Skip to content

Classifying the input data into 5 classes of Sentiments namely Highly Negative, Negative, Neutral, Positive, Highly Positive

Notifications You must be signed in to change notification settings

raza8899/sentimentAnalysis

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

2 Commits
 
 
 
 
 
 
 
 

Repository files navigation

Project Title

Sentiment Analysis

Getting Started

To get started with this code, clone the repository and start Jupyter Notebook in your computer

Prerequisites

Install these Python packages using pip

pandas, numpy, matplotlib, seaborn, nltk, sklearn

Run the whole code and check for Accuracy of different machine learning models

You can add more training data for better accuracy

About

Classifying the input data into 5 classes of Sentiments namely Highly Negative, Negative, Neutral, Positive, Highly Positive

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published