AI&ML Practical Exercises

PRACTICAL EXERCISES:

1. Implementation of Uninformed search algorithms (BFS, DFS)

2. Implementation of Informed search algorithms (A*, memory-bounded A*)

3. Implement naïve Bayes models

4. Implement Bayesian Networks

5. Build Regression models

6. Build decision trees and random forests

7. Build SVM models

8. Implement ensembling techniques

9. Implement clustering algorithms THROUGH KNOWLEDGE

10. Implement EM for Bayesian networks

11. Build simple NN models

12. Build deep learning NN models