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NEW QUESTION: 1
Refer to the exhibit.

What is the next hop address for traffic that is destined to host 10.0.1.5?
A. 10.0.1.4
B. 10.0.1.3
C. 10.0.1.50
D. Loopback D
Answer: C

NEW QUESTION: 2
How does a customer open a support tunnel?
A. Click on System Administration > Support Access, and then Edit Support Access
B. In the CLI type support, remote_access and then configure the access password.
C. Click on Network > Interfaces > Data 1, and click Enable Support access Settings
D. Click on Help Support > Remote Access and then Edit Remote Access Settings
Answer: D

NEW QUESTION: 3
Match the types of machine learning to the appropriate scenarios.
To answer, drag the appropriate machine learning type from the column on the left to its scenario on the right.
Each machine learning type may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation
Box 1: Regression
In the most basic sense, regression refers to prediction of a numeric target.
Linear regression attempts to establish a linear relationship between one or more independent variables and a numeric outcome, or dependent variable.
You use this module to define a linear regression method, and then train a model using a labeled dataset. The trained model can then be used to make predictions.
Box 2: Classification
Classification is a machine learning method that uses data to determine the category, type, or class of an item or row of data.
Box 3: Clustering
Clustering, in machine learning, is a method of grouping data points into similar clusters. It is also called segmentation.
Over the years, many clustering algorithms have been developed. Almost all clustering algorithms use the features of individual items to find similar items. For example, you might apply clustering to find similar people by demographics. You might use clustering with text analysis to group sentences with similar topics or sentiment.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/linear-regression

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