Deep learning is a subfield of machine learning where concerned algorithms are inspired by the structured and function of the brain called _____. A. Machine learning B. Artificial neural networks C. Deep learning D. Robotics

Deep learning is a subfield of machine learning where concerned algorithms are inspired by the structured and function of the brain called _____. A. Machine learning B. Artificial neural networks C. Deep learning D. Robotics
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B. Artificial neural networks 
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Computer programs that mimic the way the human brain processes information is called as A. Machine Learning B. Deep Learning C. Neural Networks D. None of these

Description : Computer programs that mimic the way the human brain processes information is called as A. Machine Learning B. Deep Learning C. Neural Networks D. None of these

Last Answer : The correct answer is: C. Neural Networks Neural Networks are computer programs or models that are designed to mimic the way the human brain processes information. They are a subset of ... advanced form of neural networks that uses multiple layers of artificial neurons to perform complex tasks.

Core of soft Computing is A. Fuzzy Computing, Neural Computing, Genetic Algorithms B. Fuzzy Networks and Artificial Intelligence C. Artificial Intelligence and Neural Science D. Neural Science and Genetic Science

Description : Core of soft Computing is A. Fuzzy Computing, Neural Computing, Genetic Algorithms B. Fuzzy Networks and Artificial Intelligence C. Artificial Intelligence and Neural Science D. Neural Science and Genetic Science

Last Answer : D. Neural Science and Genetic Science

______________is a branch of science that deals with programing the systems in such a way that they automatically learn and improve with experience A. Machine Learning B. Deep Learning C. Neural Networks D. None of these

Description : ______________is a branch of science that deals with programing the systems in such a way that they automatically learn and improve with experience A. Machine Learning B. Deep Learning C. Neural Networks D. None of these

Last Answer : A. Machine Learning 

In ____ the goal is for the software to use what it has learned in one area to solve problems in other areas. A. Machine Learning B. Deep Learning C. Neural Networks D. None of these

Description : In ____ the goal is for the software to use what it has learned in one area to solve problems in other areas. A. Machine Learning B. Deep Learning C. Neural Networks D. None of these

Last Answer : B. Deep Learning 

Computer programs that mimic the way the human brain processes information is called as:- a) Machine learning b) Deep learning c)Neural networks d) None of the above

Description : Computer programs that mimic the way the human brain processes information is called as:- a) Machine learning b) Deep learning c)Neural networks d) None of the above

Last Answer : c)Neural networks

Evolutionary computation is A . Combining different types of method or information B. Approach to the design of learning algorithms that is structured along the lines of the theory of evolution. C. Decision support systems that contain an information base filled with the knowledge of an expert formulated in terms of if-then rules. D . None of these

Description : Evolutionary computation is A . Combining different types of method or information B. Approach to the design of learning algorithms that is structured along the lines of the theory of evolution. C. ... the knowledge of an expert formulated in terms of if-then rules. D . None of these

Last Answer : B. Approach to the design of learning algorithms that is structured along the lines of the theory of evolution.

Expert systems A . Combining different types of method or information B. Approach to the design of learning algorithms that is structured along the lines of the theory of evolution C. an information base filled with the knowledge of an expert formulated in terms of if-then rules D . None of these

Description : Expert systems A . Combining different types of method or information B. Approach to the design of learning algorithms that is structured along the lines of the theory of evolution C. an information base ... the knowledge of an expert formulated in terms of if-then rules D . None of these

Last Answer : C. an information base filled with the knowledge of an expert formulated in terms of if-then rules

This set of Artificial Intelligence MCQs focuses on “Neural Networks – 2”. 1. Why is the XOR problem exceptionally interesting to neural network researchers? a) Because it can be expressed in a way that allows you to use a neural network b) Because it is complex binary operation that cannot be solved using neural networks c) Because it can be solved by a single layer perceptron d) Because it is the simplest linearly inseparable problem that exists.

