Natural Language Processing (NLP) Lab Tasks

This repository contains various lab tasks and exercises related to Natural Language Processing (NLP) using Python. The projects cover a wide range of NLP topics, including text preprocessing, vectorization, text classification, and more.

Table of Contents

1. Introduction
2. Projects

Introduction

Natural Language Processing (NLP) is a field of artificial intelligence that focuses on the interaction between computers and humans through natural language. This repository contains multiple lab tasks demonstrating different aspects and applications of NLP.

Projects

1. Text Preprocessing: Scripts for normalizing and cleaning text data.
   • Text Normalization.ipynb
2. Vectorization: Converting text data into numerical vectors.
   • Vectorization.ipynb
   • MinEdit_TF-IDF.ipynb
3. Text Classification: Implementations of text classification using various models.
   • CNN_Text_Classification.ipynb
4. Regular Expressions: Using regex for text manipulation.
   • regular_expressions.ipynb
5. Lab Exercises: Various NLP lab tasks.
   • 2020337_1.ipynb
   • 2020337_2.ipynb
   • 2020337_3.ipynb
   • 2020337_4.ipynb
   • 2020337_NLP_Lab_Final.ipynb

Requirements

To run the code in this repository, ensure you have the following packages installed:

• Python 3.x
• scikit-learn
• pandas
• numpy
• nltk
• gensim
• textblob