Movie Recommender System

Demo Video

Watch the Demo Video

Direct Link

Visit the Movie Recommender System

How to Use

1. Clone the repository to your local machine:

   git clone https://github.com/yourusername/movie-recommender-system.git
   cd movie-recommender-system

2. Install Required Packages:

   pip install -r requirements.txt

3. Run the STreamlit App:

   streamlit run app.py
   

Functionalities

• Recommends movies based on user's selection and preferences.
• Provides two recommendation options: based on movies and based on genres.
• Displays movie posters and titles for the recommended movies.

Technologies & Concepts required

• Python
• Streamlit
• scikit-learn
• requests
• Cosine Similarity
• Moduler Coding

Key Points

• Developed by Arya Chakraborty and Rituparno Das students of VIT-AP.
• The application utilizes the TMDB API to fetch movie data and posters.
• The recommendation system uses TF-IDF vectorization and cosine similarity for efficient movie suggestions.
• Users can select movies to get recommendations or choose genres for genre-based recommendations.
• The Streamlit app's layout is customized using HTML and CSS for an appealing user interface.
• The app is deployed using Streamlit sharing.
• Feel free to explore and enjoy movie recommendations tailored to your taste!

Credits

            
Arya Chakraborty                                             Rituparno Das