element61.be/en/resource/azure-machine-learning-services-complete-toolbox-ai