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This project leverages machine learning techniques to analyze and classify sentiments from text data. Using Python and popular libraries like NLTK and Scikit-learn, it processes and evaluates textual input to determine sentiment polarity—positive, negative, or neutral. It’s designed to provide valuable insights into user opinions and feedback.

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Satwikmbadiger/Senti-meter

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Senti Meter

Deployment Instructions

⚠️ Make sure python is installed in the system.

Install pipenv ( A virtual environment manager. )

pip install pipenv

Install required packages.

pipenv install

Train the models.

pipenv run train.py

Run the application

pipenv run app.py

Your application will be running on localhost by default.

To close the server press Ctrl-C

Thanks for using our application. ! 😃

⚠️ To remove the virtual enviromnent

pipenv --rm

About

This project leverages machine learning techniques to analyze and classify sentiments from text data. Using Python and popular libraries like NLTK and Scikit-learn, it processes and evaluates textual input to determine sentiment polarity—positive, negative, or neutral. It’s designed to provide valuable insights into user opinions and feedback.

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