Description : This set of Artificial Intelligence MCQs focuses on Neural Networks - 2 . 1. Why is the XOR problem exceptionally interesting to neural network researchers? a) Because it can be expressed in ... by a single layer perceptron d) Because it is the simplest linearly inseparable problem that exists.

Last Answer : d) Because it is the simplest linearly inseparable problem that exists.

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 b) (ii) is true c) (i) and (ii) are true d) None of the mentioned

Description : 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 ... b) (ii) is true c) (i) and (ii) are true d) None of the mentioned

Last Answer : c) (i) and (ii) are true

Which of the following is the model used for learning? a) Decision trees b) Neural networks c) Propositional and FOL rules d) All of the mentioned

Description : Which of the following is the model used for learning? a) Decision trees b) Neural networks c) Propositional and FOL rules d) All of the mentioned

Last Answer : d) All of the mentioned

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

Description : 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. ... ) are true c) (i), (ii) and (iii) are true d) None of the mentioned

Last Answer : a) All of the mentioned are true

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

Description : 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 ... ) are true c) (i), (ii) and (iii) are true d) None of the mentioned

Last Answer : a) All of the mentioned are true

PROLOG, LISP, NLP are the language of ____ A. Artificial Intelligence B. Machine Learning C. Internet of Things D. Deep Learning

Description : PROLOG, LISP, NLP are the language of ____ A. Artificial Intelligence B. Machine Learning C. Internet of Things D. Deep Learning

Last Answer : A. Artificial Intelligence 

the consist of computer program that mimic the way the human brain process information. (a) Machine learning (b) Deep learning (c) Neural learning (d) All of this

Description : the consist of computer program that mimic the way the human brain process information. (a) Machine learning (b) Deep learning (c) Neural learning (d) All of this

Last Answer : (c) Neural learning

Modern NLP algorithms are based on machine learning, especially statistical machine learning. a) True b) False

Description : Modern NLP algorithms are based on machine learning, especially statistical machine learning. a) True b) False

Last Answer : a) True

K-means, self-organizing maps, hierarchical clustering are the example of _____. A. Supervised learning B. Unsupervised learning C. Machine learning D. Deep learning

Description : K-means, self-organizing maps, hierarchical clustering are the example of _____. A. Supervised learning B. Unsupervised learning C. Machine learning D. Deep learning

Last Answer : B. Unsupervised learning 

Classifying email as a spam, labeling webpages based on their content, voice recognition are the example of _____. A. Supervised learning B. Unsupervised learning C. Machine learning D. Deep learning

Description : Classifying email as a spam, labeling webpages based on their content, voice recognition are the example of _____. A. Supervised learning B. Unsupervised learning C. Machine learning D. Deep learning

Last Answer : A. Supervised learning 

Neurons or artificial neurons have the capability to model networks of original neurons as found in brain A. True B. False

Description : Neurons or artificial neurons have the capability to model networks of original neurons as found in brain A. True B. False

Last Answer : A. True

A _________ is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. a) Decision tree b) Graphs c) Trees d) Neural Networks

Description : A _________ is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. a) Decision tree b) Graphs c) Trees d) Neural Networks

Last Answer : a) Decision tree

Neural Networks are complex ______________ with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions

Description : Neural Networks are complex ______________ with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions

Last Answer : a) Linear Functions

Why is the XOR problem exceptionally interesting to neural network researchers? a) Because it can be expressed in a way that allows you to use a neural network b) Because it is complex binary operation that cannot be solved using neural networks c) Because it can be solved by a single layer perceptron d) Because it is the simplest linearly inseparable problem that exists.

Description : Why is the XOR problem exceptionally interesting to neural network researchers? a) Because it can be expressed in a way that allows you to use a neural network b) Because it is complex ... solved by a single layer perceptron d) Because it is the simplest linearly inseparable problem that exists.

