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

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
by

1 Answer

Answer :

A. Supervised learning 
by

Related questions

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 

Automated vehicle is an example of ______ a) Supervised learning b) Unsupervised learning c) Active learning d) Reinforcement learning

Description : Automated vehicle is an example of ______ a) Supervised learning b) Unsupervised learning c) Active learning d) Reinforcement learning

Last Answer : a) Supervised learning

Automated vehicle is an example of ______. a) Supervised learning b) Unsupervised learning c) Active learning d) Reinforcement learning

Description : Automated vehicle is an example of ______. a) Supervised learning b) Unsupervised learning c) Active learning d) Reinforcement learning

Last Answer : a) Supervised learning

Which of the following is also called as exploratory learning? a) Supervised learning b) Active learning c) Unsupervised learning d) Reinforcement learning

Description : Which of the following is also called as exploratory learning? a) Supervised learning b) Active learning c) Unsupervised learning d) Reinforcement learning

Last Answer : c) Unsupervised learning

In which of the following learning the teacher returns reward and punishment to learner? a) Active learning b) Reinforcement learning c) Supervised learning d) Unsupervised learning

Description : In which of the following learning the teacher returns reward and punishment to learner? a) Active learning b) Reinforcement learning c) Supervised learning d) Unsupervised learning

Last Answer : b) Reinforcement learning

What are the 2 types of learning A. Improvised and unimprovised B. supervised and unsupervised C. Layered and unlayered D. None of the above

Description : What are the 2 types of learning A. Improvised and unimprovised B. supervised and unsupervised C. Layered and unlayered D. None of the above

Last Answer : B. supervised and unsupervised

Following is also called as exploratory learning: a) Supervised learning b) Active learning c) Unsupervised learning d) Reinforcement learning

Description : Following is also called as exploratory learning: a) Supervised learning b) Active learning c) Unsupervised learning d) Reinforcement learning

Last Answer : c) Unsupervised learning

In which of the following learning the teacher returns reward and punishment to learner? a) Active learning b) Reinforcement learning c) Supervised learning d) Unsupervised learning

Description : In which of the following learning the teacher returns reward and punishment to learner? a) Active learning b) Reinforcement learning c) Supervised learning d) Unsupervised learning

Last Answer : b) Reinforcement learning

Differentiate Supervised and Unsupervised learning.

Description : Differentiate Supervised and Unsupervised learning.

Last Answer : Supervised Learning Unsupervised Learning It involves learning a function From examples of its inputs And outputs It involves learning patterns in the input when no specific output values are ... will learn about Good traffic days and Bad traffic days without any advice.

Computational learning theory analyzes the sample complexity and computational complexity of __________ a) Unsupervised Learning b) Inductive learning c) Forced based learning d) Weak learning

Description : Computational learning theory analyzes the sample complexity and computational complexity of __________ a) Unsupervised Learning b) Inductive learning c) Forced based learning d) Weak learning

Last Answer : b) Inductive learning

Unsupervised learning is A. learning without computers B. problem based learning C. learning from environment D. learning from teachers

Description : Unsupervised learning is A. learning without computers B. problem based learning C. learning from environment D. learning from teachers

Last Answer : C. learning from environment

Computational learning theory analyzes the sample complexity and computational complexity of a) Unsupervised Learning b) Inductive learning c) Forced based learning d) Weak learning e) Knowledge based learning

Description : Computational learning theory analyzes the sample complexity and computational complexity of a) Unsupervised Learning b) Inductive learning c) Forced based learning d) Weak learning e) Knowledge based learning

Last Answer : b) Inductive learning

What is Supervised, unsupervised and reinforcement learning ? -AI Class 9th

Description : What is Supervised, unsupervised and reinforcement learning ? -AI Class 9th

Last Answer : Meaning of Supervised vs Unsupervised Learning vs Reinforcement Learning Supervised Learning Consider yourself as a student sitting in a classroom wherein your teacher is supervising you, ... Evaluation, Forecast Sales Recommendation System, Anomaly Detection Self Driving Cars, Gaming, Healthcare

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

Description : 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

Last Answer : B. Artificial neural networks 

. In an Unsupervised learning ____________ a) Specific output values are given b) Specific output values are not given c) No specific Inputs are given d) Both inputs and outputs are given

Description : . In an Unsupervised learning ____________ a) Specific output values are given b) Specific output values are not given c) No specific Inputs are given d) Both inputs and outputs are given

Last Answer : b) Specific output values are not given

In an Unsupervised learning a) Specific output values are given b) Specific output values are not given c) No specific Inputs are given d) Both inputs and outputs are given e) Neither inputs nor outputs are given

