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Master’s Degree Programme (MCA) – Artificial Intelligence and Machine Learning Solved Assignment Answer | MCS 224 | 2021-2022

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Free MCS 224 Solved Assignment Answer | Artificial Intelligence and Machine Learning | For July 2021 – October 2022

IGNOU MCS 224 Solved Assignment, This assignment is the curriculum of the Master of Computer Applications (MCA) program. For other courses, students check our website categories section to find their courses and assignments over there.

MCS 224 Artificial Intelligence and Machine Learning Solved Assignment 2021-2022

IGNOU MCS 224 Artificial Intelligence and Machine Learning assignment are 100 marks. There is only two sections – A & B. Students have to answer all the questions. Download IGNOU MCS 224 Assignment free without any registration, Students can easily download the IGNOU assignment question paper from the official website of the university. They are not required to pay any fees or charges for this.

Title NameMCS 224 Solved Assignment 2021-2022 | Artificial Intelligence and Machine Learning
UniversityIGNOU
Service TypeSolved Assignment (Soft Copy/Q&A form)
CourseMCA
LanguageEnglish
SemesterSession: July 2021 – January 2022
Short NameMCS 224
Assignment CodeMCS-224(III)/Asst/TMA/July2021- October 2022
ProductAssignment of MCS 224 | 2021-2022
Submission DateValid from 1st July 2021 to 31st October 2022
Assignment PdfDownload Now

How to get Artificial Intelligence and Machine Learning, MCS 224 Solved Assignment?

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If someone is unable to solve the assignment, so don’t worry we have solved this assignment for you, you only need to click the link one by one and get all the answers to this assignment sequence-wise. And if not, then our team is working on it and you will be available soon.

The answer of MCS 224 | Artificial Intelligence and Machine Learning | Solved Assignment 2021-2022:

Important Notes:

1. Submit your assignments to the Coordinator of your Study Centre on or before the due date.
2. Assignment submission before due dates is compulsory to become eligible for appearing in corresponding Term End Examinations. For further details, please refer to Programme Guide of Master of Computer Applications (MCA _NEW).
3. To become eligible for appearing the Term End Practical Examination for the lab courses, it is essential to fulfill the minimum attendance requirements as well as submission of assignments (on or before the due date). For further details, please refer to the Programme Guide of Master of Computer Applications (MCA _NEW).
4. The viva voce is compulsory for the assignments. For any course, if a student submitted the assignment and not attended the viva-voce, then the assignment is treated as not successfully completed and would be marked as ZERO.

This assignment has sixteen questions of 5 Marks each, answer all questions. Rest 20 marks are for viva voce. You may use illustrations and diagrams to enhance the explanations. Please go through the guidelines regarding assignments given in the Programme Guide for the format of presentation.

1. Differentiate between Artificial Intelligence, Machine Learning and Deep learning.

2. Briefly discuss the concept of single agent search and two agent search in Artificial Intelligence.

3. Explain A* and AO* search with the help of suitable example.

4. Compare and contrast the predicate logic and propositional logic, give suitable example for each. Also write De Morgan’s laws for both.

5. Discuss the concept of Resolution with the help of suitable example.

6. Explain the concept of semantic nets with the help of suitable diagram.

7. What do you understand by Bayesian Theory, with reference to its utility in artificial intelligence?

8. What are Fuzzy sets? How do they differ from Rough sets?

9. Write short notes on following:
a) Reinforcement Learning,
b) Ensemble method

10. Differentiate between Supervised learning and Unsupervised learning, give suitable example for each.

11. Discuss the concept of Linear regression and its utility in context of machine learning.

12. Explain the functioning of neural networks, with the help of suitable diagram.

13. Give brief introduction to the concept of feature selection and feature extraction, give suitable example for each.

14. What is pattern search? Discuss the Apriori Algorithm for pattern search.

15. What 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.

16. Write Python code to exhibit data classification through K-Nearest Neighbour (K-NN) algorithm.

Wrapped Up

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