Last Answer : d) Because it is the simplest linearly inseparable problem that exists.

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

Description : 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

Last Answer : d) All of the mentioned

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

Description : 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 ... ) are true b) (ii) is true c) All of the mentioned d) None of the mentioned

Last Answer : a) (ii) and (iii) are true

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 of the mentioned

Description : 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 ... true b) (i) and (iii) are true c) Only (i) d) All of the mentioned

Last Answer : d) All of the mentioned

Neural Networks are complex ______________with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions

Description : Neural Networks are complex ______________with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions

Last Answer : b) Nonlinear Functions

Perceptron is A. General class of approaches to a problem. B. Performing several computations simultaneously C. Structures in a database those are statistically relevant D. Simple forerunner of modern neural networks, without hidden layers

Description : Perceptron is A. General class of approaches to a problem. B. Performing several computations simultaneously C. Structures in a database those are statistically relevant D. Simple forerunner of modern neural networks, without hidden layers

Last Answer : D. Simple forerunner of modern neural networks, without hidden layers

Neural Networks are complex ———————–with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions e) Power Functions

Description : Neural Networks are complex ———————–with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions e) Power Functions

Last Answer : b) Nonlinear Functions

Neural Networks are complex ______________ with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions

Description : Neural Networks are complex ______________ with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions

Last Answer : a) Linear Functions

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

Description : 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

Last Answer : d) All of the mentioned

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

Description : 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 ... ) are true b) (ii) is true c) All of the mentioned d) None of the mentioned

Last Answer : a) (ii) and (iii) are true

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 of the mentioned

Description : 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 ... true b) (i) and (iii) are true c) Only (i) d) All of the mentioned

Last Answer : d) All of the mentioned

What is multilayer feed forward neural networks?

Description : What is multilayer feed forward neural networks?

Last Answer : It consists of many hidden units. Each hidden unit act as a perceptron that represents a soft threshold functions in the input space. Output unit act as a soft threshold linear combination of several such functions.

What are the two functions in Neural network’s Activation functions?

Description : What are the two functions in Neural network’s Activation functions? 

Last Answer : i. Threshold function  ii. Sigmoid function

Define Neural Networks.

Description : Define Neural Networks.

Last Answer : It consists of nodes or units connected by directed links. A link propagates the activation. Each link has a numeric weight which determines the strength and sign of the connection.

Artificial Intelligence has its expansion in the following application. a. Planning and Scheduling b. Game Playing c. Robotics d. All of the above

Description : Artificial Intelligence has its expansion in the following application. a. Planning and Scheduling b. Game Playing c. Robotics d. All of the above

Last Answer : d. All of the above

Artificial Intelligence has its expansion in the following application. A. Planning and Scheduling B. Game Playing C. Robotics D. All of the above

Description : Artificial Intelligence has its expansion in the following application. A. Planning and Scheduling B. Game Playing C. Robotics D. All of the above

Last Answer : D. All of the above 

In artificial Neural Network interconnected processing elements are called A. nodes or neurons B. weights C. axons D. Soma

Description : In artificial Neural Network interconnected processing elements are called A. nodes or neurons B. weights C. axons D. Soma

Last Answer : A. nodes or neurons

The characteristics of the computer system capable of thinking, reasoning and learning are known as ____________ a) machine intelligence b) human intelligence c) artificial intelligence d) virtual intelligence

Description : The characteristics of the computer system capable of thinking, reasoning and learning are known as ____________ a) machine intelligence b) human intelligence c) artificial intelligence d) virtual intelligence

Last Answer : c) artificial intelligence

Artificial intelligence is A . It uses machine-learning techniques. Here program can learn From past experience and adapt themselves to new situations B. Computational procedure that takes some value as input and produces some value as output. C. Science of making machines performs tasks that would require intelligence when performed by humans D . None of these

