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NEW QUESTION: 1
Which of these are examples of a value in a sparse vector? (Select 2 answers.)
A. [0, 1]
B. [0, 5, 0, 0, 0, 0]
C. [0, 0, 0, 1, 0, 0, 1]
D. [1, 0, 0, 0, 0, 0, 0]
Answer: A,D
Explanation:
Explanation
Categorical features in linear models are typically translated into a sparse vector in which each possible value has a corresponding index or id. For example, if there are only three possible eye colors you can represent
'eye_color' as a length 3 vector: 'brown' would become [1, 0, 0], 'blue' would become [0, 1, 0] and 'green' would become [0, 0, 1]. These vectors are called "sparse" because they may be very long, with many zeros, when the set of possible values is very large (such as all English words).
[0, 0, 0, 1, 0, 0, 1] is not a sparse vector because it has two 1s in it. A sparse vector contains only a single 1.
[0, 5, 0, 0, 0, 0] is not a sparse vector because it has a 5 in it. Sparse vectors only contain 0s and 1s.
Reference: https://www.tensorflow.org/tutorials/linear#feature_columns_and_transformations

NEW QUESTION: 2
Which description of an SD-Access wireless network infrastructure deployment is true?
A. The access point is part of the fabric underlay.
B. The WLC is part of the fabric underaly.
C. The access point is part the fabirc overlay.
D. The wireless client is part of the fabirc overlay.
Answer: C

NEW QUESTION: 3
What is the investigator trying to view by issuing the command displayed in the following screenshot?
A. List of services stopped
B. List of services recently started
C. List of services closed recently
D. List of services installed
Answer: D