IMDB Review Sentiment Analysis 🎥🎭

This project focuses on analyzing the sentiment of IMDB movie reviews (positive or negative) using a Simple Recurrent Neural Network (RNN). The model processes the sequential nature of text data to predict the sentiment of a given review.

🚀 Features

• Sentiment analysis using Simple RNN.
• Preprocessing of IMDB movie review data.
• Model evaluation with accuracy and loss metrics.
• Visualizations of training performance (loss and accuracy).
• Easy-to-follow code for learning and replication.

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📊 Results

• Accuracy: ~85% on the test set.
• Loss: Tracked over 10 epochs.

Model Training Performance

Metric	Value
Train Accuracy	86%
Test Accuracy	84%
Epochs	10

🚧 Future Improvements

• Use more advanced architectures like LSTM, GRU, or Transformers.
• Explore data augmentation for better performance.
• Add a web-based interface for live predictions.
• Experiment with hyperparameter tuning for improved accuracy.