IGNOU MCS 224 Exam Notes / Important Question

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IGNOU MCS 224 Exam Notes / Important Question

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S.NOSome Questions
1(a) Compare Narrow AI, General AI and Super AI. Give suitable example for each.
(b) Briefly discuss the formulation of state space search, with a suitable example.
2(a) What do you understand by the term “Agents” in Artificial Intelligence ? List the properties, supposed to be possessed by agents. Also, compare the SR (simple reflex) agents with model based reflex agents.
(b) Draw the block diagram of machine learning cycle and briefly discuss the role of each of its components.
3(a) What is Adversarial Search ? How it is different from the normal search ? Briefly discuss the types of adversarial search.
(b) Differentiate between the following, with an example for each :
(i) Machine learning and Data mining
(ii) Multi-class classification and Multilabel classification
4(a) What is Best First Search ? How is it different from greedy best first search ? Give time complexity and space complexity of best first search. Also, give advantage and disadvantage of best first search.
5(b) How regression differs from classification ? What is the similarity between the two ? Briefly discuss the following type of regression :-
(i) Linear regression
(ii) Multiple linear regression
(iii) Logistic regression
(iv) Polynomial regression
6Differentiate between Artificial Intelligence, Machine Learning and Deep learning
7Briefly discuss the concept of single agent search and two agent search in Artificial Intelligence.
8Explain A* and AO* search with the help of suitable example.
9Compare and contrast the predicate logic and propositional logic, give suitable example for each. Also write De Morgan’s laws for both.
10Discuss the concept of Resolution with the help of suitable example
S.NOSome Questions
11Explain the concept of semantic nets with the help of suitable diagram.
12What do you understand by Bayesian Theory, with reference to its utility in artificial intelligence?
13What are Fuzzy sets? How do they differ from Rough sets?
14Differentiate between Supervised learning and Unsupervised learning, give suitable example for each
15Discuss the concept of Linear regression and its utility in context of machine learning.
16Explain the functioning of neural networks, with the help of suitable diagram.
17Give brief introduction to the concept of feature selection and feature extraction, give suitable example for each.
18What is pattern search? Discuss the Apriori Algorithm for pattern search
19What do you understand by clustering in context of machine learning? How it differs from classification? List the algorithms used for the purpose of clustering and classification, separately.
20Write Python code to exhibit data classification through K-Nearest Neighbour (K-NN) algorithm.
S.NOShort Questions
1(a) Rule based systems and its types
(b) Frames
2(c) Dempster Scheffer theory
(d) Closed world assumption
3(e) Recursive neural networks
(f) Generative adversarial networks
4(g) Support vector machines
(h) Confusion matrix
5(i) Linear discriminant analysis
(j) Pincer search
6a) Reinforcement Learning
b) Ensemble method

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