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

Following Lab assignments have been added to this repo.

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.

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

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.

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.

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

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.

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.