Movie Recommender System

Description

The Movie Recommender System is a web application designed to provide personalized movie recommendations to users. Utilizing Django as the web framework and machine learning algorithms, this application ensures accurate recommendations based on user preferences and viewing history.

Features

• User Authentication: Users can register, log in, and log out.
• Movie Recommendations: Personalized movie recommendations based on user ratings and preferences.
• Movie Search: Search functionality to find movies by title.
• Admin Interface: Admin panel to manage movies and user accounts.

Technologies Used

• Languages:
  • Python
  • HTML/CSS
  • JavaScript
• Libraries:
  • Django
  • pandas
  • numpy
  • scikit-learn
  • scipy

Setup and Installation

Prerequisites

• Python 3.x
• pip (Python package installer)

Installation Steps

1. Clone the Repository:

   git clone https://github.com/<your-username>/Movie-Recommender-System.git

2. Navigate to the Project Directory:

   cd Movie-Recommender-System-master

3. Create and Activate Virtual Environment:

   python -m venv env
   source env/bin/activate  # On Windows use `env\Scripts\activate`

4. Install Required Packages:

   pip install -r requirements.txt

5. Navigate to the Source Directory:

   cd src

6. Apply Migrations:

   python manage.py migrate

7. Run the Development Server:

   python manage.py runserver

Usage

After completing the installation steps, access the application at http://127.0.0.1:8000/.

Screenshots

Login Page

The Login Page allows users to log in with their username and password.

Main Page

The Main Page displays a list of movies available for rating. Users can search for specific movies using the search bar.

Recommendation Page

The Recommendation Page shows personalized movie recommendations based on user ratings and preferences.

Rating Page

The Rating Page allows users to rate a specific movie. The URL includes the movie ID, e.g., http://127.0.0.1:8000/1/.

Sign Up Page

The Sign Up Page allows new users to create an account by providing a username, email address, and password.

Contributing

To contribute to the Movie Recommender System, follow these steps:

1. Fork the Repository: Create a copy of the repository on your GitHub account.
2. Create a New Branch: Make a new branch for your feature or bugfix.

   git checkout -b feature-name

3. Make Changes: Implement your feature or bugfix.
4. Commit Changes: Commit your changes with a descriptive message.

   git commit -m "Description of changes"

5. Push Changes: Push your changes to your forked repository.

   git push origin feature-name

6. Submit a Pull Request: Go to the original repository and create a pull request with your changes.

Code of Conduct

All contributors are expected to adhere to the project's Code of Conduct, which promotes a welcoming and inclusive environment.

License

This project is licensed under the MIT License. See the LICENSE file for details.