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NEW QUESTION: 1
Refer to the exhibit.


A network administrator receives a call from a contractor that was recently given wireless access to the network. The user reports that the response time is slow and suggests there might be a problem with the WLAN. The network administrator checks RF performance in AirWave to find the user and sees the output shown in the exhibit.
What can the network administrator conclude after analyzing the data?
A. Client health and CNR are high, therefore, it is unlikely the client is experiencing an RF-related issue.
B. Client health and SNR are high but usage is low; therefore, there might be packet drops.
C. Client health is low, which suggests that there are packet drops and collisions in the RF environment.
D. Goodput is low in relation to connection speed, which suggests a channel with high utilization, another channel should be used.
Answer: D

NEW QUESTION: 2
The following is a network diagram for a project.

What is the critical path for the project?
A. A-B-C-F-G-I
B. A-D-E-F-H-I
C. A-D-E-F-G-I
D. A-B-C-F-H-I
Answer: A

NEW QUESTION: 3
Sales representatives and partners of Universal Containers constantly complain about the poor quality of lead
data. Leads are owned by the Vice President of Marketing, who has established a task force and a project to
remedy the situation. Which approach should the task force consider to improve and maintain the quality of
lead data? Choose 2 answers
A. Use Data.com to clean the existing lead data and new data going forward.
B. Import the lead data using the Find Duplicates wizard on the lead object.
C. Create a workflow notification when leads are created with poor Quality data.
D. Use tools like the Lead Import wizard to identify and remove duplicates.
Answer: A,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 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. Yes
B. No
Answer: B
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