Description : Artificial intelligence is A . It uses machine-learning techniques. Here program can learn From past experience and adapt themselves to new situations B. Computational procedure that takes some ... performs tasks that would require intelligence when performed by humans D . None of these

Last Answer : C. Science of making machines performs tasks that would require intelligence when performed by humans

The characteristics of the computer system capable of thinking, reasoning and learning is known is A. machine intelligence B. human intelligence C. artificial intelligence D. virtual intelligence

Description : The characteristics of the computer system capable of thinking, reasoning and learning is known is A. machine intelligence B. human intelligence C. artificial intelligence D. virtual intelligence

Last Answer : C. artificial intelligence 

Which of the following is not the promise of artificial neural network? a) It can explain result b) It can survive the failure of some nodes c) It has inherent parallelism d) It can handle noise

Description : Which of the following is not the promise of artificial neural network? a) It can explain result b) It can survive the failure of some nodes c) It has inherent parallelism d) It can handle noise

Last Answer : a) It can explain result

An Artificial Neural Network Is based on? a) Strong Artificial Intelligence approach b) Weak Artificial Intelligence approach c) Cognitive Artificial Intelligence approach d) Applied Artificial Intelligence approach

Description : An Artificial Neural Network Is based on? a) Strong Artificial Intelligence approach b) Weak Artificial Intelligence approach c) Cognitive Artificial Intelligence approach d) Applied Artificial Intelligence approach

Last Answer : c) Cognitive Artificial Intelligence approach

Artificial neural network used for A. Pattern Recognition B. Classification C. Clustering D. All of these

Description : Artificial neural network used for A. Pattern Recognition B. Classification C. Clustering D. All of these

Last Answer : D. All of these

Which of the following is not the promise of artificial neural network? a) It can explain result b) It can survive the failure of some nodes c) It has inherent parallelism d) It can handle noise

Description : Which of the following is not the promise of artificial neural network? a) It can explain result b) It can survive the failure of some nodes c) It has inherent parallelism d) It can handle noise

Last Answer : a) It can explain result

The given illustrative diagram is related to which topic? a) Machine Learning b) Neural Network Processing c) Reasoning d) Deep learning

Description : The given illustrative diagram is related to which topic? a) Machine Learning b) Neural Network Processing c) Reasoning d) Deep learning

Last Answer : a) Machine Learning

he given illustrative diagram is related to which topic? a) Machine Learning b) Neural Network Processing c) Reasoning d) Deep learning

Description : he given illustrative diagram is related to which topic? a) Machine Learning b) Neural Network Processing c) Reasoning d) Deep learning

Last Answer : Machine Learning

Is branch of science that deals with programming the system in such that they automatically learn with experience (a) Machine learning (b) Deep earning (c) Neural learning (d) All of above

Description : Is branch of science that deals with programming the system in such that they automatically learn with experience (a) Machine learning (b) Deep earning (c) Neural learning (d) All of above

Last Answer : (a) Machine learning

The goal is for the software to use what is it is was learned in one area to solve problem in other area. (a) Machine learning (b) Deep learning (c) Neural network (d) All of above

Description : The goal is for the software to use what is it is was learned in one area to solve problem in other area. (a) Machine learning (b) Deep learning (c) Neural network (d) All of above

Last Answer : (b) Deep learning

Neural Computing A. mimics human brain B. information processing paradigm C. Both (a) and (b) D. None of the above

Description : Neural Computing A. mimics human brain B. information processing paradigm C. Both (a) and (b) D. None of the above

Last Answer : C. Both (a) and (b)

_________ is a computational model based on the structure of biological neural networks? (A) Artificial Neural Network (ANN) (B) Biological Network (C) Both(A) & (B) (D) None of the Above

Description : _________ is a computational model based on the structure of biological neural networks? (A) Artificial Neural Network (ANN) (B) Biological Network (C) Both(A) & (B) (D) None of the Above

Last Answer : (A) Artificial Neural Network (ANN)