/Movies-Recommender-System

🎥 Personalized movie recommendations using content-based filtering

Primary LanguageJupyter NotebookApache License 2.0Apache-2.0

Movie Recommender System

This project implements a content-based movie recommender system using Streamlit. Given a selected movie, it provides personalized recommendations for similar movies based on their descriptions, genres, keywords, cast, and crew information.

Demo Images

Installation and Usage

  1. Clone the Repository:

    git clone https://github.com/hardikjp7/Movies-Recommender-System.git

  2. Navigate to Project Directory:

    cd Movies-Recommender-System

  3. Install Dependencies:

    pip install -r requirements.txt

  4. Run the Streamlit App:

    streamlit run app.py

  5. Open the Web Browser: Once the Streamlit app is running, open your web browser and go to http://localhost:8501 to access the Movie Recommender System.

Features

  • Allows users to select a movie from a dropdown menu.
  • Provides personalized movie recommendations based on the selected movie.
  • Displays movie posters along with their titles for easy visualization.
  • Fullscreen layout for an immersive experience.
  • Bigger poster size and bolder movie names for better visibility.

Note:

Ensure that you have obtained the necessary API key from The Movie Database (TMDb) and saved it securely before running the Streamlit app.

For more information and detailed documentation, please refer to the project's GitHub repository: Movies-Recommender-System