CSE241N-Artificial-Intelligence
This repository contains the solutions to the programming assignments of CSE241N-Artificial-Intelligence - IIT (BHU), Varanasi. The following assignments have been added to the repository
Assignment 0 - Installation Guide and Tools
Basic Installations and guide to use various tools.
Assignment 1 - Sudoku solver
Implement how to solve a Sudoku puzzle using backtracking.
You are also required to look into and implement one more algorihm. (Like CSP : Constraints Satfisfaction Problem)
Assignment 2 - Linear Regression
Implement a basic linear regression model that is used to fit 2-D data. Further details given in sub folder.
Assignment 3 - Logistic Regression
Implement a binary classification model for text documents using Logistic Regression. Feature calculation is done from the training data using Bag Of Words and Tf-idf. Futher details given in the sub folder.
Assignment 4 - K-Means Clustering
Implement an unsupervised learning model for text documents using K-Means Clustering. Feature calculation is done from the training data using Bag Of Words and Tf-idf.
Assignment 5 - Part-of-Speech Tagging using HMMs and Viterbi Algorithm
Implement the Viterbi algorithm and a Hidden Markov Model to assign Part-of-speech tags to words in a given sentence by caculating transition and emission probablities using the training data. Futher details given in sub folder.
Assignment 6 - Exam Schedular
Implement proper problem statement and ways to deal with such problems.
Assignment 7 - Logic
In this assignment, you will implement classes for Logic Programming and implement Resolution-Refutation for automatic theorem proving.
Assignment 8 - Guided Search
In this assignment, you will implement the following guided search algorithms.
- Hill Climbing Search
- Best First Search
- Beam Search
- A* Search
- Depth First Search
- Breadth First Search