Sentiment Analysis Using LSTM

This project leverages deep learning techniques to perform sentiment analysis on textual data. Using TensorFlow and the IMDB dataset, it trains an LSTM-based neural network to classify movie reviews as positive or negative.

Key Features

• LSTM Model Architecture: Implements a Sequential model with layers such as Embedding, LSTM, Dense, and Dropout for robust sentiment classification.
• IMDB Dataset Utilization: Preprocessed and padded sequences for training and testing using the IMDB dataset.
• Data Preprocessing: Includes tokenization and sequence padding for handling text data efficiently.
• Visualizations: Generates graphs to visualize training accuracy, loss, and other metrics.
• User-Friendly Design: Structured for easy replication and experimentation.

Installation

Follow these steps to set up the project on your local machine:

1. Clone the repository:

Clone the repository to your local machine:

git clone https://github.com/himanibhammar/CinemaSentiment.git
cd CinemaSentiment