Description : In an Unsupervised learning a) Specific output values are given b) Specific output values are not given c) No specific Inputs are given d) Both inputs and outputs are given e) Neither inputs nor outputs are given

Last Answer : b) Specific output values are not given

In supervised learning A. classes are not predefined B. classes are predefined C. classes are not required

Description : In supervised learning A. classes are not predefined B. classes are predefined C. classes are not required

Last Answer : B. classes are predefined

Supervised Learning is A. learning with the help of examples B. learning without teacher C. learning with the help of teacher D. learning with computers as supervisor

Description : Supervised Learning is A. learning with the help of examples B. learning without teacher C. learning with the help of teacher D. learning with computers as supervisor

Last Answer : C. learning with the help of teacher

Feature of ANN in which ANN creates its own organization or representation of information it receives during learning time is A. Adaptive Learning B. Self Organization C. What-If Analysis D. Supervised Learniing

Description : Feature of ANN in which ANN creates its own organization or representation of information it receives during learning time is A. Adaptive Learning B. Self Organization C. What-If Analysis D. Supervised Learniing

Last Answer : B. Self Organization

______________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 

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 

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.

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 

Which of the following is not an application of learning? a) Data mining b) WWW c) Speech recognition d) None of the mentioned

Description : Which of the following is not an application of learning? a) Data mining b) WWW c) Speech recognition d) None of the mentioned

Last Answer : d) None of the mentioned

Machine learning invent by _____. A. John McCarthy B. Nicklaus Wirth C. Joseph Weizenbaum D. Arthur Samuel

Description : Machine learning invent by _____. A. John McCarthy B. Nicklaus Wirth C. Joseph Weizenbaum D. Arthur Samuel

Last Answer : D. Arthur Samuel 

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

IBM’s deep blue system is example of ___. A. Reactive machine B. Limited memory C. Theory of mind D. None of above

Description : IBM’s deep blue system is example of ___. A. Reactive machine B. Limited memory C. Theory of mind D. None of above 

Last Answer : A. Reactive machine 

Which of the following is an example of active learning? a) News Recommender system b) Dust cleaning machine c) Automated vehicle d) None of the mentioned

Description : Which of the following is an example of active learning? a) News Recommender system b) Dust cleaning machine c) Automated vehicle d) None of the mentioned

Last Answer : a) News Recommender system

Following is an example of active learning: a) News Recommender system b) Dust cleaning machine c) Automated vehicle d) None of the mentioned

Description : Following is an example of active learning: a) News Recommender system b) Dust cleaning machine c) Automated vehicle d) None of the mentioned

Last Answer : a) News Recommender system

The Face Recognition system is based on? a) Strong Artificial Intelligence approach b) Weak Artificial Intelligence approach c) Cognitive Artificial Intelligence approach d) Applied Artificial Intelligence approach

Description : The Face Recognition system 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 : d) Applied Artificial Intelligence approach

Playing chess, purchasing suggestions on e-commerce site, self-driving cars, speech recognition, and image recognition are the example of ____. A. Narrow AI B. General AI C. Super AI D. None of above

Description : Playing chess, purchasing suggestions on e-commerce site, self-driving cars, speech recognition, and image recognition are the example of ____. A. Narrow AI B. General AI C. Super AI D. None of above

Last Answer : A. Narrow AI 

The computer's capability of distinguishing spoken words is called _____: a) voice analysis b) speech acknowledgement c) voice recognition d) speech interpretation e) vocalization

Description : The computer's capability of distinguishing spoken words is called _____: a) voice analysis b) speech acknowledgement c) voice recognition d) speech interpretation e) vocalization

Last Answer : c) voice recognition

Compare and contrast Rule based learning , Machine Learning, Deep Learning. -AI Class 9th

Description : Compare and contrast Rule based learning , Machine Learning, Deep Learning. -AI Class 9th

Last Answer : Rule based learning Deep Learning Machine Learning Rules-based systems are a simple kind of artificial intelligence, which uses a series of simple IF-THEN-ELSE statements that guide a computer ... to utilize machine learning models Pure coding processing Pace of change Simple guidelines don't apply

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

How many types are available in machine learning? a) 1 b) 2 c) 3 d) 4

Description : How many types are available in machine learning? a) 1 b) 2 c) 3 d) 4

Last Answer : c) 3

What is Machine learning? a) The autonomous acquisition of knowledge through the use of computer programs b) The autonomous acquisition of knowledge through the use of manual programs c) The selective acquisition of knowledge through the use of computer programs d) The selective acquisition of knowledge through the use of manual programs

