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CineMood AI is an AI-powered movie review sentiment analysis tool built using Streamlit and TensorFlow. It classifies user-submitted movie reviews into different sentiment categories, ranging from extremely positive to strongly negative. The app features a sleek UI, animations, and an interactive confidence meter for better user engagement.

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Subrat1920/IMDB-Sentiment-Analysis

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IMDB Sentiment Analysis

🎬 Overview

CineMood AI is an AI-powered movie review sentiment analysis tool built using Streamlit and TensorFlow. It classifies user-submitted movie reviews into different sentiment categories, ranging from extremely positive to strongly negative. The app features a sleek UI, animations, and an interactive confidence meter for better user engagement.

🚀 Features

  • Deep Learning Sentiment Analysis using a pre-trained Keras model
  • Beautiful, Animated UI with CSS enhancements
  • Real-time Prediction with confidence score visualization
  • Interactive Elements including particle animations

🛠️ Installation

1. Clone the Repository

git clone https://github.com/Subrat1920/IMDB-Sentiment-Analysis.git
cd IMDB-Sentiment-Analysis

2. Create a Virtual Environment

python -m venv venv
source venv/bin/activate  # For MacOS/Linux
venv\Scripts\activate  # For Windows

3. Install Dependencies

pip install -r requirements.txt

4. Download the Pre-trained Model

Ensure that your Keras sentiment model (sentiment_model.keras) is placed inside the Notebook/keras_models/ directory.

5. Run the Application

streamlit run app.py

📝 Usage

  1. Enter a movie review in the text box.
  2. Click the "🔮 Analyze Sentiment" button.
  3. View the prediction result with an emoji, confidence level, and visual indicator.

📦 Dependencies

  • streamlit
  • tensorflow
  • numpy
  • scipy

🤝 Contributing

Feel free to fork this repository and submit pull requests. Contributions are welcome!

About

CineMood AI is an AI-powered movie review sentiment analysis tool built using Streamlit and TensorFlow. It classifies user-submitted movie reviews into different sentiment categories, ranging from extremely positive to strongly negative. The app features a sleek UI, animations, and an interactive confidence meter for better user engagement.

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