AIMLDL Question Bank

 

Unit 1

1. What is artificial intelligence and machine learning? Explain in detail with real life examples. Explain the need of AI and ML

2. What are applications of AI and ML. Explain with example in detail

3. Explain the history of AI. Explain types of AI

4. Explain advantages and disadvantages of AI and ML. Explain ethical consideration of AI

Unit 2

1. Explain propositional logic in detail

2. Explain forward chaining and backward chaining

3. Explain Language, Semantics, and Reasoning

Unit 3

1. What is supervised machine learning and unsupervised machine learning

2. Explain different types of machine learning

3. What is regression? Explain simple linear regression with example

4. demonstrate multilinear regression with example

5. Demonstrate logistic regression with example. 

6. What is regression and classification problem. Explain with example.

7. Demonstrate unsupervised machine learning with clustering.

8. What is the clustering technique of ML? demonstrate KMeans clustering with an example

9. What is PCA? Explain the need of PCA

10. Demonstrate Principle component analysis with example

11. What  is model Evaluation metrics. Explain with example

12. Demonstrate data standardization and normalization with example

13. Demonstrate the LebelEncoding and OneHot encoding techniques using example

14. Demonstrate the support vector machine with example

15. Explain SVC. Explain the variour key terms used in SVM

16. Explain reinforcement learning. Explai the applications of reinforcement learning

17. Demonstrate the confusion matrix and classification report. Why is need of these techniques. How Accuracy is calculated

18. Explain the MSE, R squared error, Adjusted R-squared error with example.

Unit 4

1. What is deep learning? Explain the various techniques used in deep learning

2. Explain ANN, CNN  technique of deep learning

3. Explain the RNN and GAN techniques of DL

4. Explai the deep learning techniques with real life examples. Explain advantages and disadvantages

Unit 5

1. What is natural language processing? Explain the need of natural language processing

2. Explain various steps in natural language processing

3. Explain Tokenization, Stemming and Lemmatization techniques of NLP

4. Demonstrate the Feature extraction of NLP

5. What is text mining? Explain text preprocessing techniques

6. What is image processing? Explain the ML techniques used in image processing

7. What is computer vision? Explain the advantages and need of computer vision

8. What are chatbots?  Explain the advantages and need of Chatbots. Explain various ML techniques used in Chatbots