Artificial Intelligence(CSE 202) Lab Work

Scripts, data sets and other files for the Lab Practical of Artificial Intelligence(CSE 202).

Following Lab assignments have been added to this repo.

Implementing POS tagging

The aim of this practical is to achieve Part of Speech(POS) tagging using HunPos(HMMs model) and CRF++(CRF model). All the other details can be seen in the sub-folder.

Chunking

All the details can be seen in the sub-folder.

Hidden Markov Model and Viterbi

The aim here is to deduce the tags, words, transition probabilities, emission probabilities, and prior probabilities using some training data and then use these to predict POS tags using Viterbi's Algorithm.

Linear and Logistic Regression

Basic Linear and Logistic Regression with any number of features support. Gradient Descent Algorithm is used for training the model. More details under the sub-folder.

Proposition Logic

Some utility classes and functions for evaluating PL expressions. Currently, support exists for five basic operators: NOT, OR, AND, ->, and <->

Using Stanford Parser

This task basically involves Stanford Parser. Both Phrase Structure and Dependency parsing were practiced in this task. I made a list of all useful commands; they can be seen in the sub-folder.

Phrase Structure to Dependency parsing and Karaka Relations

Using phrase struture trees generated by Stanford Parser, the task was to generate Dependency trees using some algorithm. The relations between words had to be Karaka Relations.