Create an elective advisory system for students based on the type of degree and field they are pursuing (e.g. M.Tech-CSE)
Find the best route from one city to another based on the given prolog based facts using DFS and Best First Search approach (consider admissible and consistent heuristics as additional facts)
Use Durable Rules library in Python to create a course advisory system based on student grades and interest
Machine Learning (ML) use case - to analyse data attributes, build and evaluate models with the goal of providing appropriate job roles to different users
Natural Language Processing (NLP) use case - to create an elective advisory system by taking verbose input from user, identifying key words and creating appropriate prolog facts to generate user-centric advisory results
- SWI-Prolog for Prolog programming
- Spyder Platform (Anaconda) for python module
- Jupyter Notebook for Machine Learning Task (aslo for generating code report)