Sentiment Analysis Model using Classification and Vector Spaces

Overview

This project implements a sentiment analysis model using classification techniques and vector spaces in Natural Language Processing (NLP). The goal is to analyze and classify the sentiment (positive, negative, neutral) of text data.

Features

• Classification Techniques: Utilizes machine learning algorithms for sentiment classification.
• Vector Spaces: Implements vector space models to represent text data.
• NLP Techniques: Leverages Natural Language Processing techniques for text preprocessing and feature extraction.

Requirements

• Python 3.x
• Libraries: (list the libraries you are using, e.g., nltk, scikit-learn, etc.)
• Any specific hardware requirements, if applicable

Installation

1. Clone the repository:

   git clone https://github.com/your_username/sentiment-analysis.git
   cd sentiment-analysis