Artificial Intelligence and Machine Learning
1. Explain the significance of AI.
2. Explain the significance of ML.
3. Compare Supervised and Unsupervised learning.
4. What is Machine Learning? Explain the working of Machine Learning.
5. Compare AI with Data Science.
6. Explain the need of AI in Mechanical Engineering.
7. Write briefly the major milestones of Artificial Intelligence (AI).
8. Write briefly about Ancient History of Artificial Intelligence (AI).
9. What is PCA? How it is used for dimensionality reduction?
10.What is Reinforcement Learning? the concept with the help of
suitable examples and flow diagrams.
11.What is the difference between AI and ML?
12.What is Principal Component Analysis? Can we Use PCA for feature selection?
13.What is feature selection? Explain the role of feature selection in machine
learning.
14.What is a decision tree? How it is used for classification. Explain with suitable examples.
15.List the advantages and disadvantages of decision trees.
16.Define the following:
i. Input variable
ii. Leaf node
iii. Internal nodes
iv. Information Gain
v. Entropy
17.What is overfitting? Specify the reasons for overfitting.
18.Explain under fitting. What are the reasons for under fitting? How do we know if we are under fitting or over fitting?
19.What is meant by feature selection? Explain the term features selection ranking and its importance.
20.What is meant by embedded feature selection?
21.What is meant by greedy forward selection? What are the steps for greedy
algorithm.
22.Which attribute you will choose to split following dataset in to decision tree:
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