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.

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 4 of 9

Explore more Topics under Artificial Intelligence

01

Introduction to AI

02

Intelligent Agents

03

Problem Solving

04

Game Planning

05

Knowledge and Reasoning

06

Uncertain Knowledge

07

Perceiving and Acting

08

Natural Language Processing

09

LISP Programming

10

Expert Systems

Q31.

The output at each node is called_____.

node value

Weight

neurons

axons

Discuss

Answer: (a).node value

Q32.

What is full form of ANNs?

Artificial Neural Node

AI Neural Networks

Artificial Neural Networks

Artificial Neural numbers

Discuss

Answer: (c).Artificial Neural Networks

Q33.

In FeedForward ANN, information flow is _________.

unidirectional

bidirectional

multidirectional

All of the above

Discuss

Answer: (a).unidirectional

Q34.

Which of the following is not an Machine Learning strategies in ANNs?

Unsupervised Learning

Reinforcement Learning

Supreme Learning

Supervised Learning

Discuss

Answer: (c).Supreme Learning

Q35.

Which of the following is an Applications of Neural Networks?

Automotive

Aerospace

Electronics

All of the above

Discuss

Answer: (d).All of the above

Q36.

What is perceptron?

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

an auto-associative neural network

a double layer auto-associative neural network

a neural network that contains feedback

Discuss

Answer: (a).a single layer feed-forward neural network with pre-processing

Q37.

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, 3, 2 and 1 respectively. What will be the output?

Discuss

Answer: (b).40

Q38.

What is back propagation?

It is another name given to the curvy function in the perceptron

It is the transmission of error back through the network to adjust the inputs

It is the transmission of error back through the network to allow weights to be adjusted so that the network can learn

None of the Above

Discuss

Answer: (c).It is the transmission of error back through the network to allow weights to be adjusted so that the network can learn

Q39.

The network that involves backward links from output to the input and hidden layers is called _________

Self organizing map

Perceptrons

Recurrent neural network

Multi layered perceptron

Discuss

Answer: (c).Recurrent neural network

Q40.

The BN variables are composed of how many dimensions?

Discuss

Answer: (b).3

Page 4 of 9

Welcome to the Learning MCQs Page

Learning MCQs | Page 4 of 9

Explore more Topics under Artificial Intelligence

Introduction to AI

Intelligent Agents

Problem Solving

Game Planning

Knowledge and Reasoning

Uncertain Knowledge

Perceiving and Acting

Natural Language Processing

LISP Programming

Expert Systems

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