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Welcome to the Learning MCQs Page

Dive deep into the fascinating world of Learning with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Learning, a crucial aspect of Artificial Intelligence. In this section, you will encounter a diverse range of MCQs that cover various aspects of Learning, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within Artificial Intelligence.

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Check out the MCQs below to embark on an enriching journey through Learning. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Artificial Intelligence.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Learning. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Learning MCQs | Page 2 of 9

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Q11.
A perceptron is:

a.

a single layer feed-forward neural network with pre-processing

b.

an auto-associative neural network

c.

a double layer auto-associative neural network

d.

a neural network that contains feedback

Discuss
Answer: (a).a single layer feed-forward neural network with pre-processing
Q12.
An auto-associative network is:

a.

a neural network that contains no loops

b.

a neural network that contains feedback

c.

a neural network that has only one loop

d.

a single layer feed-forward neural network with pre-processing

Discuss
Answer: (b).a neural network that contains feedback
Q13.
Which of the following is true?
(i) On average, neural networks have higher computational rates than conventional computers.
(ii) Neural networks learn by example.
(iii) Neural networks mimic the way the human brain works.

a.

All of the mentioned are true

b.

(ii) and (iii) are true

c.

(i), (ii) and (iii) are true

d.

None of the mentioned

Discuss
Answer: (a).All of the mentioned are true
Q14.
A 4-input neuron has weights 1, 2, 3 and 4. The transfer function is linear with the constant of proportionality being equal to 2. The inputs are 4, 10, 5 and 20 respectively. The output will be:

a.

238

b.

76

c.

119

d.

123

Discuss
Answer: (a).238
Q15.
Which of the following is true for neural networks?
(i) The training time depends on the size of the network.
(ii) Neural networks can be simulated on a conventional computer.
(iii) Artificial neurons are identical in operation to biological ones.

a.

All of the mentioned are true

b.

(ii) is true

c.

(i) and (ii) are true

d.

None of the mentioned

Discuss
Answer: (c).(i) and (ii) are true
Q16.
What are the advantages of neural networks over conventional computers?
(i) They have the ability to learn by example
(ii) They are more fault tolerant
(iii)They are more suited for real time operation due to their high ‘computational’ rates

a.

(i) and (ii) are true

b.

(i) and (iii) are true

c.

Only (i)

d.

All are true

Discuss
Answer: (d).All are true
Q17.
Which of the following is true?
Single layer associative neural networks do not have the ability to:
(i) perform pattern recognition
(ii) find the parity of a picture
(iii)determine whether two or more shapes in a picture are connected or not

a.

(ii) and (iii) are true

b.

(ii) is true

c.

All of the mentioned

d.

None of the mentioned

Discuss
Answer: (a).(ii) and (iii) are true
Q18.
Which is true for neural networks?

a.

It has set of nodes and connections

b.

Each node computes it’s weighted input

c.

Node could be in excited state or non-excited state

d.

All of the mentioned

Discuss
Answer: (d).All of the mentioned
Q19.
Neuro software is:

a.

A software used to analyze neurons

b.

It is powerful and easy neural network

c.

Designed to aid experts in real world

d.

It is software used by Neuro surgeon

Discuss
Answer: (b).It is powerful and easy neural network
Q20.
Why are linearly separable problems of interest of neural network researchers?

a.

Because they are the only class of problem that network can solve successfully

b.

Because they are the only class of problem that Perceptron can solve successfully

c.

Because they are the only mathematical functions that are continue

d.

Because they are the only mathematical functions you can draw

Discuss
Answer: (b).Because they are the only class of problem that Perceptron can solve successfully
Page 2 of 9

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