Movie-Recommendation-System

🎬 Movie Recommendation System

A content-based movie recommendation system that suggests similar movies based on user-selected titles. Built with Python and Streamlit, and containerized using Docker for easy deployment.

📌 Overview

This project leverages content-based filtering to recommend movies. By analyzing movie features, it computes similarities between movies and suggests titles that closely match the user’s selection.

🚀 Features

• Content-Based Filtering: Recommends movies similar to the selected title using cosine similarity.
• Interactive UI: Built with Streamlit for a user-friendly interface.
• Dockerized Deployment: Easily deployable using Docker containers.
• TMDb API Integration: Fetches movie details and posters using The Movie Database API.

🛠️ Technologies Used

• Programming Language: Python
• Web Framework: Streamlit
• API Integration: TMDb API
• Containerization: Docker (Docker image: tkdutta/movierecommender)

📂 Project Structure

movie_recommendation_system/
├── app/
│   ├── main.py
│   ├── utils.py
│   └── ...
├── Dockerfile
├── requirements.txt
├── .env.example
└── README.md

⚙️ Setup Instructions

1. Clone the Repository

   git clone https://github.com/tuhindutta/movie_recommendation_system.git
   cd movie_recommendation_system
   

2. Set Up Environment Variables Create a .env file in the root directory and add your TMDb API access token (API Read Access Token created in https://www.themoviedb.org/):

   ACCESS_TOKEN=your_tmdb_api_access_token
   

3. Build and Run the Docker Container

   docker run -d -p 8501:8501 --name movierecommender --env-file .env tkdutta/movierecommender:tag
   

   The application will be accessible at http://localhost:8501

🧪 Usage

Upon accessing the application:

1. Select a movie from the dropdown list.
2. Click on the “Recommend” button.
3. View a list of similar movies along with their posters and details.

🤝 Contributing

Contributions are welcome! Please fork the repository and submit a pull request for any enhancements or bug fixes. For more details and updates, visit the GitHub Repository.