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Sentiment Analysis on Product Review

Home Page: https://share.streamlit.io/kehsihba19/sentiment-on-review/Frontend/main.py

Python 38.15% Jupyter Notebook 61.85%
python fastapi streamlit

sentiment-on-review's Introduction

Sentiment Analysis on Product Review

This is the repository for the Sentiment Analysis on Product Reviews for classifying positive and negative reviews.

Built Using Machine Learning

Streamlit App

forthebadge made-with-python

Project Breakdown

  • Training Model
  • Backend support to get prediction for a review using API
  • Frontend support for users to interact with API

  • Training Machine Learning Model

  • Fetching Data
  • Cleaning Data
  • Fitting the model for highest accuracy
  • Saving the model

  • ๐Ÿ‘‡ Checkout the jupyter notebook of the trained model

    Badge


    Backend Server

    The Backend server is written using Python Framework FastAPI and hosted on Heroku

  • Post request with product review will return a response about the type of rating

  • ๐Ÿ‘‡ Read More about the documentation of API

    Badge


    Frontend

    The Frontend is written using Python Framework Streamlit and hosted on Streamlit hosting service

  • Single Review Analysis
  • Multiple Review Analyis(File upload with format as csv)

  • ๐Ÿ‘‡ Checkout the website

    Badge


    UI Design


    ๐Ÿ›  Local Setup

    
    1. Clone the repo
    >> git clone repo_link
    
    2. Change your current directory to the repo
    >> cd directory_name
    
    3. Activate virtual environment
    >> $base> python -m venv venv
    >> $base> .\venv\Scripts\activate
    
    4. Run the backend server
    >> (venv) $base> cd Backend
    >> (venv) $base/Backend> pip install -r requirements.txt
    >> (venv) $base/Backend> uvicorn main:app --reload
    
    5. Run the frontend server(make sure to edit url for API calls to backend server url)
    >> (venv) $base> cd Frontend
    >> (venv) $base/Frontend> pip install -r requirements.txt
    >> (venv) $base/Frontend> streamlit run main.py
    
    

    Contributing

    Pull requests are welcome.

    For major changes, please open an issue first to discuss what you would like to change.

    Show some โค๏ธ and โญ the repo to support the project

    License

    GPL-3.0 License

    Star the Repo in case you liked it :)

    ยฉ kehsihba19

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