This project involves building a sentiment analysis model using Recurrent Neural Networks (RNN) to classify movie reviews from the IMDb dataset as either positive or negative. The IMDb dataset consists of 50,000 highly polarized movie reviews, with 25,000 labeled as positive and 25,000 as negative, making it an ideal dataset for binary sentiment classification tasks.
This project is hosted on - https://rnn-classification-4qyd35scpyeq4u9xjycxmd.streamlit.app/
- Clone this repo into your system.
- Create virtual environment using the command -
conda create -p myenv python==3.9.0- Now install all the packages which are listed in requirements.txt
pip install -r requirements.txt-
Now run all the cell in the Experiments.ipynb And Prediction.ipynb as per your need.
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To run on streamlit -
streamlit run main.pyFrontend Client: Streamlit Services
Model Used: RNN - Recurrent Neural Network
Dataset Used: IMDB Dataset
If you have any feedback or just to say Hi!, please reach out to me at mahobiashubham4@gmail.com