Description : What is Machine learning? a) The autonomous acquisition of knowledge through the use of computer programs b) The autonomous acquisition of knowledge through the use of manual programs c) The ... use of computer programs d) The selective acquisition of knowledge through the use of manual programs

Last Answer : a) The autonomous acquisition of knowledge through the use of computer programs

Transparency A . The large set of candidate solutions possible for a problem B. The information stored in a database that can be retrieved with a single query C. Worth of the output of a machine learning program that makes it understandable for humans D . None of these

Description : Transparency A . The large set of candidate solutions possible for a problem B. The information stored in a database that can be retrieved with a single query C. Worth of the output of a machine learning program that makes it understandable for humans D . None of these

Last Answer : C. Worth of the output of a machine learning program that makes it understandable for humans

Shallow knowledge A . The large set of candidate solutions possible for a problem B. The information stored in a database that can be, retrieved with a single query C. Worth of the output of a machine learning program that makes it understandable for humans D . None of these

Description : Shallow knowledge A . The large set of candidate solutions possible for a problem B. The information stored in a database that can be, retrieved with a single query C. Worth of the output of a machine learning program that makes it understandable for humans D . None of these

Last Answer : B. The information stored in a database that can be, retrieved with a single query

Search space A . The large set of candidate solutions possible for a problem B. The information stored in a database that can be, retrieved with a single query. C. Worth of the output of a machine learning program that makes it understandable for humans D . None of these

Description : Search space A . The large set of candidate solutions possible for a problem B. The information stored in a database that can be, retrieved with a single query. C. Worth of the output of a machine learning program that makes it understandable for humans D . None of these

Last Answer : A . The large set of candidate solutions possible for a problem

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

How many types are available in machine learning? a) 1 b) 2 c) 3 d) 4

Description : How many types are available in machine learning? a) 1 b) 2 c) 3 d) 4

Last Answer : c) 3

What are the types of machine learning?

Description : What are the types of machine learning?

Last Answer : i. Supervised Learning  ii. Unsupervised Learning  iii. Reinforcement Learning

What is Machine learning? A. The autonomous acquisition of knowledge through the use of computer programs B. The autonomous acquisition of knowledge through the use of manual programs C. The selective acquisition of knowledge through the use of computer programs D. The selective acquisition of knowledge through the use of manual programs

Description : What is Machine learning? A. The autonomous acquisition of knowledge through the use of computer programs B. The autonomous acquisition of knowledge through the use of manual programs C. The ... use of computer programs D. The selective acquisition of knowledge through the use of manual programs

Last Answer : A. The autonomous acquisition of knowledge through the use of computer programs 

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 

8-Unsolicited email is also known as _____. Choose one of the following to complete the sentence: Exhibit: Mark one answer: Junk Bulk Trash Spam

Description : 8-Unsolicited email is also known as _____. Choose one of the following to complete the sentence: Exhibit: Mark one answer: Junk Bulk Trash Spam

Last Answer : Spam

Which agent deals with happy and unhappy states? a) Simple reflex agent b) Model based agent c) Learning agent d) Utility based agent

Description : Which agent deals with happy and unhappy states? a) Simple reflex agent b) Model based agent c) Learning agent d) Utility based agent

Last Answer : d) Utility based agent

Ability to learn how to do tasks based on the data given for training or initial experience A. Self Organization B. Adaptive Learning C. Fault tolerance D. Robustness

Description : Ability to learn how to do tasks based on the data given for training or initial experience A. Self Organization B. Adaptive Learning C. Fault tolerance D. Robustness

Last Answer : B. Adaptive Learning

Define knowledge based Inductive learning.

Description : Define knowledge based Inductive learning.

Last Answer : KBIL algorithm finds inductive hypotheses that explain sets of observations with the help of background knowledge.

Which of the following neural networks uses supervised learning? (A) Multilayer perceptron (B) Self organizing feature map (C) Hopfield network (1) (A) only (2) (B) only (3) (A) and (B) only (4) (A) and (C) only

Description : Which of the following neural networks uses supervised learning? (A) Multilayer perceptron (B) Self organizing feature map (C) Hopfield network (1) (A) only (2) (B) only (3) (A) and (B) only (4) (A) and (C) only

Last Answer : (1) (A) only

The Hadoop list includes the HBase database, the Apache Mahout ________ system, and matrix operations. a) Machine learning b) Pattern recognition c) Statistical classification d) Artificial intelligence

Description : The Hadoop list includes the HBase database, the Apache Mahout ________ system, and matrix operations. a) Machine learning b) Pattern recognition c) Statistical classification d) Artificial intelligence

Last Answer : Machine learning