Description : How many things are concerned in the design of a learning element? a) 1 b) 2 c) 3 d) 4
Last Answer : c) 3
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
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.
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
Description : Which is used to choose among multiple consistent hypotheses? a) Razor b) Ockham razor c) Learning element d) None of the mentioned
Last Answer : b) Ockham razor
Description : Which modifies the performance element so that it makes better decision? a) Performance element b) Changing element c) Learning element d) None of the mentioned
Last Answer : c) Learning element
Description : Which is used to provide the feedback to the learning element? a) Critic b) Actuators c) Sensor d) None of the mentioned
Last Answer : a) Critic
Description : Which element in the agent are used for selecting external actions? a) Perceive b) Performance c) Learning d) Actuator
Last Answer : b) Performance
Description : What are issues in learning element?
Last Answer : i. Component ii. Feedback iii. Representation
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
Description : NLP is concerned with the interactions between computers and human (natural) languages. a) True b) False
Last Answer : a) True
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
Description : Modern NLP algorithms are based on machine learning, especially statistical machine learning. a) True b) False
Description : How many literals are available in top-down inductive learning methods? a) 1 b) 2 c) 3 d) 4
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
Description : Inductive learning involves finding a __________ a) Consistent Hypothesis b) Inconsistent Hypothesis c) Regular Hypothesis d) Irregular Hypothesis
Last Answer : a) Consistent Hypothesis
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
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
Description : Which of the following is the component of learning system? a) Goal b) Model c) Learning rules d) All of the mentioned
Last Answer : d) All of the mentioned
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
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
Description : Automated vehicle is an example of ______ a) Supervised learning b) Unsupervised learning c) Active learning d) Reinforcement learning
Last Answer : a) Supervised learning
Description : Which of the following does not include different learning methods? a) Memorization b) Analogy c) Deduction d) Introduction
Last Answer : d) Introduction
Description : How many types are available in machine learning? a) 1 b) 2 c) 3 d) 4
Description : What is used in determining the nature of the learning problem? a) Environment b) Feedback c) Problem d) All of the mentioned
Last Answer : b) Feedback
Description : What will take place as the agent observes its interactions with the world? a) Learning b) Hearing c) Perceiving d) Speech
Last Answer : a) Learning
Description : Which is the only way to learn about the different kinds of human faces? a) Perception b) Speech c) Learning d) Hearing
Last Answer : c) Learning
Description : Which method is used to search better by learning? a) Best-first search b) Depth-first search c) Metalevel state space d) None of the mentioned
Last Answer : c) Metalevel state space
Description : What kind of observing environments are present in artificial intelligence? a) Partial b) Fully c) Learning d) Both Partial & Fully
Last Answer : d) Both Partial & Fully
Description : What can operate over the joint state space? a) Decision-making algorithm b) Learning algorithm c) Complex algorithm d) Both Decision-making & Learning algorithm
Last Answer : d) Both Decision-making & Learning algorithm
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
Description : Which is used to improve the agents performance? a) Perceiving b) Learning c) Observing d) None of the mentioned
Last Answer : b) Learning
Description : In which agent does the problem generator is present? a) Learning agent b) Observing agent c) Reflex agent d) None of the mentioned
Last Answer : a) Learning agent
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
Description : Shaping teaching techniques to fit the learning patterns of individual students is the goal of __________ a) decision support b) automatic programming c) intelligent computer-assisted instruction d) expert systems
Last Answer : c) intelligent computer-assisted instruction
Description : The action of the Simple reflex agent completely depends upon __________ a) Perception history b) Current perception c) Learning theory d) Utility functions
Last Answer : b) Current perception
Description : External actions of the agent is selected by __________ a) Perceive b) Performance c) Learning d) Actuator
Description : The performance of an agent can be improved by __________ a) Learning b) Observing c) Perceiving d) None of the mentioned
Description : Generality is the measure of _____________ a) Ease with which the method can be adapted to different domains of application b) The average time required to construct the target knowledge structures ... unreliable feedback and with a variety of training examples d) The overall power of the system
Last Answer : a) Ease with which the method can be adapted to different domains of application
Description : Membership function can be thought of as a technique to solve empirical problems on the basis of A. knowledge B. examples C. learning D. experience
Last Answer : D. experience
Description : In supervised learning A. classes are not predefined B. classes are predefined C. classes are not required
Last Answer : B. classes are predefined
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
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
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
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
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
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
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