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🎬 Sentiment Analysis Web App (IMDB Reviews)

🚀 Live Demo:- 👉 https://sentiment-analysis-3pcy8vhomecrfbnmpjmgqq.streamlit.app/


📌 Overview

Ever wondered how platforms like IMDB analyze lakhs of reviews and instantly tell whether a movie is good or bad?

This project solves exactly that.

👉 A Deep Learning-based Sentiment Analysis Web App
👉 Enter any movie review
👉 Get instant prediction → Positive ✅ / Negative ❌


🧠 How It Works

  • The model does not understand words directly
  • It converts text into numerical sequences
  • Then processes them using a Recurrent Neural Network (RNN)

Example:

"Not bad at all" → Positive ✅ "Terrible movie" → Negative ❌

👉 Unlike basic models, it understands context, not just keywords.


📊 Dataset

  • 50,000 IMDB movie reviews
  • 25,000 Positive
  • 25,000 Negative
  • Preprocessed and tokenized for training

⚙️ Tech Stack

  • 🐍 Python
  • 🤖 TensorFlow & Keras
  • 🔁 RNN (Recurrent Neural Network)
  • 🌐 Streamlit (for deployment)

🚀 Features

  • Real-time sentiment prediction
  • Simple & interactive UI
  • Handles contextual understanding
  • Deployed and accessible online

🖥️ Run Locally

  1. Clone the repository:

git clone https://github.com/ravicoder01/Sentiment-Analysis.git

  1. Navigate to project folder:

cd your-repo-name

  1. Install dependencies:

pip install -r requirements.txt

  1. Run the app:

streamlit run app.py


😅 Challenges Faced

  • TensorFlow installation issues
  • Version compatibility problems
  • Model loading errors during deployment

👉 But debugging these made the project stronger 💪


📸 Demo

Try it live here 👇
👉 https://sentiment-analysis-3pcy8vhomecrfbnmpjmgqq.streamlit.app/


🙌 Contributing

Contributions are welcome!

  • Fork the repo
  • Create a new branch
  • Make your changes
  • Submit a pull request

⭐ Support

If you found this project useful:

👉 Give it a star ⭐ on GitHub
👉 Share your feedback


📬 Connect

Feel free to reach out for collaboration or feedback!


#MachineLearning #DeepLearning #AI #Python #TensorFlow #Streamlit #RNN

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