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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

    • 👇 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

    • 👇 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)

    • 👇 Checkout the website

    Badge

    UI Design

    🛠 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 ❤️ and ⭐ the repo to support the project

    License

    GPL-3.0 License

    Star the Repo in case you liked it :)

    © kehsihba19